Kang Ni
Engineering · Purdue University West Lafayette
Publications
60
Citations
312
Est. group size
—
Recurring co-author estimate
Active years
21
Publishing since 2006
Kang Ni's research focuses on developing machine learning and deep learning methods for analyzing remote sensing images, including satellite radar (SAR) and hyperspectral data, to classify land cover, detect targets, and map terrain features. Much of the work involves designing specialized neural network architectures (such as transformers and graph networks) that combine information from multiple sensor types, like optical, radar, and LiDAR data. This research supports applications in environmental monitoring, land use mapping, and object detection from aerial or satellite imagery.
Publication output has grown substantially over the last decade, rising from just a few papers per year before 2022 to a peak of 14 in 2024, with continued strong activity in 2025.
Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026
- Structural–Temporal and Frequency–Temporal Dual Learning for Optical-SAR Time-Series Classification
IEEE Geoscience and Remote Sensing Letters · 2026
- Complex Scattering-Aware and Globally Enhanced Hybrid Network for SAR Target Recognition
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · 2026
- Coarse-to-Fine High-Order Network for Hyperspectral and LiDAR Classification
IEEE Transactions on Geoscience and Remote Sensing · 2025
- MoCoLSK: Modality-Conditioned High-Resolution Downscaling for Land Surface Temperature
IEEE Transactions on Geoscience and Remote Sensing · 2025
- SAR Image Time Series for Land Cover Mapping via Sparse Local–Global Temporal Transformer Network
IEEE Transactions on Aerospace and Electronic Systems · 2025
- Spatial-Frequency Aggregation Transformer for Remote Sensing Scene Classification
2025
- IDNet: Intensity-Constrained Detail-Enhanced Network for Hyperspectral and LiDAR Collaborative Classification
IEEE Transactions on Geoscience and Remote Sensing · 2025
- Learning optical flow from spiking camera with direction disassembly
IET Image Processing · 2025
- Extending SST vanadis to Add SIMT Functional Units
2025
- Author response for "Coarse-to-Fine High-Order Network for Hyperspectral and LiDAR Classification"
2025
- Hyperspectral Object Tracking via Band and Context Refinement Network
Remote Sensing · 2025
- MHST: Multiscale Head Selection Transformer for Hyperspectral and LiDAR Classification
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · 2024
- DenoDet: Attention as Deformable Multisubspace Feature Denoising for Target Detection in SAR Images
IEEE Transactions on Aerospace and Electronic Systems · 2024
- Hyperspectral and LiDAR Classification via Frequency Domain-Based Network
IEEE Transactions on Geoscience and Remote Sensing · 2024
- Selective Spectral–Spatial Aggregation Transformer for Hyperspectral and LiDAR Classification
IEEE Geoscience and Remote Sensing Letters · 2024
- IEEE Geoscience and Remote Sensing Letters×8
- IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing×5
- IEEE Transactions on Geoscience and Remote Sensing×5
- IEEE Transactions on Aerospace and Electronic Systems×4
- Remote Sensing×3
- Hessah Albanwan
Engineering · The Ohio State University
- Susmita Ghosh
Engineering · Purdue University West Lafayette
- Huapeng Li
Engineering · The Ohio State University
- Tianyu Li
Engineering · Purdue University West Lafayette
- Okan K. Ersoy
Engineering · Purdue University West Lafayette
This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.
Last updated Jul 20, 2026.
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