This important study investigates whether perceived gender is represented in the brain in a category-invariant manner across faces, bodies, and objects, identifying the right middle temporal gyrus ...

🌾 Computer Vision and Machine Learning project for classifying 5 rice grain varieties using OpenCV-based feature extraction and KNN, achieving 96.99% classification accuracy. Binary classification ...

Aims To develop and validate DeepAdapter, a novel deep learning algorithm that integrates self-supervised learning (SSL) and unsupervised domain adaptation (UDA) to enhance model generalisability for ...

A photonic quantum neural network (QNN) achieved 100% accuracy on a nonlinearly separable task, while a comparable artificial neural network (ANN) failed to learn the same problem. Classical models ...

Abstract: This paper presents a Pseudo-Multi-Task Segmentation Neural Network (PMTNet) for cropland mapping in mountainous regions using high-resolution remote sensing images. PMTNet extends BsiNet by ...

DNA methylation-based classification has improved central nervous system (CNS) tumor diagnostics, but pediatric data on real-world implementation remain limited. We evaluated two DNA methylation-based ...

Google's TorchTPU aims to enhance TPU compatibility with PyTorch Google seeks to help AI developers reduce reliance on Nvidia's CUDA ecosystem TorchTPU initiative is part of Google's plan to attract ...

[Click here for an explanation regarding the code and how to start: https://github.com/KI-Research-Institute/Soft-Decision-Tree/blob/main/Instructions] Background and ...

Speaking at a recent conference panel, officials identified a top use case on their wish list: assisting with the classification of records and the authorization to access those records. “I would ...

ABSTRACT: Accurate measurement of time-varying systematic risk exposures is essential for robust financial risk management. Conventional asset pricing models, such as the Fama-French three-factor ...