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Your search keyword '"Tang, Wenxiao"' showing total 18 results
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18 results on '"Tang, Wenxiao"'

1. Airport Boarding Bridge Pedestrian Detection Based on Spatial Attention and Joint Crowd Density Estimation

Author

Han, Xu, Wan, Hao, Tang, Wenxiao, Kang, Wenxiong, 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, Fang, Lu, editor, Pei, Jian, editor, Zhai, Guangtao, editor, and Wang, Ruiping, editor

Published
2024
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2. LF-LVS: Label-Free Left Ventricular Segmentation for Transthoracic Echocardiogram

Author

Kang, Qing, Tang, Wenxiao, Liu, Zheng, Kang, Wenxiong, 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, Liu, Qingshan, editor, Wang, Hanzi, editor, Ma, Zhanyu, editor, Zheng, Weishi, editor, Zha, Hongbin, editor, Chen, Xilin, editor, Wang, Liang, editor, and Ji, Rongrong, editor

Published
2024
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14. DDAD: Detachable Crowd Density Estimation Assisted Pedestrian Detection

Author

Tang, Wenxiao, Liu, Kun, Shakeel, M. Saad, Wang, Hao, and Kang, Wenxiong

Abstract

Detecting pedestrians is a challenging computer vision task, especially in the intelligent transportation system. Mainstream pedestrian detection methods purely utilize information of bounding boxes, which overlooks the role of other valuable attributes (e.g., head, head-shoulders, and keypoints) of pedestrians and leads to sub-optimal solutions. Some works leveraged these valuable attributes with a minor performance improvement at the expense of increased computational complexity during the inference phase. To alleviate this dilemma, we propose a simple yet effective method, namely Detachable crowd Density estimation Assisted pedestrian Detection (DDAD), which leverages the crowd density attributes to assist pedestrian detection in the real-world scenes (e.g., crowded scenes and small-scale pedestrian scenes). The advantage of the crowd density estimation is that it allows the network to focus more on the human head and the small-scale pedestrians, which improves the features representation of pedestrians heavily occluded or far from cameras. Our DDAD works on a principle of multi-task learning and can be seamlessly applied to both one-stage and two-stage pedestrian detectors by equipping them with an extra detachable branch of crowd density estimation. The equipped crowd density estimation branch is trained with the annotations derived from the existing pedestrian bounding box annotations, occurring no extra annotation cost. Moreover, it can be removed during the inference phase without sacrificing the inference speed. Extensive experiments conducted on two challenging datasets, i.e., CrowdHuman and CityPersons, demonstrate that our proposed DDAD achieves a significant improvement upon the state-of-the-art methods. Code is available at https://github.com/SCUT-BIP-Lab/DDAD.

Published
2023
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18. Electronic and magnetic properties of transition-metal-doped monolayer B 2 S 2 within GGA + U framework.

Author

Chen W, Chen Q, Zhang J, Zhou L, Tang W, Wang Z, Deng J, and Wang S

Abstract

Considering the significant role of magnetism induction in two-dimensional (2D) semiconductor materials, we systematically investigate the effects of various dopants from the 3d and 4d transition metal (TM) series, including Ti, V, Mn, Fe, Co, Ni, Cu, Zn, Zr, Nb, Mo, Ru, Rh, Pd, Ag and Cd, on the electronic and magnetic properties of monolayer B 2 S 2 through first-principles calculations. The calculated formation energies indicate that substitutional doping at the B site with various TM atoms could be achieved under S-rich growth conditions. What matters is that with the exception of systems doped with Cu, Tc, and Ag elements, which exhibit non-magnetic semiconductor properties, all other doped systems demonstrate magnetism. Specifically, the Cr-, Ni- and Pd-doped monolayers are magnetic half-metals, while the rest are magnetic semiconductors. We have also performed calculations of magnetic couplings between two TM atoms with an impurity concentration of 3.12%, revealing the prevalence of weak magnetic coupling in the majority of the magnetic systems examined. Moreover, the monolayers doped with Cr, Zr and Pd atoms exhibit ferromagnetic ground states. These findings strongly support the high potential for inducing magnetism in the B 2 S 2 monolayer through B-site doping., Competing Interests: The authors declare no competing financial interests., (This journal is © The Royal Society of Chemistry.)

Published
2024
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