1 code implementation • 24 Aug 2023 • Qiuyu Zhu, Hao Wang, Xuewen Zu, Chengfei Liu
Considering that there are many layers in CNN, through experimental comparison and analysis, MFD Loss acts on multiple front layers of CNN, constrains the output features of each layer and each channel, and performs supervision training jointly with classification loss function during network training.
no code implementations • 6 Apr 2022 • Feng Xia, Shuo Yu, Chengfei Liu, Ivan Lee
In the first procedure, we propose to lower the network scale by optimizing the network structure with maximal k-edge-connected subgraphs.
no code implementations • 4 Jan 2021 • Aman Abidi, Lu Chen, Rui Zhou, Chengfei Liu
By exploiting the discoveries, we propose novel algorithms for maintaining the two indices, which substantially reduces the cost of maintenance.
no code implementations • 8 Feb 2020 • Zafaryab Rasool, Rui Zhou, Lu Chen, Chengfei Liu, Jiajie Xu
Efficient query algorithms are proposed for these indices which significantly avoids irrelevant comparisons at the cost of space.
no code implementations • IEEE Transactions on Knowledge and Data Engineering 2019 • Jiajie Xu, Jing Zhao, Rui Zhou, Chengfei Liu
However, the standard attention mechanism uses fixed feature representations, and has a limited ability to represent distinct features of locations.