Remote sensing image scene classification (RSI-SC) is crucial for various high-level
applications, including RSI retrieval, image captioning, and object detection. Deep learning …

Although deep learning models have shown impressive performance on supervised
learning tasks, they often struggle to generalize well when the training (source) and test …

Recently, the remarkable success of ChatGPT has sparked a renewed wave of interest in
artificial intelligence (AI), and the advancements in Vision–Language Models (VLMs) have …

Abstract arge-scale foundation models, such as CLIP, have demonstrated impressive zero-
shot generalization performance on downstream tasks, leveraging well-designed language …

Abstract We delve into Open Domain Generalization (ODG) marked by domain and category
shifts between training's labeled source and testing's unlabeled target domains. Existing …

Traditional multimodal contrastive learning brings text and its corresponding image closer
together as a positive pair, where the text typically consists of fixed sentence structures or …

This paper proposes a novel laddering vision foundation model for change detection (CD) of
remote sensing images. Current approaches have limitations in simultaneously extracting …

Few-shot open-set recognition, as a new paradigm, leveraging a limited amount of
supervised data to identify specific Remote Sensing (RS) scene categories and generalize …

Remote sensing semantic segmentation is considered a key step in the intelligent
interpretation of high-resolution remote sensing (HRRS) images, with widespread …

Deep Learning (DL) is undergoing a paradigm shift with the emergence of foundation
models, aptly named by their crucial, yet incomplete nature. In this work, we focus on …