262 citations · 1.9k across the 56 of their papers we have counts for
9 papers · 1 filter
Learning Open Set Network with Discriminative Reciprocal Points
Guangyao Chen, Limeng Qiao, Yemin Shi +5
Open set recognition is an emerging research area that aims to simultaneously classify samples from predefined classes and identify the rest as 'unknown'. In this process, one of t…
Human Perception-based Evaluation Criterion for Ultra-high Resolution Cell Membrane Segmentation
Ruohua Shi, Wenyao Wang, Zhixuan Li +6
Computer vision technology is widely used in biological and medical data analysis and understanding. However, there are still two major bottlenecks in the field of cell membrane se…
Vision at A Glance: Interplay between Fine and Coarse Information Processing Pathways
Zilong Ji, Xiaolong Zou, Tiejun Huang +1
Object recognition is often viewed as a feedforward, bottom-up process in machine learning, but in real neural systems, object recognition is a complicated process which involves t…
Incorporating Learnable Membrane Time Constant to Enhance Learning of Spiking Neural Networks
Wei Fang, Zhaofei Yu, Yanqi Chen +3
Spiking Neural Networks (SNNs) have attracted enormous research interest due to temporal information processing capability, low power consumption, and high biological plausibility.…
Learning Individually Inferred Communication for Multi-Agent Cooperation
Ziluo Ding, Tiejun Huang, Zongqing Lu
Communication lays the foundation for human cooperation. It is also crucial for multi-agent cooperation. However, existing work focuses on broadcast communication, which is not onl…
Self-Guided Adaptation: Progressive Representation Alignment for Domain Adaptive Object Detection
Zongxian Li, Qixiang Ye, Chong Zhang +3
Unsupervised domain adaptation (UDA) has achieved unprecedented success in improving the cross-domain robustness of object detection models. However, existing UDA methods largely i…
Kernel Quantization for Efficient Network Compression
Zhongzhi Yu, Yemin Shi, Tiejun Huang +1
This paper presents a novel network compression framework Kernel Quantization (KQ), targeting to efficiently convert any pre-trained full-precision convolutional neural network (CN…
Towards the Next Generation of Retinal Neuroprosthesis: Visual Computation with Spikes
Zhaofei Yu, Jian K. Liu, Shanshan Jia +4
Neuroprosthesis, as one type of precision medicine device, is aiming for manipulating neuronal signals of the brain in a closed-loop fashion, together with receiving stimulus from…
Video Coding for Machines: A Paradigm of Collaborative Compression and Intelligent Analytics
Ling-Yu Duan, Jiaying Liu, Wenhan Yang +2
Video coding, which targets to compress and reconstruct the whole frame, and feature compression, which only preserves and transmits the most critical information, stand at two end…