SSMRadNet : A Sample-wise State-Space Framework for Efficient and Ultra-Light Radar Segmentation and Object Detection

Anuvab Sen, Mir Sayeed Mohammad, Saibal Mukhopadhyay. SSMRadNet : A Sample-wise State-Space Framework for Efficient and Ultra-Light Radar Segmentation and Object Detection. In IEEE/CVF Winter Conference on Applications of Computer Vision, WACV 2026, Tucson, AZ, USA, March 6-10, 2026. pages 4365-4374, IEEE, 2026. [doi]

@inproceedings{SenMM26,
  title = {SSMRadNet : A Sample-wise State-Space Framework for Efficient and Ultra-Light Radar Segmentation and Object Detection},
  author = {Anuvab Sen and Mir Sayeed Mohammad and Saibal Mukhopadhyay},
  year = {2026},
  doi = {10.1109/WACV61042.2026.00425},
  url = {https://doi.org/10.1109/WACV61042.2026.00425},
  researchr = {https://researchr.org/publication/SenMM26},
  cites = {0},
  citedby = {0},
  pages = {4365-4374},
  booktitle = {IEEE/CVF Winter Conference on Applications of Computer Vision, WACV 2026, Tucson, AZ, USA, March 6-10, 2026},
  publisher = {IEEE},
  isbn = {979-8-3315-5511-5},
}