1 citations · 2 across the 3 of their papers we have counts for
7 papers
Gated Domain-Invariant Feature Disentanglement for Domain Generalizable Object Detection
Haozhuo Zhang, Huimin Yu, Yuming Yan +1
For Domain Generalizable Object Detection (DGOD), Disentangled Representation Learning (DRL) helps a lot by explicitly disentangling Domain-Invariant Representations (DIR) from Dom…
A Hybrid Precipitation Prediction Method based on Multicellular Gene Expression Programming
Hongya Li, Yuzhong Peng, Chuyan Deng +3
Prompt and accurate precipitation forecast is very important for development management of regional water resource, flood disaster prevention and people's daily activity and produc…
CompoNet: Learning to Generate the Unseen by Part Synthesis and Composition
Nadav Schor, Oren Katzir, Hao Zhang +1
Data-driven generative modeling has made remarkable progress by leveraging the power of deep neural networks. A reoccurring challenge is how to enable a model to generate a rich va…
Sequence-based Multimodal Apprenticeship Learning For Robot Perception and Decision Making
Fei Han, Xue Yang, Yu Zhang +1
Apprenticeship learning has recently attracted a wide attention due to its capability of allowing robots to learn physical tasks directly from demonstrations provided by human expe…
Simultaneous Feature and Body-Part Learning for Real-Time Robot Awareness of Human Behaviors
Fei Han, Xue Yang, Christopher Reardon +2
Robot awareness of human actions is an essential research problem in robotics with many important real-world applications, including human-robot collaboration and teaming. Over the…
Self-Reflective Risk-Aware Artificial Cognitive Modeling for Robot Response to Human Behaviors
Fei Han, Christopher Reardon, Lynne E. Parker +1
In order for cooperative robots ("co-robots") to respond to human behaviors accurately and efficiently in human-robot collaboration, interpretation of human actions, awareness of n…