Frontiers

AI-Driven Complex Networks: Structure, Dynamics, and Intelligent Applications

In an increasingly interconnected world, understanding the behavior and structure of complex networks has become essential ...
Hosted on MSN

Neural network Python from scratch with softmax

Implement Neural Network in Python from Scratch ! In this video, we will implement MultClass Classification with Softmax by making a Neural Network in Python from Scratch. We will not use any build in ...
IEEE

Optimization of Convolutional Neural Networks With Multi-Objective Function Metaheuristics for Melanoma Detection

Abstract: Early and accurate detection of melanoma remains a critical challenge in medical imaging. Convolutional Neural Networks (CNNs) have demonstrated superior classification performance, often ...
PR Newswire

MicroCloud Hologram Inc. Releases Next-Generation Quantum Convolutional Neural Network Multi-Class Classification Technology, Driving Quantum Machine Learning Towards ...

SHENZHEN, China, Nov. 15, 2025 /PRNewswire/ -- MicroCloud Hologram Inc. (NASDAQ: HOLO), ("HOLO" or the "Company"), a technology service provider, has launched a groundbreaking technological ...
C&EN

Integrating ESM-2 and Graph Neural Networks with AlphaFold-2 Structures for Enhanced Protein Function Prediction

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Protein function prediction is essential for elucidating biological processes and ...
Scientific Research Publishing

Identification of Cherry Powdery Mildew Using Deep Convolutional Neural Network ()

1 School of Electronic Information and Artificial Intelligence, Leshan Normal University, Leshan, China. 2 Sichuan Prefabricated Cabin Power Equipment Engineering Technology Research Center, Leshan, ...
IEEE

A Convolutional Neural Network Steganalysis Method Based on ShuffleBottleneck and Attention Mechanism

Abstract: The steganography detection method based on deep learning fuse feature extraction and classification into one model, which reduces the human intervention in feature extraction and obtains a ...
Frontiers

Transformer network enhanced by dual convolutional neural network and cross-attention for wheelset bearing fault diagnosis

Advances in deep learning methods have demonstrated remarkable progress in wheelset fault diagnosis. However, current deep neural networks suffer from design flaws, including low accuracy, high ...