Artificial intelligence systems that look nothing alike on the surface are starting to behave as if they share a common ...

CNN in deep learning is a special type of neural network that can understand images and visual information. It works just like human vision: first it detects edges, lines and then recognizes faces and ...

Store any user state in query parameters; imagine JSON in a browser URL, while keeping types and structure of data, e.g.numbers will be decoded as numbers not strings. With TS validation. Shared state ...

ABSTRACT: Magnetic Resonance Imaging (MRI) is commonly applied to clinical diagnostics owing to its high soft-tissue contrast and lack of invasiveness. However, its sensitivity to noise, attributable ...

ABSTRACT: In this paper, a novel multilingual OCR (Optical Character Recognition) method for scanned papers is provided. Current open-source solutions, like Tesseract, offer extremely high accuracy ...

Objective: Existing visual scoring systems for cerebral small vessel disease (CSVD) cannot assess the global lesion load accurately and quantitatively. We aimed to develop an automated segmentation ...

This study proposes an automated tongue analysis system that combines deep learning with traditional Chinese medicine to enhance the accuracy and objectivity of tongue diagnosis. The system includes a ...

I am currently doing a small research for my study on Sparse Transfer Learning and SparseML library is a good approach for my work. My topic is about applying sparse transfer learning on different ...