Hardness Recognition of Robotic Forearm Based on Semi-supervised Generative Adversarial Networks.
Xiaoliang QianErkai LiJianwei ZhangSu-Na ZhaoQing E. WuHuanlong ZhangWei WangYuanyuan WuPublished in: Frontiers Neurorobotics (2019)
Keyphrases
- semi supervised
- unsupervised learning
- recognition accuracy
- object recognition
- generative model
- semi supervised learning
- degrees of freedom
- recognition rate
- feature extraction
- pattern recognition
- automatic recognition
- recognition process
- recognition algorithm
- robotic systems
- network structure
- supervised learning
- np hard
- active learning
- semi supervised clustering
- social networks
- semi supervised classification
- human hand
- labeled data
- unlabeled data
- multi view
- mobile robot
- path planning
- activity recognition
- topic models
- complex networks
- real time
- partial occlusion
- np complete
- phase transition
- co training
- worst case
- probabilistic model
- multi agent
- learning algorithm