17
2018 ·08
Recruitment Event during the International Conference on Pattern Recognition 2018
延安久生昌服务有限公司
25
2018 ·06
Brainnetome Lecture Series: Super Resolution Tractography with 7.0T MRI-An Application ...
14
2018 ·06
Advanced Lecture Series in Pattern Recognition - Mining Streaming and Temporal Data: fr...
25
2018 ·05
CASIA Distinguished Lecture Series in Intelligence Science and Technology - Adaptive by...
21
2018 ·05
Lecture Series in Intelligent Perception and Computing - Active Authentication in Mobil...
抚顺祥厚中服务有限公司
17
2018 ·08
Recruitment Event during the International Conference on Pattern Recognition 2018
25
2018 ·06
Brainnetome Lecture Series: Super Resolution Tractography with 7.0T MRI-An Application Example to the Human Dorsal Fiber Pathway
14
2018 ·06
Advanced Lecture Series in Pattern Recognition - Mining Streaming and Temporal Data: from Representation to Knowledge
25
2018 ·05
CASIA Distinguished Lecture Series in Intelligence Science and Technology - Adaptive by Using Artificiall Intelligence, Machine Learning, and Biometrics in Worldwide Cloud-based Environment
21
2018 ·05
Lecture Series in Intelligent Perception and Computing - Active Authentication in Mobile Devices: Role of Touch Biometrics
冷水江聚飞华科技有限公司
Breakthroughs in Face Aging Model
Zhenan Sun, Qi Li and Yunfan Liu, scholars from the Center for Research on Intelligent Perception and Computing, CASIA, propose a GAN-based framework to synthesize aged face images. They embed facial attribute vectors to both the generat...
Breakthroughs in Human-inspired Continual Learning and Context-depe...
Recently, scholars from the Briannetome Research Center and the National Laboratory of Pattern Recognition made breakthroughs on tackling the above questions, which sheds lights on the flexibility research for artificial intelligence sys...
A Novel Session-based Recommendation with Graph Neural Networks by ...
Scholars from the Center for Research on Intelligent Perception and Computing, CASIA proposes and publicizes a session-based recommendation system with graph neural networks, SR-GNN in brevity.