State Space Model (SSM) is a mathematical model used to describe and analyze the
behavior of dynamic systems. This model has witnessed numerous applications in several …

Remote sensing image change captioning (RSICC) aims to describe surface changes
between multitemporal remote sensing images in language, including the changed object …

Hyperspectral image (HSI) classification plays a crucial role in remote sensing (RS)
applications, enabling the precise identification of materials and land cover based on …

Deep learning methods, especially convolutional neural networks (CNNs) and vision
transformers (ViTs), are frequently employed to perform semantic segmentation of high …

Temporal image analysis in remote sensing has traditionally centered on change detection,
which identifies regions of change between images captured at different times. However …

This work introduces Mamba Imitation Learning (MaIL), a novel imitation learning (IL)
architecture that offers a computationally efficient alternative to state-of-the-art (SoTA) …

In an era of frequent extreme weather and global warming, obtaining precise, fine-grained
near-surface weather forecasts is increasingly essential for human activities. Downscaling …

RGB-Event based tracking is an emerging research topic, focusing on how to effectively
integrate heterogeneous multi-modal data (synchronized exposure video frames and …

Skin lesion segmentation is key for early skin cancer detection. Challenges in automatic
segmentation from dermoscopic images include variations in color, texture, and artifacts of …

Event cameras, drawing inspiration from biological systems, efficiently detect changes in
ambient light with low latency and high dynamic range while consuming minimal power. The …