zhang yi
Affiliations: | University of Electronic Science and Technology of China, Chengdu Shi, Sichuan Sheng, China |
Area:
multistability, convergence, recurrent neural networksWebsite:
http://cilab.uestc.edu.cn/person/zhangyi/index.htmlGoogle:
"zhang yi"Bio:
Mean distance: 14.9 (cluster 6) | S | N | B | C | P |
Cross-listing: MathTree
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Publications
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| Zhou Y, Yen GG, Yi Z. (2021) Evolutionary Shallowing Deep Neural Networks at Block Levels. Ieee Transactions On Neural Networks and Learning Systems |
| Qi X, Hu J, Zhang L, et al. (2020) Automated Segmentation of the Clinical Target Volume in the Planning CT for Breast Cancer Using Deep Neural Networks. Ieee Transactions On Cybernetics |
| Pi Y, Zhao Z, Xiang Y, et al. (2020) Automated diagnosis of bone metastasis based on multi-view bone scans using attention-augmented deep neural networks. Medical Image Analysis. 65: 101784 |
| Xu X, Wang C, Guo J, et al. (2020) MSCS-DeepLN: Evaluating lung nodule malignancy using multi-scale cost-sensitive neural networks. Medical Image Analysis. 65: 101772 |
| Gou J, Wang L, Yi Z, et al. (2020) Weighted discriminative collaborative competitive representation for robust image classification. Neural Networks : the Official Journal of the International Neural Network Society. 125: 104-120 |
| Wang L, Zhang L, Zhu M, et al. (2020) Automatic diagnosis for thyroid nodules in ultrasound images by deep neural networks. Medical Image Analysis. 61: 101665 |
| He T, Hu J, Song Y, et al. (2020) Multi-task learning for the segmentation of organs at risk with label dependence. Medical Image Analysis. 61: 101666 |
| Shu X, Zhang L, Wang Z, et al. (2020) Deep Neural Networks with Region-based Pooling Structures for Mammographic Image Classification. Ieee Transactions On Medical Imaging |
| Wang L, Zhang L, Wang J, et al. (2020) Memory Mechanisms for Discriminative Visual Tracking Algorithms With Deep Neural Networks Ieee Transactions On Cognitive and Developmental Systems. 12: 98-108 |
| Chen W, Yu J, Yi Z, et al. (2020) The Effect of Coefficients on the Continuous Attractors in Coupled Highway Neural Networks Neurocomputing |