Publications (15)
A Novel Framework to Jointly Compress and Index Remote Sensing Images for Efficient Content-Based Retrieval
Gencer Sumbul, Jun Xiang, Nimisha Thekke Madam +1
Remote sensing (RS) images are usually stored in compressed format to reduce the storage size of the archives. Thus, existing content-based image retrieval (CBIR) systems in RS req…
Data-driven Probabilistic Trajectory Learning with High Temporal Resolution in Terminal Airspace
Jun Xiang, Jun Chen
Predicting flight trajectories is a research area that holds significant merit. In this paper, we propose a data-driven learning framework, that leverages the predictive and featur…
Learning-accelerated A* Search for Risk-aware Path Planning
Jun Xiang, Junfei Xie, Jun Chen
Safety is a critical concern for urban flights of autonomous Unmanned Aerial Vehicles. In populated environments, risk should be accounted for to produce an effective and safe path…
Mini-PointNetPlus: a local feature descriptor in deep learning model for 3d environment perception
Chuanyu Luo, Nuo Cheng, Sikun Ma +4
Common deep learning models for 3D environment perception often use pillarization/voxelization methods to convert point cloud data into pillars/voxels and then process it with a 2D…
VCC-DSA: A Novel Vascular Consistency Constrained DSA Imaging Model for Motion Artifact Suppression
Rongjun Ge, Weilong Mao, Jian Lu +9
Digital Subtraction Angiography (DSA) is a clinically significant imaging technique for diagnosing cerebrovascular disease, as gold-standard. However, the artifacts caused by motio…
Learning Probabilistic Obstacle Spaces from Data-driven Uncertainty using Neural Networks
Jun Xiang, Jun Chen
Identifying the obstacle space is crucial for path planning. However, generating an accurate obstacle space remains a significant challenge due to various sources of uncertainty, i…