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270 results on '"Fasli, Maria"'

1. Employing Universal Voting Schemes for Improved Visual Place Recognition Performance

Author

Waheed, Maria, Milford, Michael, Zhai, Xiaojun, Fasli, Maria, McDonald-Maier, Klaus, and Ehsan, Shoaib

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Visual Place Recognition has been the subject of many endeavours utilizing different ensemble approaches to improve VPR performance. Ideas like multi-process fusion, Fly-Inspired Voting Units, SwitchHit or Switch-Fuse involve combining different VPR techniques together, utilizing different strategies. However, a major aspect often common to many of these strategies is voting. Voting is an extremely relevant topic to explore in terms of its application and significance for any ensemble VPR setup. This paper analyses several voting schemes to maximise the place detection accuracy of a VPR ensemble set up and determine the optimal voting schemes for selection. We take inspiration from a variety of voting schemes that are widely employed in fields such as politics and sociology and it is evident via empirical data that the selection of the voting method influences the results drastically. The paper tests a wide variety of voting schemes to present the improvement in the VPR results for several data sets. We aim to determine whether a single optimal voting scheme exists or, much like in other fields of research, the selection of a voting technique is relative to its application and environment. We propose a ranking of these different voting methods from best to worst which allows for better selection. While presenting our results in terms of voting method's performance bounds, in form of radar charts, PR curves to showcase the difference in performance and a comparison methodology using a McNemar test variant to determine the statistical significance of the differences. This test is performed to further confirm the reliability of outcomes and draw comparisons for better and informed selection a voting technique., Comment: arXiv admin note: substantial text overlap with arXiv:2305.05705

Published
2024

2. Aggregating Multiple Bio-Inspired Image Region Classifiers For Effective And Lightweight Visual Place Recognition

Author

Arcanjo, Bruno, Ferrarini, Bruno, Fasli, Maria, Milford, Michael, McDonald-Maier, Klaus D., and Ehsan, Shoaib

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Visual place recognition (VPR) enables autonomous systems to localize themselves within an environment using image information. While VPR techniques built upon a Convolutional Neural Network (CNN) backbone dominate state-of-the-art VPR performance, their high computational requirements make them unsuitable for platforms equipped with low-end hardware. Recently, a lightweight VPR system based on multiple bio-inspired classifiers, dubbed DrosoNets, has been proposed, achieving great computational efficiency at the cost of reduced absolute place retrieval performance. In this work, we propose a novel multi-DrosoNet localization system, dubbed RegionDrosoNet, with significantly improved VPR performance, while preserving a low-computational profile. Our approach relies on specializing distinct groups of DrosoNets on differently sliced partitions of the original image, increasing extrinsic model differentiation. Furthermore, we introduce a novel voting module to combine the outputs of all DrosoNets into the final place prediction which considers multiple top refence candidates from each DrosoNet. RegionDrosoNet outperforms other lightweight VPR techniques when dealing with both appearance changes and viewpoint variations. Moreover, it competes with computationally expensive methods on some benchmark datasets at a small fraction of their online inference time.

Published
2023

4. DisplaceNet: Recognising Displaced People from Images by Exploiting Dominance Level

Author

Kalliatakis, Grigorios, Ehsan, Shoaib, Fasli, Maria, and McDonald-Maier, Klaus

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Every year millions of men, women and children are forced to leave their homes and seek refuge from wars, human rights violations, persecution, and natural disasters. The number of forcibly displaced people came at a record rate of 44,400 every day throughout 2017, raising the cumulative total to 68.5 million at the years end, overtaken the total population of the United Kingdom. Up to 85% of the forcibly displaced find refuge in low- and middle-income countries, calling for increased humanitarian assistance worldwide. To reduce the amount of manual labour required for human-rights-related image analysis, we introduce DisplaceNet, a novel model which infers potential displaced people from images by integrating the control level of the situation and conventional convolutional neural network (CNN) classifier into one framework for image classification. Experimental results show that DisplaceNet achieves up to 4% coverage-the proportion of a data set for which a classifier is able to produce a prediction-gain over the sole use of a CNN classifier. Our dataset, codes and trained models will be available online at https://github.com/GKalliatakis/DisplaceNet., Comment: To be published in CVPR Workshop on Computer Vision for Global Challenges (CV4GC). arXiv admin note: substantial text overlap with arXiv:1902.03817

Published
2019

5. GET-AID: Visual Recognition of Human Rights Abuses via Global Emotional Traits

Author

Kalliatakis, Grigorios, Ehsan, Shoaib, Fasli, Maria, and McDonald-Maier, Klaus D.

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

In the era of social media and big data, the use of visual evidence to document conflict and human rights abuse has become an important element for human rights organizations and advocates. In this paper, we address the task of detecting two types of human rights abuses in challenging, everyday photos: (1) child labour, and (2) displaced populations. We propose a novel model that is driven by a human-centric approach. Our hypothesis is that the emotional state of a person -- how positive or pleasant an emotion is, and the control level of the situation by the person -- are powerful cues for perceiving potential human rights violations. To exploit these cues, our model learns to predict global emotional traits over a given image based on the joint analysis of every detected person and the whole scene. By integrating these predictions with a data-driven convolutional neural network (CNN) classifier, our system efficiently infers potential human rights abuses in a clean, end-to-end system we call GET-AID (from Global Emotional Traits for Abuse IDentification). Extensive experiments are performed to verify our method on the recently introduced subset of Human Rights Archive (HRA) dataset (2 violation categories with the same number of positive and negative samples), where we show quantitatively compelling results. Compared with previous works and the sole use of a CNN classifier, this paper improves the coverage up to 23.73% for child labour and 57.21% for displaced populations. Our dataset, codes and trained models are available online at https://github.com/GKalliatakis/GET-AID., Comment: 10 pages, 6 figures

Published
2019

7. Detection of Human Rights Violations in Images: Can Convolutional Neural Networks help?

Author

Kalliatakis, Grigorios, Ehsan, Shoaib, Fasli, Maria, Leonardis, Ales, Gall, Juergen, and McDonald-Maier, Klaus D.

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

After setting the performance benchmarks for image, video, speech and audio processing, deep convolutional networks have been core to the greatest advances in image recognition tasks in recent times. This raises the question of whether there are any benefit in targeting these remarkable deep architectures with the unattempted task of recognising human rights violations through digital images. Under this perspective, we introduce a new, well-sampled human rights-centric dataset called Human Rights Understanding (HRUN). We conduct a rigorous evaluation on a common ground by combining this dataset with different state-of-the-art deep convolutional architectures in order to achieve recognition of human rights violations. Experimental results on the HRUN dataset have shown that the best performing CNN architectures can achieve up to 88.10\% mean average precision. Additionally, our experiments demonstrate that increasing the size of the training samples is crucial for achieving an improvement on mean average precision principally when utilising very deep networks., Comment: In Proceedings of the 12th International Conference on Computer Vision Theory and Applications (VISAPP 2017), 8 pages

Published
2017

11. Challenging systematic prejudices. An investigation into bias against women and girls in large language models.

Author

van Niekerk, Daniel, Pérez-Ortiz, María, Shawe-Taylor, John, Orlič, Davor, Drobnjak, Ivana, Kay, Jackie, Siegel, Noah, Evans, Katherine, Moorosi, Nyalleng, Eliassi-Rad, Tina, Tanczer, Leonie Maria, Holmes, Wayne, Deisenroth, Marc Peter, Straw, Isabel, Fasli, Maria, Adams, Rachel, Oliver, Nuria, Mladenić, Dunja, and Aneja, Urvashi

Subjects
LANGUAGE models, LIFE cycles (Biology), ARTIFICIAL intelligence, CHATGPT, PREJUDICES, WOMEN'S roles
Abstract

Artificial intelligence is being adopted across industries at an unprecedented pace. Alongside its posited benefits, AI also presents serious risks to society, making the implementation of normative frameworks to reduce these risks a global imperative. The UNESCO Recommendation on the Ethics of AI asserts that "AI actors should make all reasonable efforts to minimize and avoid reinforcing or perpetuating discriminatory or biased applications and outcomes throughout the life cycle of the AI system to ensure fairness of such systems". To date however, AI-based systems often perpetuate (and even scale and amplify) human, structural and social biases. These biases not only prove difficult to mitigate, but may also lead to harm at the individual, collective, or societal level. This study explores biases in three significant large language models (LLMs): OpenAI's GPT-2 and ChatGPT, along with Meta's Llama 2, highlighting their role in both advanced decision-making systems and as user-facing conversational agents. Across multiple studies, the brief reveals how biases emerge in the text generated by LLMs, through gendered word associations, positive or negative regard for gendered subjects, or diversity in text generated by gender and culture. The research uncovers persistent social biases within these state-of-the-art language models, despite ongoing efforts to mitigate such issues. The findings underscore the critical need for continuous research and policy intervention to address the biases that exacerbate as these technologies are integrated across diverse societal and cultural landscapes. The emphasis on GPT-2 and Llama 2 being open-source foundational models is particularly noteworthy, as their widespread adoption underlines the urgent need for scalable, objective methods to assess and correct biases, ensuring fairness in AI systems globally. [ABSTRACT FROM AUTHOR]

Published
2024

12. Plan Acquisition in a BDI Agent Framework Through Intentional Learning

Author

Luna Ramirez, Wulfrano Arturo, Fasli, Maria, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Berndt, Jan Ole, editor, Petta, Paolo, editor, and Unland, Rainer, editor

Published
2017
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13. Explainable Early Prediction of Gestational Diabetes Biomarkers by Combining Medical Background and Wearable Devices: A Pilot Study With a Cohort Group in South Africa

Author

Kolozali, Sefki, White, Sara L., Norris, Shane, Fasli, Maria, and van Heerden, Alastair

Abstract

This study aims to explore the potential of Internet of Things (IoT) devices and explainable Artificial Intelligence (AI) techniques in predicting biomarker values associated with GDM when measured 13–16 weeks prior to diagnosis. We developed a system that forecasts biomarkers such as LDL, HDL, triglycerides, cholesterol, HbA1c, and results from the Oral Glucose Tolerance Test (OGTT) including fasting glucose, 1-hour, and 2-hour post-load glucose values. These biomarker values are predicted based on sensory measurements collected around week 12 of pregnancy, including continuous glucose levels, short physical movement recordings, and medical background information. To the best of our knowledge, this is the first study to forecast GDM-associated biomarker values 13 to 16 weeks prior to the GDM screening test, using continuous glucose monitoring devices, a wristband for activity detection, and medical background data. We applied machine learning models, specifically Decision Tree and Random Forest Regressors, along with Coupled-Matrix Tensor Factorisation (CMTF) and Elastic Net techniques, examining all possible combinations of these methods across different data modalities. The results demonstrated good performance for most biomarkers. On average, the models achieved Mean Squared Error (MSE) between 0.29 and 0.42 and Mean Absolute Error (MAE) between 0.23 and 0.45 for biomarkers like HDL, LDL, cholesterol, and HbA1c. For the OGTT glucose values, the average MSE ranged from 0.95 to 2.44, and the average MAE ranged from 0.72 to 0.91. Additionally, the utilisation of CMTF with Alternating Least Squares technique yielded slightly better results (0.16 MSE and 0.07 MAE on average) compared to the well-known Elastic Net feature selection technique. While our study was conducted with a limited cohort in South Africa, our findings offer promising indications regarding the potential for predicting biomarker values in pregnant women through the integration of wearable devices and medical background data in the analysis. Nevertheless, further validation on a larger, more diverse cohort is imperative to substantiate these encouraging results.

Published
2024
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14. Exploiting Different Bioinformatics Resources for Enhancing Content Recommendations

Author

Almuhaimeed, Abdullah, Fasli, Maria, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Kobsa, Alfred, Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Casteleyn, Sven, editor, Rossi, Gustavo, editor, and Winckler, Marco, editor

Published
2014
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22. Extracting Reputation with Knock-Out Tournament-Based Pairwise Elicitation in Complex Social Networks

Author

Centeno, Roberto, Hermoso, Ramón, Fasli, Maria, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Goebel, Randy, editor, Siekmann, Jörg, editor, Wahlster, Wolfgang, editor, Chesñevar, Carlos Iván, editor, Onaindia, Eva, editor, Ossowski, Sascha, editor, and Vouros, George, editor

Published
2013
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23. Policies for Role Maintenance through Incentives: How to Keep Agents on Track

Author

Lopes Cardoso, Henrique, Hermoso, Ramón, Fasli, Maria, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Goebel, Randy, editor, Siekmann, Jörg, editor, Wahlster, Wolfgang, editor, Chesñevar, Carlos Iván, editor, Onaindia, Eva, editor, Ossowski, Sascha, editor, and Vouros, George, editor

Published
2013
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24. Analysis of Query Reformulations in a Search Engine of a Local Web Site

Author

Albakour, M-Dyaa, Kruschwitz, Udo, Nanas, Nikolaos, Adeyanju, Ibrahim, Song, Dawei, Fasli, Maria, De Roeck, Anne, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Baeza-Yates, Ricardo, editor, de Vries, Arjen P., editor, Zaragoza, Hugo, editor, Cambazoglu, B. Barla, editor, Murdock, Vanessa, editor, Lempel, Ronny, editor, and Silvestri, Fabrizio, editor

Published
2012
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25. Heuristic Resource Search in a Self-Organised Distributed Multi Agent System

Author

Al-Asfoor, Muntasir, Neville, Brendan, Fasli, Maria, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Kuipers, Fernando A., editor, and Heegaard, Poul E., editor

Published
2012
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29. Enriching Query Flow Graphs with Click Information

Author

Albakour, M-Dyaa, Kruschwitz, Udo, Adeyanju, Ibrahim, Song, Dawei, Fasli, Maria, De Roeck, Anne, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Salem, Mohamed Vall Mohamed, editor, Shaalan, Khaled, editor, Oroumchian, Farhad, editor, Shakery, Azadeh, editor, and Khelalfa, Halim, editor

Published
2011
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30. Exploring Ant Colony Optimisation for Adaptive Interactive Search

Author

Albakour, M-Dyaa, Kruschwitz, Udo, Nanas, Nikolaos, Song, Dawei, Fasli, Maria, De Roeck, Anne, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Amati, Giambattista, editor, and Crestani, Fabio, editor

Published
2011
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31. Moving towards Adaptive Search in Digital Libraries

Author

Kruschwitz, Udo, Albakour, M-Dyaa, Niu, Jinzhong, Leveling, Johannes, Nanas, Nikolaos, Kim, Yunhyong, Song, Dawei, Fasli, Maria, De Roeck, Anne, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Bernardi, Raffaella, editor, Chambers, Sally, editor, Gottfried, Björn, editor, Segond, Frédérique, editor, and Zaihrayeu, Ilya, editor

Published
2011
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32. AutoEval: An Evaluation Methodology for Evaluating Query Suggestions Using Query Logs

Author

Albakour, M-Dyaa, Kruschwitz, Udo, Nanas, Nikolaos, Kim, Yunhyong, Song, Dawei, Fasli, Maria, De Roeck, Anne, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Clough, Paul, editor, Foley, Colum, editor, Gurrin, Cathal, editor, Jones, Gareth J. F., editor, Kraaij, Wessel, editor, Lee, Hyowon, editor, and Mudoch, Vanessa, editor

Published
2011
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40. Socrates: A Production-Driven SCM Agent

Author

González, Carlos R. Jaimez, Fasli, Maria, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Dough, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Carbonell, Jaime G., editor, Siekmann, Jörg, editor, La Poutré, Han, editor, Sadeh, Norman M., editor, and Janson, Sverker, editor

Published
2006
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41. Automatic Web Service Composition Based on Graph Network Analysis Metrics

Author

Gekas, John, Fasli, Maria, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Meersman, Robert, editor, and Tari, Zahir, editor

Published
2005
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42. On Deciding to Trust

Author

Michalakopoulos, Michael, Fasli, Maria, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Herrmann, Peter, editor, Issarny, Valérie, editor, and Shiu, Simon, editor

Published
2005
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44. On Commitments, Roles, and Obligations

Author

Fasli, Maria, Goos, G., editor, Hartmanis, J., editor, van Leeuwen, J., editor, Carbonell, Jaime G., editor, Siekmann, Jörg, editor, Dunin-Keplicz, Barbara, editor, and Nawarecki, Edward, editor

Published
2002
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