Researchers in Turkey have developed BCECNN, an AI model that detects breast cancer with 98.75% accuracy and explains its ...

A new framework integrates graph databases with real-time machine learning to enhance fraud detection and risk control in digital finance. By ...

And he took the decision to stay even though his experience with a previous fitness offerings and healthy food venture called CrankOut had shown him that success takes more than just hard work or a ...

This FAQ explores the fundamental architecture of neural networks, the two-phase learning process that optimizes millions of ...

Simple quantum-classical neural networks achieve good results in classifying lesions with fewer computational parameters.

This is a general purpose aimbot, which uses a neural network for enemy/target detection. The aimbot doesn't read/write memory from/to the target process. It is essentially a "pixel bot", designed ...

Deep learning-based image steganalysis has progressed in recent times, with efforts more concerted toward prioritizing detection accuracy over lightweight frameworks. In the context of AI-driven ...

College of Integrated Circuits and Micro-Nano Electronics, School of Microelectronics, State Key Laboratory of Integrated Chip and System, Fudan University, Shanghai 200433, China ...

Researchers in China have created a dataset of various PV faults and normalized it to accommodate different array sizes and typologies. After testing the new approach in combination with the 1D-CNN ...

Abstract: In recent years, real-valued neural networks have made significant progress in computer vision tasks such as image classification, object detection, and semantic segmentation. However, ...