Introduction: Understanding and predicting drug sensitivity in cancer therapy demands innovative approaches that integrate multi-modal data to enhance treatment efficacy. In alignment with the ...

💡 TL;DR: Given an image and nothing else (i.e. no prompts or candidate labels), NOVIC can generate an accurate fine-grained textual classification label in real-time, with coverage of the vast ...

Explore the first part of our series on sleep stage classification using Python, EEG data, and powerful libraries like Sklearn and MNE. Perfect for data scientists and neuroscience enthusiasts!

Introduction: Image emotion classification (IEC), which predicts human emotional perception from images, is a research highlight for its wide applications. Recently, most existing methods have focused ...

Abstract: As one of the core tasks in vision recognition, image classification is widely used in various scenarios. Most existing mainstream image classification models use the Convolutional Neural ...

Python libraries are pre-written collections of code designed to simplify programming by providing ready-made functions for specific tasks. They eliminate the need to write repetitive code and cover ...

Whole Slide Image (WSI) classification in digital pathology presents several critical challenges due to the immense size and hierarchical nature of WSIs. WSIs contain billions of pixels and hence ...

Serving tens of millions of developers, Microsoft's dev team for Python in Visual Studio Code shipped a new release with three major new features, including a "full" language server mode for Pylance, ...

Abstract: Recently, many image inpainting methods have achieved promising performance in recovering damaged natural images in various scenes. Different from natural images, blur-readable (BR) 2D ...