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2,234 results on '"Kim, Woo Jin"'

1. Multi-Site Class-Incremental Learning with Weighted Experts in Echocardiography

Author

Bransby, Kit M., Kim, Woo-jin Cho, Oliveira, Jorge, Thorley, Alex, Beqiri, Arian, Gomez, Alberto, and Chartsias, Agisilaos

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence
Abstract

Building an echocardiography view classifier that maintains performance in real-life cases requires diverse multi-site data, and frequent updates with newly available data to mitigate model drift. Simply fine-tuning on new datasets results in "catastrophic forgetting", and cannot adapt to variations of view labels between sites. Alternatively, collecting all data on a single server and re-training may not be feasible as data sharing agreements may restrict image transfer, or datasets may only become available at different times. Furthermore, time and cost associated with re-training grows with every new dataset. We propose a class-incremental learning method which learns an expert network for each dataset, and combines all expert networks with a score fusion model. The influence of ``unqualified experts'' is minimised by weighting each contribution with a learnt in-distribution score. These weights promote transparency as the contribution of each expert is known during inference. Instead of using the original images, we use learned features from each dataset, which are easier to share and raise fewer licensing and privacy concerns. We validate our work on six datasets from multiple sites, demonstrating significant reductions in training time while improving view classification performance., Comment: Accepted for Oral at MICCAI workshop ASMUS-2024

Published
2024

2. ProDepth: Boosting Self-Supervised Multi-Frame Monocular Depth with Probabilistic Fusion

Author

Woo, Sungmin, Lee, Wonjoon, Kim, Woo Jin, Lee, Dogyoon, and Lee, Sangyoun

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Self-supervised multi-frame monocular depth estimation relies on the geometric consistency between successive frames under the assumption of a static scene. However, the presence of moving objects in dynamic scenes introduces inevitable inconsistencies, causing misaligned multi-frame feature matching and misleading self-supervision during training. In this paper, we propose a novel framework called ProDepth, which effectively addresses the mismatch problem caused by dynamic objects using a probabilistic approach. We initially deduce the uncertainty associated with static scene assumption by adopting an auxiliary decoder. This decoder analyzes inconsistencies embedded in the cost volume, inferring the probability of areas being dynamic. We then directly rectify the erroneous cost volume for dynamic areas through a Probabilistic Cost Volume Modulation (PCVM) module. Specifically, we derive probability distributions of depth candidates from both single-frame and multi-frame cues, modulating the cost volume by adaptively fusing those distributions based on the inferred uncertainty. Additionally, we present a self-supervision loss reweighting strategy that not only masks out incorrect supervision with high uncertainty but also mitigates the risks in remaining possible dynamic areas in accordance with the probability. Our proposed method excels over state-of-the-art approaches in all metrics on both Cityscapes and KITTI datasets, and demonstrates superior generalization ability on the Waymo Open dataset., Comment: Accepted by ECCV 2024. Project Page: https://sungmin-woo.github.io/prodepth/

Published
2024

3. BackMix: Mitigating Shortcut Learning in Echocardiography with Minimal Supervision

Author

Bransby, Kit Mills, Beqiri, Arian, Kim, Woo-Jin Cho, Oliveira, Jorge, Chartsias, Agisilaos, and Gomez, Alberto

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence
Abstract

Neural networks can learn spurious correlations that lead to the correct prediction in a validation set, but generalise poorly because the predictions are right for the wrong reason. This undesired learning of naive shortcuts (Clever Hans effect) can happen for example in echocardiogram view classification when background cues (e.g. metadata) are biased towards a class and the model learns to focus on those background features instead of on the image content. We propose a simple, yet effective random background augmentation method called BackMix, which samples random backgrounds from other examples in the training set. By enforcing the background to be uncorrelated with the outcome, the model learns to focus on the data within the ultrasound sector and becomes invariant to the regions outside this. We extend our method in a semi-supervised setting, finding that the positive effects of BackMix are maintained with as few as 5% of segmentation labels. A loss weighting mechanism, wBackMix, is also proposed to increase the contribution of the augmented examples. We validate our method on both in-distribution and out-of-distribution datasets, demonstrating significant improvements in classification accuracy, region focus and generalisability. Our source code is available at: https://github.com/kitbransby/BackMix, Comment: Accepted at MICCAI 2024 (Pre-print)

Published
2024

6. CEO to the Rescue: Residential Proximity of Private Firm CEOs and the Evolution of Corporate Profitability

Author

KIM, WOO JIN and YANG, DONG-RYUNG

Subjects
CEO, Corporate Governance, Geographic, Commitment, Social Sciences, Industries. Land use. Labor, HD28-9999, Economic theory. Demography, HB1-3840
Abstract

This paper documents how the net profit margin of private firms improves when the CEOs of the companies relocate their primary residence to be closer to the corporate headquarters. By reviewing 127 Korean non-public companies belonging to 66 private business groups, we find that the top managers move closer to the headquarters when the profitability of the firms has recently deteriorated. A one basis point decline in the margin causes CEOs to relocate their homes approximately two kilometers closer to their corporate headquarters. The profit margin rebounds after their relocation. This finding implies that physical proximity can serve as a proxy for personal commitment.

Published
2016
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8. Size‐Induced Ferroelectricity in Antiferroelectric Oxide Membranes

Author

Xu, Ruijuan, Crust, Kevin J, Harbola, Varun, Arras, Rémi, Patel, Kinnary Y, Prosandeev, Sergey, Cao, Hui, Shao, Yu‐Tsun, Behera, Piush, Caretta, Lucas, Kim, Woo Jin, Khandelwal, Aarushi, Acharya, Megha, Wang, Melody M, Liu, Yin, Barnard, Edward S, Raja, Archana, Martin, Lane W, Gu, X Wendy, Zhou, Hua, Ramesh, Ramamoorthy, Muller, David A, Bellaiche, Laurent, and Hwang, Harold Y

Subjects
Macromolecular and Materials Chemistry, Chemical Sciences, Physical Chemistry, Engineering, Physical Sciences, Materials Engineering, Affordable and Clean Energy, antiferroelectric materials, membranes, phase transition, size effects, sodium niobate, Nanoscience & Nanotechnology, Chemical sciences, Physical sciences
Abstract

Despite extensive studies on size effects in ferroelectrics, how structures and properties evolve in antiferroelectrics with reduced dimensions still remains elusive. Given the enormous potential of utilizing antiferroelectrics for high-energy-density storage applications, understanding their size effects will provide key information for optimizing device performances at small scales. Here, the fundamental intrinsic size dependence of antiferroelectricity in lead-free NaNbO3 membranes is investigated. Via a wide range of experimental and theoretical approaches, an intriguing antiferroelectric-to-ferroelectric transition upon reducing membrane thickness is probed. This size effect leads to a ferroelectric single-phase below 40 nm, as well as a mixed-phase state with ferroelectric and antiferroelectric orders coexisting above this critical thickness. Furthermore, it is shown that the antiferroelectric and ferroelectric orders are electrically switchable. First-principle calculations further reveal that the observed transition is driven by the structural distortion arising from the membrane surface. This work provides direct experimental evidence for intrinsic size-driven scaling in antiferroelectrics and demonstrates enormous potential of utilizing size effects to drive emergent properties in environmentally benign lead-free oxides with the membrane platform.

Published
2023

9. Pixel-Level Equalized Matching for Video Object Segmentation

Author

Cho, Suhwan, Kim, Woo Jin, Cho, MyeongAh, Lee, Seunghoon, Lee, Minhyeok, Park, Chaewon, and Lee, Sangyoun

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Feature similarity matching, which transfers the information of the reference frame to the query frame, is a key component in semi-supervised video object segmentation. If surjective matching is adopted, background distractors can easily occur and degrade the performance. Bijective matching mechanisms try to prevent this by restricting the amount of information being transferred to the query frame, but have two limitations: 1) surjective matching cannot be fully leveraged as it is transformed to bijective matching at test time; and 2) test-time manual tuning is required for searching the optimal hyper-parameters. To overcome these limitations while ensuring reliable information transfer, we introduce an equalized matching mechanism. To prevent the reference frame information from being overly referenced, the potential contribution to the query frame is equalized by simply applying a softmax operation along with the query. On public benchmark datasets, our proposed approach achieves a comparable performance to state-of-the-art methods.

Published
2022

10. Left Ventricle Contouring of Apical Three-Chamber Views on 2D Echocardiography

Author

Gomez, Alberto, Porumb, Mihaela, Mumith, Angela, Judge, Thierry, Gao, Shan, Kim, Woo-Jin Cho, Oliveira, Jorge, and Chartsias, Agis

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition
Abstract

We propose a new method to automatically contour the left ventricle on 2D echocardiographic images. Unlike most existing segmentation methods, which are based on predicting segmentation masks, we focus at predicting the endocardial contour and the key landmark points within this contour (basal points and apex). This provides a representation that is closer to how experts perform manual annotations and hence produce results that are physiologically more plausible. Our proposed method uses a two-headed network based on the U-Net architecture. One head predicts the 7 contour points, and the other head predicts a distance map to the contour. This approach was compared to the U-Net and to a point based approach, achieving performance gains of up to 30\% in terms of landmark localisation (<4.5mm) and distance to the ground truth contour (<3.5mm)., Comment: Submitted to MICCAI-ASMUS 2022

Published
2022

12. Character of the 'normal state' of the nickelate superconductors

Author

Lee, Kyuho, Wang, Bai Yang, Osada, Motoki, Goodge, Berit H., Wang, Tiffany C., Lee, Yonghun, Harvey, Shannon, Kim, Woo Jin, Yu, Yijun, Murthy, Chaitanya, Raghu, Srinivas, Kourkoutis, Lena F., and Hwang, Harold Y.

Subjects
Condensed Matter - Superconductivity
Abstract

The occurrence of superconductivity in proximity to various strongly correlated phases of matter has drawn extensive focus on their normal state properties, to develop an understanding of the state from which superconductivity emerges. The recent finding of superconductivity in layered nickelates raises similar interests. However, transport measurements of doped infinite-layer nickelate thin films have been hampered by materials limitations of these metastable compounds - in particular, a relatively high density of extended defects. Here, by moving to a substrate (LaAlO$_{3}$)$_{0.3}$(Sr$_{2}$TaAlO$_{6}$)$_{0.7}$ which better stabilizes the growth and reduction conditions, we can synthesize the doping series of Nd$_{1-x}$Sr$_{x}$NiO$_{2}$ essentially free from extended defects. This enables the first examination of the 'intrinsic' temperature and doping dependent evolution of the transport properties. The normal state resistivity exhibits a low-temperature upturn in the underdoped regime, linear behavior near optimal doping, and quadratic temperature dependence for overdoping. This is strikingly similar to the copper oxides, despite key distinctions - namely the absence of an insulating parent compound, multiband electronic structure, and a Mott-Hubbard orbital alignment rather than the charge-transfer insulator of the copper oxides. These results suggest an underlying universality in the emergent electronic properties of both superconducting families.

Published
2022
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24. Development and Application of an Active Pharmacovigilance Framework Based on Electronic Healthcare Records from Multiple Centers in Korea

Author

Choe, Seon, Lee, Suhyun, Park, Chan Hee, Lee, Jeong Hoon, Kim, Hyo Jung, Byeon, Sun-ju, Choi, Jeong-Hee, Yang, Hyeon-Jong, Sim, Da Woon, Cho, Bum-Joo, Koo, Hoseok, Kang, Min-Gyu, Jeong, Ji Bong, Choi, In Young, Kim, Sae-Hoon, Kim, Woo Jin, Jung, Jae-Woo, Lhee, Sang-Hoon, Ko, Young-Jin, Park, Hye-Kyung, Kang, Dong Yoon, and Kim, Ju Han

Published
2023
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29. Burden of Uncontrolled Severe Asthma With and Without Elevated Type-2 Inflammatory Biomarkers

Author

del Olmo, Ricardo, Anderson, Gary, Reddel, Helen, Rabahi, Marcelo, McIvor, Andrew, Sadatsafavi, Mohsen, Weinreich, Ulla, Burgel, Pierre-Régis, Devouassoux, Gilles, Papi, Alberto, Inoue, Hiromasa, Rendon, Adrián, van den Berge, Maarten, Beasley, Richard, García-Navarro, Alvar Agusti, Faner, Rosa, Rivera, José Olaguibel, Janson, Christer, Bilińska-Izydorczyk, Magdalena, Fagerås, Malin, Fihn-Wikander, Titti, Franzén, Stefan, Keen, Christina, Ostridge, Kristoffer, Chalmers, James, Harrison, Timothy, Pavord, Ian, Price, David, Azim, Adnan, Belton, Laura, Blé, Francois-Xavier, Erhard, Clement, Gairy, Kerry, Hughes, Rod, Lassi, Glenda, Müllerová, Hana, Rapsomaniki, Eleni, Scott, Ian Christopher, Chipps, Bradley, Christenson, Stephanie, Make, Barry, Tomaszewski, Erin, Benhabib, Gabriel, Ruiz, Xavier Bocca, Lisanti, Raul Eduardo, Marino, Gustavo, Mattarucco, Walter, Nogueira, Juan, Parody, Maria, Pascale, Pablo, Rodriguez, Pablo, Silva, Damian, Svetliza, Graciela, Victorio, Carlos F., Rolon, Roxana Willigs, Yañez, Anahi, Baines, Stuart, Bowler, Simon, Bremner, Peter, Bull, Sheetal, Carroll, Patrick, Chaalan, Mariam, Farah, Claude, Hammerschlag, Gary, Hancock, Kerry, Harrington, Zinta, Katsoulotos, Gregory, Kim, Joshua, Langton, David, Lee, Donald, Peters, Matthew, Prassad, Lakshman, Sajkov, Dimitar, Santiago, Francis, Simpson, Frederick Graham, Tai, Sze, Thomas, Paul, Wark, Peter, Delfini Cançado, José Eduardo, Cunha, Thúlio, Lima, Marina, Cardoso, Alexandre Pinto, FitzGerald, J. Mark, Anees, Syed, Bertley, John, Bell, Alan, Cheema, Amarjit, Chouinard, Guy, Csanadi, Michael, Dhar, Anil, Dhillon, Ripple, Kanawaty, David, Kelly, Allan, Killorn, William, Landry, Daniel, Luton, Robert, Mandhane, Piushkumar, Pek, Bonavuth, Petrella, Robert, Stollery, Daniel, Wang, Chen, Chen, Meihua, Chen, Yan, Gu, Wei, Christopher Hui, Kim Ming, Li, Manxiang, Li, Shiyue, Lijun, Ma, Qin, Guangyue, Song, Weidong, Tan, Wei, Tang, Yijun, Wang, Tan, Wen, Fuqiang, Wu, Feng, Xiang, PingChao, Xiao, Zuke, Xiong, Shengdao, Yang, Jinghua, Yang, Jingping, Zhang, Caiqing, Zhang, Min, Zhang, Ping, Zhang, Wei, Zheng, Xiaohe, Zhu, Dan, Bueno, Carlos Matiz, Grimaldos, Fabio Bolivar, Arboleda, Alejandra Cañas, Molina de Salazar, Dora, Bendstrup, Elisabeth, Hilberg, Ole, Kjellerup, Carsten, Raherison, Chantal, Bonniaud, Philippe, Brun, Olivier, Chouaid, Christos, Couturaud, Francis, de Blic, Jacques, Debieuvre, Didier, Delsart, Dominique, Demaegdt, Axelle, Demoly, Pascal, Deschildre, Antoine, Egron, Carole, Falchero, Lionel, Goupil, François, Kessler, Romain, Le Roux, Pascal, Mabire, Pascal, Mahay, Guillaume, Martinez, Stéphanie, Melloni, Boris, Moreau, Laurent, Riviere, Emilie, Roux-Claudé, Pauline, Soulier, Michel, Vignal, Guillaume, Yaici, Azzedine, Bals, Robert, Aries, Sven Philip, Beck, Ekkehard, Deimling, Andreas, Feimer, Jan, Grimm-Sachs, Vera, Groth, Gesine, Herth, Felix, Hoheisel, Gerhard, Kanniess, Frank, Lienert, Thomas, Mronga, Silke, Reinhardt, Jörg, Schlenska, Christian, Stolpe, Christoph, Teber, Ishak, Timmermann, Hartmut, Ulrich, Thomas, Velling, Peter, Wehgartner-Winkler, Sabina, Welling, Juergen, Winkelmann, Ernst-Joachim, Barbetta, Carlo, Braido, Fulvio, Cardaci, Vittorio, Clini, Enrico Maria, Costantino, Maria Teresa, Cuttitta, Giuseppina, di Gioacchino, Mario, Fois, Alessandro, Foschino-Barbaro, Maria Pia, Gammeri, Enrico, Inchingolo, Riccardo, Lavorini, Federico, Molino, Antonio, Nucera, Eleonora, Patella, Vincenzo, Pesci, Alberto, Ricciardolo, Fabio, Rogliani, Paola, Sarzani, Riccardo, Vancheri, Carlo, Vincenti, Rigoletta, Endo, Takeo, Fujita, Masaki, Hara, Yu, Horiguchi, Takahiko, Hosoi, Keita, Ide, Yumiko, Inomata, Minehiko, Inoue, Koji, Inoue, Sumito, Kato, Motokazu, Kawasaki, Masayuki, Kawayama, Tomotaka, Kita, Toshiyuki, Kobayashi, Kanako, Koto, Hiroshi, Nishi, Koichi, Saito, Junpei, Shimizu, Yasuo, Shirai, Toshihiro, Sugihara, Naruhiko, Takahashi, Ken-ichi, Tashimo, Hiroyuki, Tomii, Keisuke, Yamada, Takashi, Yanai, Masaru, Rendon, Adrian, Javier, Ruth Cerino, Peregrina, Alfredo Domínguez, Corzo, Marco Fernández, Gonzalez, Efraín Montano, Ramírez-Venegas, Alejandra, Boersma, Willem, Djamin, R.S., Eijsvogel, Michiel, Franssen, Frits, Goosens, Martijn, Graat-Verboom, Lidwien, Veen, Johannes in 't, Janssen, Rob, Kuppens, Kim, van de Ven, Mario, Bakke, Per, Brunstad, Ole Petter, Einvik, Gunnar, Høines, Kristian Jong, Khusrawi, Alamdar, Oien, Torbjorn, Yoon, Ho Joo, Chang, Yoon-Seok, Cho, Young Joo, Hwang, Yong Il, Kim, Woo Jin, Koh, Young-Il, Lee, Byung-Jae, Lee, Kwan-Ho, Lee, Sang-Pyo, Lee, Yong Chul, Lim, Seong Yong, Min, Kyung Hun, Oh, Yeon-Mok, Park, Choon-Sik, Park, Hae-Sim, Park, Heung-Woo, Rhee, Chin Kook, Yoon, Hyoung-Kyu, Andújar, Rubén, Anoro, Laura, García, María Buendía, Mozo, Paloma Campo, Campos, Sergio, Maldonado, Francisco Casas, Martínez, Manuel Castilla, Serrano, Carolina Cisneros, Casanova, Lorena Comeche, Corbacho, Dolores, Del Campo Matías, Felix, Echave-Sustaeta, Jose, Corral, Gloria Francisco, Setién, Pedro Gamboa, Clemente, Marta García, Núñez, Ignacio García, Robaina, Jose García, Salmones, Mercedes García, Marín Trigo, Jose Maria, Fernandez, Marta Nuñez, Palomo, Sara Nuñez, Pérez de Llano, Luis, Bastida, Ana Pueyo, Rañó, Ana, González-Moro, José Rodríguez, Reig, Albert Roger, Garrido, José Velasco, Curiac, Dan, Lif-Tiberg, Cornelia, Luts, Anders, Råhlen, Lennart, Rustscheff, Stefan, Adams, Frances, Bradman, Drew, Broughton, Emma, Cosgrove, John, Flood-Page, Patrick, Fuller, Elizabeth, Hartley, David, Hattotuwa, Keith, Jones, Gareth, Lewis, Keir, McGarvey, Lorcan, Morice, Alyn, Pandya, Preeti, Patel, Manish, Roy, Kay, Sathyamurthy, Ramamurthy, Thiagarajan, Swaminathan, Turner, Alice, Vestbo, Jorgen, Wedzicha, Wisia, Wilkinson, Tom, Wilson, Pete, Al-Asadi, Lo’Ay, Anholm, James, Averill, Francis, Bansal, Sandeep, Baptist, Alan, Campbell, Colin, Campos, Michael A., Crook, Gretchen, DeLeon, Samuel, Eid, Alain, Epstein, Ellen, Fritz, Stephen, Harris, Hoadley, Hewitt, Mitzie, Holguin, Fernando, Hudes, Golda, Jackson, Richard, Kaufman, Alan, Kaufman, David, Klapholz, Ari, Krishna, Harshavardhan, Lee, Daria, Lin, Robert, Maselli-Caceres, Diego, Mehta, Vinay, Moy, James N., Nwokoro, Ugo, Parikh, Purvi, Parikh, Sudhir, Perrino, Frank, Ruhlmann, James, Sassoon, Catherine, Settipane, Russell A., Sousa, Daniel, Sriram, Peruvemba, Wachs, Richard, Ding, Bo, Chen, Stephanie, Quinton, Anna, Cook, William, and Reddel, Helen K.

Published
2024
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32. Insulator-to-Metal Crossover near the Edge of the Superconducting Dome in Nd$_{1-x}$Sr$_x$NiO$_2$

Author

Hsu, Yu-Te, Wang, Bai Yang, Berben, Maarten, Li, Danfeng, Lee, Kyuho, Duffy, Caitlin, Ottenbros, Thom, Kim, Woo Jin, Osada, Motoki, Wiedmann, Steffen, Hwang, Harold Y., and Hussey, Nigel E.

Subjects
Condensed Matter - Superconductivity, Condensed Matter - Strongly Correlated Electrons
Abstract

We report a systematic magnetotransport study of superconducting infinite-layer nickelate thin films Nd$_{1-x}$Sr$_x$NiO$_2$ with $0.15 \leq x \leq 0.225$. By suppressing superconductivity with out-of-plane magnetic fields up to 37.5 T, we find that the normal state resistivity of Nd$_{1-x}$Sr$_x$NiO$_2$ is characterized by a crossover from a metallic $T^2$-behavior to an insulating log(1/$T$)-behavior for all $x$ except $x = 0.225$, at which the resistivity is predominantly metallic. The log(1/$T$)-behavior is found to be robust against magnetic fields, inconsistent with scenarios involving localization or Kondo scattering, and points to an anomalous insulating state possibly driven by strong correlations. In the metallic state, we find no evidence for non-Fermi-liquid behavior arising from proximity to a putative quantum critical point located inside the superconducting dome.

Published
2021

33. Asymmetric Contour Uncertainty Estimation for Medical Image Segmentation

Author

Judge, Thierry, Bernard, Olivier, Cho Kim, Woo-Jin, Gomez, Alberto, Chartsias, Agisilaos, Jodoin, Pierre-Marc, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Greenspan, Hayit, editor, Madabhushi, Anant, editor, Mousavi, Parvin, editor, Salcudean, Septimiu, editor, Duncan, James, editor, Syeda-Mahmood, Tanveer, editor, and Taylor, Russell, editor

Published
2023
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37. Unsupervised Video Anomaly Detection via Normalizing Flows with Implicit Latent Features

Author

Cho, MyeongAh, Kim, Taeoh, Kim, Woo Jin, Cho, Suhwan, and Lee, Sangyoun

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

In contemporary society, surveillance anomaly detection, i.e., spotting anomalous events such as crimes or accidents in surveillance videos, is a critical task. As anomalies occur rarely, most training data consists of unlabeled videos without anomalous events, which makes the task challenging. Most existing methods use an autoencoder (AE) to learn to reconstruct normal videos; they then detect anomalies based on their failure to reconstruct the appearance of abnormal scenes. However, because anomalies are distinguished by appearance as well as motion, many previous approaches have explicitly separated appearance and motion information-for example, using a pre-trained optical flow model. This explicit separation restricts reciprocal representation capabilities between two types of information. In contrast, we propose an implicit two-path AE (ITAE), a structure in which two encoders implicitly model appearance and motion features, along with a single decoder that combines them to learn normal video patterns. For the complex distribution of normal scenes, we suggest normal density estimation of ITAE features through normalizing flow (NF)-based generative models to learn the tractable likelihoods and identify anomalies using out of distribution detection. NF models intensify ITAE performance by learning normality through implicitly learned features. Finally, we demonstrate the effectiveness of ITAE and its feature distribution modeling on six benchmarks, including databases that contain various anomalies in real-world scenarios.

Published
2020

38. Attitudes toward Using and Teaching Confidence Intervals: A Latent Profile Analysis on Elementary Statistics Instructors

Author

Kim, Hyung Won, Kim, Woo Jin, Wilson, Aaron T., and Ko, Ho Kyoung

Abstract

The use of confidence intervals (CIs) for making a statistical inference is gaining popularity in research communities. To evaluate college statistics instructors' readiness to teach CIs, this study explores their attitudes toward teaching CIs in elementary statistics courses, and toward using CIs in inferential statistics. Data were collected with a survey that classifies instructors' attitudes on the basis of three previously established pedagogical components: affective, cognitive, and behavioral. Based on the survey responses from 270 participants, we created three profiles (subgroups) via latent profile analysis, and identified each profile's pattern of attitudes toward CIs and common characteristics of the instructors that fit each profile. In addition, we compared the profiles across groupings created by six variables: gender, academic background, statistics teaching experience, subject preference, degree level, and desire to improve teaching. The results of the latent profile analysis support three profiles within the population of statistics instructors, and the results of the comparative analysis of teacher characteristics indicate that the six variables are moderate to strong predictors of the grouping of the sample into three profiles.

Published
2019

39. Electronic band structure of (111) $SrRuO_{3}$ thin film$-$an angle-resolved photoemission spectroscopy study

Author

Ryu, Hanyoung, Ishida, Yukiaki, Kim, Bongju, Kim, Jeong Rae, Kim, Woo Jin, Kohama, Yoshimitsu, Imajo, Shusaku, Yang, Zhuo, Kyung, Wonshik, Hahn, Sungsoo, Sohn, Byungmin, Song, Inkyung, Kim, Minsoo, Huh, Soonsang, Jung, Jongkeun, Kim, Donghan, Noh, Tae Won, Das, Saikat, and Kim, Changyoung

Subjects
Condensed Matter - Strongly Correlated Electrons, Condensed Matter - Materials Science
Abstract

We studied the electronic band structure of pulsed laser deposition (PLD) grown (111)-oriented SrRuO$_3$ (SRO) thin films using \textit{in situ} angle-resolved photoemission spectroscopy (ARPES) technique. We observed previously unreported, light bands with a renormalized quasiparticle effective mass of about 0.8$m_{e}$. The electron-phonon coupling underlying this mass renormalization yields a characteristic "kink" in the band dispersion. The self-energy analysis using the Einstein model suggests five optical phonon modes covering an energy range 44 to 90 meV contribute to the coupling. Besides, we show that the quasiparticle spectral intensity at the Fermi level is considerably suppressed, and two prominent peaks appear in the valance band spectrum at binding energies of 0.8 eV and 1.4 eV, respectively. We discuss the possible implications of these observations. Overall, our work demonstrates that high-quality thin films of oxides with large spin-orbit coupling can be grown along the polar (111) orientation by the PLD technique, enabling \textit{in situ} electronic band structure study. This could allow for characterizing the thickness-dependent evolution of band structure of (111) heterostructures$-$a prerequisite for exploring possible topological quantum states in the bilayer limit.

Published
2020
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40. AD-VO: Scale-Resilient Visual Odometry Using Attentive Disparity Map

Author

Lee, Joosung, Hwang, Sangwon, Lee, Kyungjae, Kim, Woo Jin, Lee, Junhyeop, Chung, Tae-young, and Lee, Sangyoun

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Visual odometry is an essential key for a localization module in SLAM systems. However, previous methods require tuning the system to adapt environment changes. In this paper, we propose a learning-based approach for frame-to-frame monocular visual odometry estimation. The proposed network is only learned by disparity maps for not only covering the environment changes but also solving the scale problem. Furthermore, attention block and skip-ordering scheme are introduced to achieve robust performance in various driving environment. Our network is compared with the conventional methods which use common domain such as color or optical flow. Experimental results confirm that the proposed network shows better performance than other approaches with higher and more stable results., Comment: 5 pages, 5 figures, 2018.02 papers

Published
2020

46. Cluster Analyses From the Real-World NOVELTY Study: Six Clusters Across the Asthma-COPD Spectrum

Author

Olmo, Ricardo del, Anderson, Gary, Reddel, Helen, Rabahi, Marcelo, McIvor, Andrew, Sadatsafavi, Mohsen, Weinreich, Ulla, Burgel, Pierre-Régis, Devouassoux, Gilles, Papi, Alberto, Inoue, Hiromasa, Rendon, Adrián, van den Berge, Maarten, Beasley, Richard, García-Navarro, Alvar Agusti, Faner, Rosa, Olaguibel Rivera, José, Janson, Christer, Bilińska-Izydorczyk, Magdalena, Fagerås, Malin, Fihn-Wikander, Titti, Franzén, Stefan, Keen, Christina, Ostridge, Kristoffer, Chalmers, James, Harrison, Timothy, Pavord, Ian, Price, David, Azim, Adnan, Belton, Laura, Blé, Francois-Xavier, Erhard, Clement, Gairy, Kerry, Hughes, Rod, Lassi, Glenda, Müllerová, Hana, Rapsomaniki, Eleni, Scott, Ian Christopher, Chipps, Bradley, Christenson, Stephanie, Make, Barry, Tomaszewski, Erin, Benhabib, Gabriel, Ruiz, Xavier Bocca, Lisanti, Raul Eduardo, Marino, Gustavo, Mattarucco, Walter, Nogueira, Juan, Parody, Maria, Pascale, Pablo, Rodriguez, Pablo, Silva, Damian, Svetliza, Graciela, Victorio, Carlos F., Rolon, Roxana Willigs, Yañez, Anahi, Baines, Stuart, Bowler, Simon, Bremner, Peter, Bull, Sheetal, Carroll, Patrick, Chaalan, Mariam, Farah, Claude, Hammerschlag, Gary, Hancock, Kerry, Harrington, Zinta, Katsoulotos, Gregory, Kim, Joshua, Langton, David, Lee, Donald, Peters, Matthew, Prassad, Lakshman, Sajkov, Dimitar, Santiago, Francis, Simpson, Frederick Graham, Tai, Sze, Thomas, Paul, Wark, Peter, Cançado, José Eduardo Delfini, Cunha, Thúlio, Lima, Marina, Cardoso, Alexandre Pinto, FitzGerald, J. Mark, Anees, Syed, Bertley, John, Bell, Alan, Cheema, Amarjit, Chouinard, Guy, Csanadi, Michael, Dhar, Anil, Dhillon, Ripple, Kanawaty, David, Kelly, Allan, Killorn, William, Landry, Daniel, Luton, Robert, Mandhane, Piushkumar, Pek, Bonavuth, Petrella, Robert, Stollery, Daniel, Wang, Chen, Chen, Meihua, Chen, Yan, Gu, Wei, Christopher Hui, Kim Ming, Li, Manxiang, Li, Shiyue, Lijun, Ma, Qin, Guangyue, Song, Weidong, Tan, Wei, Tang, Yijun, Wang, Tan, Wen, Fuqiang, Wu, Feng, Xiang, PingChao, Xiao, Zuke, Xiong, Shengdao, Yang, Jinghua, Yang, Jingping, Zhang, Caiqing, Zhang, Min, Zhang, Ping, Zhang, Wei, Zheng, Xiaohe, Zhu, Dan, Bueno, Carlos Matiz, Grimaldos, Fabio Bolivar, Arboleda, Alejandra Cañas, de Salazar, Dora Molina, Bendstrup, Elisabeth, Hilberg, Ole, Kjellerup, Carsten, Raherison, Chantal, Bonniaud, Philippe, Brun, Olivier, Chouaid, Christos, Couturaud, Francis, de Blic, Jacques, Debieuvre, Didier, Delsart, Dominique, Demaegdt, Axelle, Demoly, Pascal, Deschildre, Antoine, Egron, Carole, Falchero, Lionel, Goupil, François, Kessler, Romain, Le Roux, Pascal, Mabire, Pascal, Mahay, Guillaume, Martinez, Stéphanie, Melloni, Boris, Moreau, Laurent, Riviere, Emilie, Roux-Claudé, Pauline, Soulier, Michel, Vignal, Guillaume, Yaici, Azzedine, Bals, Robert, Aries, Sven Philip, Beck, Ekkehard, Deimling, Andreas, Feimer, Jan, Grimm-Sachs, Vera, Groth, Gesine, Herth, Felix, Hoheisel, Gerhard, Kanniess, Frank, Lienert, Thomas, Mronga, Silke, Reinhardt, Jörg, Schlenska, Christian, Stolpe, Christoph, Teber, Ishak, Timmermann, Hartmut, Ulrich, Thomas, Velling, Peter, Wehgartner-Winkler, Sabina, Welling, Juergen, Winkelmann, Ernst-Joachim, Barbetta, Carlo, Braido, Fulvio, Cardaci, Vittorio, Clini, Enrico Maria, Costantino, Maria Teresa, Cuttitta, Giuseppina, di Gioacchino, Mario, Fois, Alessandro, Foschino-Barbaro, Maria Pia, Gammeri, Enrico, Inchingolo, Riccardo, Lavorini, Federico, Molino, Antonio, Nucera, Eleonora, Patella, Vincenzo, Pesci, Alberto, Ricciardolo, Fabio, Rogliani, Paola, Sarzani, Riccardo, Vancheri, Carlo, Vincenti, Rigoletta, Endo, Takeo, Fujita, Masaki, Hara, Yu, Horiguchi, Takahiko, Hosoi, Keita, Ide, Yumiko, Inomata, Minehiko, Inoue, Koji, Inoue, Sumito, Kato, Motokazu, Kawasaki, Masayuki, Kawayama, Tomotaka, Kita, Toshiyuki, Kobayashi, Kanako, Koto, Hiroshi, Nishi, Koichi, Saito, Junpei, Shimizu, Yasuo, Shirai, Toshihiro, Sugihara, Naruhiko, Takahashi, Ken-ichi, Tashimo, Hiroyuki, Tomii, Keisuke, Yamada, Takashi, Yanai, Masaru, Rendon, Adrian, Cerino Javier, Ruth, Domínguez Peregrina, Alfredo, Fernández Corzo, Marco, Montano Gonzalez, Efraín, Ramírez-Venegas, Alejandra, Boersma, Willem, Djamin, R.S., Eijsvogel, Michiel, Franssen, Frits, Goosens, Martijn, Graat-Verboom, Lidwien, Veen, Johannes in 't, Janssen, Rob, Kuppens, Kim, van de Ven, Mario, Bakke, Per, Brunstad, Ole Petter, Einvik, Gunnar, Høines, Kristian Jong, Khusrawi, Alamdar, Oien, Torbjorn, Yoon, Ho Joo, Chang, Yoon-Seok, Cho, Young Joo, Hwang, Yong Il, Kim, Woo Jin, Koh, Young-Il, Lee, Byung-Jae, Lee, Kwan-Ho, Lee, Sang-Pyo, Lee, Yong Chul, Lim, Seong Yong, Min, Kyung Hun, Oh, Yeon-Mok, Park, Choon-Sik, Park, Hae-Sim, Park, Heung-Woo, Rhee, Chin Kook, Yoon, Hyoung-Kyu, García-Navarro, Alvar Agustí, Andújar, Rubén, Anoro, Laura, Buendía García, María, Mozo, Paloma Campo, Campos, Sergio, Casas Maldonado, Francisco, Castilla Martínez, Manuel, Cisneros Serrano, Carolina, Comeche Casanova, Lorena, Corbacho, Dolores, Campo Matías, Felix Del, Echave-Sustaeta, Jose, Corral, Gloria Francisco, Gamboa Setién, Pedro, García Clemente, Marta, Núñez, Ignacio García, García Robaina, Jose, García Salmones, Mercedes, Marín Trigo, Jose Maria, Fernandez, Marta Nuñez, Palomo, Sara Nuñez, Pérez de Llano, Luis, Pueyo Bastida, Ana, Rañó, Ana, Rodríguez González-Moro, José, Reig, Albert Roger, Velasco Garrido, José, Curiac, Dan, Lif-Tiberg, Cornelia, Luts, Anders, Råhlen, Lennart, Rustscheff, Stefan, Adams, Frances, Bradman, Drew, Broughton, Emma, Cosgrove, John, Flood-Page, Patrick, Fuller, Elizabeth, Hartley, David, Hattotuwa, Keith, Jones, Gareth, Lewis, Keir, McGarvey, Lorcan, Morice, Alyn, Pandya, Preeti, Patel, Manish, Roy, Kay, Sathyamurthy, Ramamurthy, Thiagarajan, Swaminathan, Turner, Alice, Vestbo, Jørgen, Wedzicha, Wisia, Wilkinson, Tom, Wilson, Pete, Al-Asadi, Lo’Ay, Anholm, James, Averill, Francis, Bansal, Sandeep, Baptist, Alan, Campbell, Colin, Campos, Michael A., Crook, Gretchen, DeLeon, Samuel, Eid, Alain, Epstein, Ellen, Fritz, Stephen, Harris, Hoadley, Hewitt, Mitzie, Holguin, Fernando, Hudes, Golda, Jackson, Richard, Kaufman, Alan, Kaufman, David, Klapholz, Ari, Krishna, Harshavardhan, Lee, Daria, Lin, Robert, Maselli-Caceres, Diego, Mehta, Vinay, Moy, James N., Nwokoro, Ugo, Parikh, Purvi, Parikh, Sudhir, Perrino, Frank, Ruhlmann, James, Sassoon, Catherine, Settipane, Russell A., Sousa, Daniel, Sriram, Peruvemba, Wachs, Richard, Bansal, Aruna T., Agustí, Alvar, Fageras, Malin, Alacqua, Marianna, and Reddel, Helen K.

Published
2023
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