1 code implementation • NeurIPS 2020 • Yukuan Yang, Fangyun Wei, Miaojing Shi, Guoqi Li
In this paper, we restore the negative information in few-shot object detection by introducing a new negative- and positive-representative based metric learning framework and a new inference scheme with negative and positive representatives.
2 code implementations • 5 Sep 2019 • Yukuan Yang, Shuang Wu, Lei Deng, Tianyi Yan, Yuan Xie, Guoqi Li
In this way, all the operations in the training and inference can be bit-wise operations, pushing towards faster processing speed, decreased memory cost, and higher energy efficiency.
no code implementations • 15 Sep 2019 • Zheyu Yang, Yujie Wu, Guanrui Wang, Yukuan Yang, Guoqi Li, Lei Deng, Jun Zhu, Luping Shi
To the best of our knowledge, DashNet is the first framework that can integrate and process ANNs and SNNs in a hybrid paradigm, which provides a novel solution to achieve both effectiveness and efficiency for high-speed object tracking.
no code implementations • 28 Dec 2019 • Yukuan Yang, Lei Deng, Peng Jiao, Yansong Chua, Jing Pei, Cheng Ma, Guoqi Li
In summary, this work provides a new solution for lensless imaging through scattering media using transfer learning in DNNs.
no code implementations • 30 Nov 2020 • Jiayi Yang, Lei Deng, Yukuan Yang, Yuan Xie, Guoqi Li
However, neural network quantization can be used to reduce computation load while maintaining comparable accuracy and original network structure.
no code implementations • 27 May 2021 • Yukuan Yang, Xiaowei Chi, Lei Deng, Tianyi Yan, Feng Gao, Guoqi Li
In summary, the EOQ framework is specially designed for reducing the high cost of convolution and BN in network training, demonstrating a broad application prospect of online training in resource-limited devices.