2022 - Research.com Computer Science in China Leader Award
Yi Yang focuses on Artificial intelligence, Pattern recognition, Machine learning, Convolutional neural network and Discriminative model. Artificial intelligence is closely attributed to Computer vision in his study. His work carried out in the field of Pattern recognition brings together such families of science as Object detection, Similarity, Feature and Image retrieval.
His Machine learning research focuses on TRECVID and how it relates to Leverage. As a part of the same scientific family, Yi Yang mostly works in the field of Convolutional neural network, focusing on Training set and, on occasion, Regularization. His Discriminative model research integrates issues from Embedding, Feature learning, Outlier and Pooling.
Artificial intelligence, Pattern recognition, Optoelectronics, Machine learning and Discriminative model are his primary areas of study. His Artificial intelligence study frequently draws connections between related disciplines such as Computer vision. His work deals with themes such as Laser, Optics and Graphene, which intersect with Optoelectronics.
His Graphene study is focused on Nanotechnology in general.
The scientist’s investigation covers issues in Artificial intelligence, Pattern recognition, Machine learning, Discriminative model and Segmentation. His Artificial intelligence research is multidisciplinary, incorporating elements of Domain, Computer vision and Code. Yi Yang has researched Pattern recognition in several fields, including Object detection and Representation.
His Machine learning study which covers Graph that intersects with Graph. His research is interdisciplinary, bridging the disciplines of Feature learning and Discriminative model. His studies deal with areas such as Object and Embedding as well as Feature.
His main research concerns Artificial intelligence, Pattern recognition, Machine learning, Discriminative model and Segmentation. Yi Yang has included themes like Domain and Code in his Artificial intelligence study. His research in Pattern recognition tackles topics such as Process which are related to areas like Ground truth and Benchmark.
His Machine learning study combines topics in areas such as Adversarial system, Graph and Task. His Discriminative model research incorporates themes from Parsing, Representation and Feature learning. As a member of one scientific family, Yi Yang mostly works in the field of Convolutional neural network, focusing on Contextual image classification and, on occasion, Object detection and Pruning.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Articulated pose estimation with flexible mixtures-of-parts
Yi Yang;Deva Ramanan.
computer vision and pattern recognition (2011)
Deep Captioning with Multimodal Recurrent Neural Networks (m-RNN)
Junhua Mao;Junhua Mao;Wei Xu;Yi Yang;Jiang Wang.
international conference on learning representations (2015)
Person Re-identification: Past, Present and Future
Liang Zheng;Yi Yang;Alexander G. Hauptmann.
arXiv: Computer Vision and Pattern Recognition (2016)
Articulated Human Detection with Flexible Mixtures of Parts
Yi Yang;Deva Ramanan.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2013)
Attention to Scale: Scale-Aware Semantic Image Segmentation
Liang-Chieh Chen;Yi Yang;Jiang Wang;Wei Xu.
computer vision and pattern recognition (2016)
Unlabeled Samples Generated by GAN Improve the Person Re-identification Baseline in Vitro
Zhedong Zheng;Liang Zheng;Yi Yang.
international conference on computer vision (2017)
l 2,1 -norm regularized discriminative feature selection for unsupervised learning
Yi Yang;Heng Tao Shen;Zhigang Ma;Zi Huang.
international joint conference on artificial intelligence (2011)
Random Erasing Data Augmentation
Zhun Zhong;Liang Zheng;Guoliang Kang;Shaozi Li.
arXiv: Computer Vision and Pattern Recognition (2017)
L2,1-Norm Regularized Discriminative Feature Selection for Unsupervised
Yi Yang;Heng Tao Shen;Zhigang Ma;Zi Huang.
international joint conference on artificial intelligence (2011)
Beyond Part Models: Person Retrieval with Refined Part Pooling (and a Strong Convolutional Baseline)
Yifan Sun;Liang Zheng;Yi Yang;Qi Tian.
european conference on computer vision (2018)
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