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X-WR-CALDESC:Events for Department of Electrical and Computer Engineering (HKUECE) 電機與計算機工程系
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TZID:Asia/Hong_Kong
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DTSTART:20230101T000000
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DTSTART;TZID=Asia/Hong_Kong:20240507T100000
DTEND;TZID=Asia/Hong_Kong:20240507T110000
DTSTAMP:20260512T175340
CREATED:20240426T084308Z
LAST-MODIFIED:20250114T063723Z
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SUMMARY:RPG Seminar – Hybrid Module with Multiple Receptive Fields and Self-attention Layers for Medical Image Segmentation
DESCRIPTION:Meeting ID: 958 6149 4641\nPassword: 505358 \nAbstract:\nRecent advances in medical image segmentation models combine convolution with the attention mechanism which provides an effective approach to formulate long-term dependencies. However\, many works either replaced the convolutional layers with attention layers or embedded attention layers into convolutional neural network (CNN)-based models. To explore the potential of hybrid architecture\, we propose a simple cascade module that builds up multiple receptive fields using convolutional kernels with different sizes and learns global context via self-attention layers. Benefiting from the powerful representation ability of the proposed module\, multilayer perceptrons (MLPs) with shift operation are adopted to bridge the encoder and decoder to reduce the model size without losing accuracy. Experiments show that our model consistently outperforms the latest 2D and 3D models by large margins on three public tasks and is more resilient to shape\, size\, and boundary variations. \nSpeaker:\nMr. Wenbo QI\nDepartment of Electrical and Electronic Engineering\nThe University of Hong Kong \nBiography of the speaker:\nMr. Wenbo QI received the B.Eng. degree from the University of Science and Technology of China in 2019\, and the M.Eng. degree from The University of Hong Kong in 2020\, where he is currently pursuing the Ph.D. degree with the Department of Electrical and Electronic Engineering. His research interests include computer vision\, medical image processing. \nOrganizer:\nProf. S. C. CHAN \nAll are welcome.
URL:https://ece.hku.hk/events/20240507-1/
LOCATION:Online via Zoom
CATEGORIES:Seminar
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