61 citations · 135 across the 11 of their papers we have counts for
11 papers
DiffCR: A Fast Conditional Diffusion Framework for Cloud Removal from Optical Satellite Images
Xuechao Zou, Kai Li, Junliang Xing +4
Optical satellite images are a critical data source; however, cloud cover often compromises their quality, hindering image applications and analysis. Consequently, effectively remo…
High-Fidelity Lake Extraction via Two-Stage Prompt Enhancement: Establishing a Novel Baseline and Benchmark
Ben Chen, Xuechao Zou, Kai Li +3
Lake extraction from remote sensing imagery is a complex challenge due to the varied lake shapes and data noise. Current methods rely on multispectral image datasets, making it cha…
LEFormer: A Hybrid CNN-Transformer Architecture for Accurate Lake Extraction from Remote Sensing Imagery
Ben Chen, Xuechao Zou, Yu Zhang +4
Lake extraction from remote sensing images is challenging due to the complex lake shapes and inherent data noises. Existing methods suffer from blurred segmentation boundaries and…
From Abstractions to Grounded Languages for Robust Coordination of Task Planning Robots
Yu Zhang
In this paper, we consider a first step to bridge a gap in coordinating task planning robots. Specifically, we study the automatic construction of languages that are maximally flex…
AI Challenges in Human-Robot Cognitive Teaming
Tathagata Chakraborti, Subbarao Kambhampati, Matthias Scheutz +1
Among the many anticipated roles for robots in the future is that of being a human teammate. Aside from all the technological hurdles that have to be overcome with respect to hardw…
Plan Explanations as Model Reconciliation: Moving Beyond Explanation as Soliloquy
Tathagata Chakraborti, Sarath Sreedharan, Yu Zhang +1
When AI systems interact with humans in the loop, they are often called on to provide explanations for their plans and behavior. Past work on plan explanations primarily involved t…
Explicablility as Minimizing Distance from Expected Behavior
Anagha Kulkarni, Yantian Zha, Tathagata Chakraborti +3
In order to have effective human-AI collaboration, it is necessary to address how the AI agent's behavior is being perceived by the humans-in-the-loop. When the agent's task plans…
Proactive Decision Support using Automated Planning
Satya Gautam Vadlamudi, Tathagata Chakraborti, Yu Zhang +1
Proactive decision support (PDS) helps in improving the decision making experience of human decision makers in human-in-the-loop planning environments. Here both the quality of the…
Plan Explicability and Predictability for Robot Task Planning
Yu Zhang, Sarath Sreedharan, Anagha Kulkarni +3
Intelligent robots and machines are becoming pervasive in human populated environments. A desirable capability of these agents is to respond to goal-oriented commands by autonomous…
Plan or not: Remote Human-robot Teaming with Incomplete Task Information
Vignesh Narayanan, Yu Zhang, Nathaniel Mendoza +1
Human-robot interaction can be divided into two categories based on the physical distance between the human and robot: remote and proximal. In proximal interaction, the human and r…
Learning of Agent Capability Models with Applications in Multi-agent Planning
Yu Zhang, Subbarao Kambhampati
One important challenge for a set of agents to achieve more efficient collaboration is for these agents to maintain proper models of each other. An important aspect of these models…