Publications

Select Recent Publications

Select recent publications from our lab are listed below. For a full list, please check out this Google Scholar link.

• Y. Hu, B. Banerjee, S. Prasad, " Label-Efficient Hyperspectral Image Classification via Spectral FiLM Modulation of Low-Level Pretrained Diffusion Features," in Proceedings of the ICML Terrabytes Workshop, Vancouver, BC, Canada, July 2025. 

• A. Perez, S. Prasad, "Layer Optimized Spatial Spectral Masked Autoencoder for Semantic Segmentation of Hyperspectral Imagery,". In Proceedings of the Winter Conference on Applications of Computer Vision Workshops (pp. 599-607), March 2025.

• A. Yaghmour, M. Crawford, S. Prasad,  "A Sensor Agnostic Domain Generalization Framework for Leveraging Geospatial Foundation Models: Enhancing Semantic Segmentation via Synergistic Pseudo-Labeling and Generative Learning,". arXiv preprint arXiv:2505.01558, to appear in IEEE CVPR Workshop Proceedings, June 2025

• A. Awasthi, T. Ly, J. Nizam, V. Mehta, S. Ahmad, R. Nemani, S. Prasad, and H. V. Nguyen. "Anomaly detection in satellite videos using diffusion models." In Proceedings of the IEEE 26th International Workshop on Multimedia Signal Processing (MMSP), West Lafayette, IN, USA, 2024.

• A. Yaghmour, S. Prasad, M. Crawford, “Attention Guided Semi-Supervised Generative Transfer Learning for Hyperspectral Image Analysis”, In IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2024.

• W Liu, S Prasad, M Crawford, "Investigation of Hierarchical Spectral Vision Transformer Architecture for Classification of Hyperspectral Imagery," in the IEEE Transactions on Geoscience and Remote Sensing, 2024.

• A. Yaghmour, S. Prasad, M. Crawford, “Adversarial Discriminative Knowledge Transfer with a Multi-Class Discriminator for Robust GeoAI”, In IGARSS 2023-2023 IEEE International Geoscience and Remote Sensing Symposium (pp. 4883-4886), 2023.

• J. Silvestre, S. Prasad, “Spatially constrained Deep Semantic Segmentation of Geospatial Imagery for building footprint extraction,” In Proceedings of the SPIE DCS Conference, 2023.

• N. Makkar, L. Yang, S. Prasad, “Adversarial learning based Discriminative Domain Adaptation for geospatial image analysis,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 15, 150-162, 2022.

• S. Prasad, J. Chanussot, “Hyperspectral Image Analysis: Advances in Machine Learning and Signal Processing,” Springer Nature, 2020.

• S. Mukherjee, S. Prasad, “A spatial-spectral semisupervised deep learning framework using siamese networks and angular loss”, in Computer Vision and Image Understanding, 2020

• K. Safari, S. Prasad, D. Labate, “A Multiscale Deep Learning Approach for High-Resolution Hyperspectral Image Classification,” in IEEE Geoscience and Remote Sensing Letters, 2020

• F. Shahraki, S. Prasad, “Joint Spatial and Graph Convolutional Neural Networks-A Hybrid Model for Spatial-Spectral Geospatial Image Analysis”, in Proceedings of IEEE IGARSS, 2020

• D Labate, K Safari, N Karantzas, S Prasad, FF Shahraki, “Structured receptive field networks and applications to hyperspectral image classification,” in Wavelets and Sparsity, 2019

• JL Contreras-Vidal, S Prasad, A Kilicarslan, N Bhagat, R Bhattacharyya, RM Uhlenbrock, DW Payton, JS Panova, JD Marcus, TB Panova, EC Leuthardt, LJ Love, R Coker, DW Moran, P Nuyujukian, JC Kao, K Shenoy, ND Schiff, JC Kao, P Nuyujukian, MM Churchland, JP Cunningham, K Shenoy, “Brain–machine interfaces”, Nature Biotechnology, 2019