Over the past few decades, computer scientists have developed increasingly advanced artificial intelligence (AI) systems that ...
For years, the computer vision community has operated on two separate tracks: generative models (which produce images) and discriminative models (which understand them). The assumption was ...
Computer vision is driving healthcare gains in imaging, safety, staff well-being, and efficiency, but scaling it requires ...
Abstract: Pre-trained vision-language models (VLMs) and language models (LMs) have recently garnered significant attention due to their remarkable ability to represent textual concepts, opening up new ...
How do you combine SigLIP2, DINOv3, and SAM3 into a single vision backbone without sacrificing dense or segmentation performance? NVIDIA’s C-RADIOv4 is a new agglomerative vision backbone that ...
AS-Lab/Marthi-et-al-2025-MedVisionLlama-Pre-Trained-LLM-Layers-to-Enhance-Medical-Image-Segmentation
This repository contains the official implementation of "MedVisionLlama: Leveraging Pre-Trained Large Language Model Layers to Enhance Medical Image Segmentation" by Gurucharan Marthi Krishna Kumar, ...
Automated apple harvesting is hindered by clustered fruits, varying illumination, and inconsistent depth perception in complex orchard environments. While deep learning models such as Faster R-CNN and ...
This project showcases a sophisticated pipeline for object detection and segmentation using a Vision-Language Model (VLM) and the Segment Anything Model 2 (SAM2). The core idea is to leverage the ...
For startups and established businesses, understanding the importance of segmentation is essential for the granular analysis of consumer demographics, behaviors, needs, and preferences. These insights ...
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