7 papers
CR-JEPA: Cross-Modal Joint-Embedding Predictive Learning for Remote Sensing Image Retrieval
Md Aminur Hossain, Ayush V. Patel, Nitant Dube +1
Cross-modal remote sensing image retrieval aims to retrieve semantically related scenes across heterogeneous sensing modalities. This remains challenging because paired observation…
HQ-JEPA: Hybrid Quantum Joint-Embedding Predictive Architecture for Cross-Modal Remote Sensing Representation Learning
Md Aminur Hossain, Ayush V. Patel, Sanjay K. Singh +1
We introduce HQ-JEPA, a hybrid quantum-classical joint-embedding predictive architecture for cross-modal remote sensing representation learning. The proposed framework extends JEPA…
Spatial-Frequency Gated Swin Transformer for Remote Sensing Single-Image Super-Resolution
Md Aminur Hossain, Parekh Valkesh, Ayush V. Patel +3
Remote Sensing (RS) single-image super-resolution aims to reconstruct high-resolution imagery from low-resolution observations while preserving fine spatial structures. Recent Swin…
HQ-UNet: A Hybrid Quantum-Classical U-Net with a Quantum Bottleneck for Remote Sensing Image Segmentation
Md Aminur Hossain, Ayush V. Patel, Ikshwaku Vanani +1
Semantic segmentation in remote sensing is commonly addressed using classical deep learning architectures such as U-Net, which require a large number of parameters to model complex…
QMC-Net: Data-Aware Quantum Representations for Remote Sensing Image Classification
Md Aminur Hossain, Ayush V. Patel, Biplab Banerjee
Hybrid quantum-classical models offer a promising route for learning from complex data; however, their application to multi-band remote sensing imagery often relies on generic, dat…
HQF-Net: A Hybrid Quantum-Classical Multi-Scale Fusion Network for Remote Sensing Image Segmentation
Md Aminur Hossain, Ayush V. Patel, Siddhant Gole +2
Remote sensing semantic segmentation requires models that can jointly capture fine spatial details and high-level semantic context across complex scenes. While classical encoder-de…