TANG HE
·Scientific Research
Current position:
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Scientific Research
Research Field
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We study the basic theories and applications of computer vision and machine learning (deep learning), and focus on the following topics:
Basic tasks of computer vision, e.g., object detection, recognition and segmentation of images;
Deep neural networks applied in medical image analysis, e.g., computer aided diagnosis and medical image segmentation.
Paper Publications
MORE+- [1] Partitioned Saliency Ranking with Dense Pyramid Transformers.Proceedings of the ACM Multimedia (ACM MM):1874-1883
- [2] Unite-Divide-Unite: Joint Boosting Trunk and Structure for High-accuracy Dichotomous Image Segmentation.Proceedings of the ACM Multimedia (ACM MM).2023:2139-2147
- [3] CoLA: Conditional dropout and language-driven robust dual-modal salient object detection.Proceedings of the European Conference on Computer Vision (ECCV).2024:354-371
- [4] He Wang.LeNo: Adversarial Robust Salient Object Detection Networks with Learnable Noise.AAAI Conference on Artificial Intelligence.2023
- [5] Jialun Pei.Transformer-based Efficient Salient Instance Segmentation Networks with Orientative Query.IEEE Transactions on Multimedia.2022
Patents
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Published Books
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