Abstract: Image segmentation and classification are fundamental tasks in computer vision, forming the backbone of many real-world applications from autonomous driving to medical diagnostics. With the ...

Abstract: Analysis of MRI images and extraction of brain tumors from MRI images are challenging tasks in medical image processing. In image processing consist of four stages image Acquisition, ...

ABSTRACT: Automatic detection of cognitive distortions from short written text could support large-scale mental-health screening and digital cognitive-behavioural therapy (CBT). Many recent approaches ...

The company had clashed with the military over how officials wanted to use its cutting-edge A.I. model. The order could vastly complicate intelligence analysis and defense work. By Julian E. Barnes ...

Ultrasound guidance is widely used in lumbar regional anesthesia and chronic pain management because it provides radiation-free, portable, and real-time visualization. Among lumbar ultrasound views, ...

Liver cancer, including hepatocellular carcinoma (HCC), is a leading cause of cancer-related deaths globally, emphasizing the need for accurate and early detection methods. LiverCompactNet classifies ...

Meta Platforms Inc. today is expanding its suite of open-source Segment Anything computer vision models with the release of SAM 3 and SAM 3D, introducing enhanced object recognition and ...

Image segmentation is a fundamental process in digital image analysis, with applications in object recognition, medical imaging, and computer vision. Traditional segmentation techniques often struggle ...

Binary classification of Diabetic Retinopathy using SVM in MATLAB with fundus image features. This repository compares the performance of Adaline, Logistic Regression, and Perceptron models on binary ...