This letter focuses on remote sensing image interpretation and aims to promote the use of contrastive self-supervised learning (SSL) in varied applications of remote sensing image classification. The ...

ChatGPT-style models are being trained to detect what a news article really thinks about an issue – even when that stance is ...

Recently, various contrastive learning techniques have been developed to categorize time series data and have exhibited promising performance for real-world applications. A general paradigm is to ...

In the sec 3.4 of paper, "we propose an alignment verification module to regularize the motion generator using contrastive-based pretrained encoders (Em for motion and Et for text)." So, what specific ...

This paper fills this gap with OpenVision, a fully-open, cost-effective family of vision encoders that match or surpass the performance of OpenAI's CLIP when integrated into multimodal frameworks like ...

To address these challenges, we propose AffiGrapher, a physics-driven graph neural network that integrates a physics-informed graph architecture with contrastive learning. Incorporating multiple RNA ...

By fine-tuning the LLM in the caption space with contrastive learning, we extract its textual capabilities into the output embeddings, significantly improving the output layer’s textual discriminabil.