The proposed Coordinate-Aware Feature Excitation (CAFE) module and Position-Aware Upsampling (Pos-Up) module both adhere to ...
Abstract: Classifying whether a plant is herbal or poisonous is a significant challenge for trekkers, hikers, and nature enthusiasts, particularly in remote areas where several unfamiliar plant ...
Geographic atrophy is a growing worldwide health issue, with approximately 8 million patients impacted, according to a ...
This project implements Vision Transformer (ViT) for image classification. Unlike CNNs, ViT splits images into patches and processes them as sequences using transformer architecture. It includes patch ...
Abstract: Medical image analysis remains challenging due to inherent limitations in imaging modalities, where structural aliasing and noise artifacts persistently compromise diagnostic accuracy. While ...
Based on Spikingformer, this study proposes a lightweight spiking transformer SAR-Spikingformer optimized for the classification of synthetic aperture radar (SAR) images. SAR-Spikingformer introduces ...
Railway image classification (RIC) represents a critical application in railway infrastructure monitoring, involving the analysis of hyperspectral datasets with complex spatial-spectral relationships ...
Computer vision libraries have changed how AI models classify images. These tools help digital systems understand visual data very well. They allow AI models to spot complex patterns and objects in ...
According to @DeepLearningAI, Meta has released DINOv3, a powerful self-supervised vision transformer designed to significantly enhance image embeddings for tasks such as segmentation and depth ...
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