Newspoint on MSN

Unlock Your Career Potential with These Top AI Certifications

Artificial intelligence is rapidly becoming one of the most lucrative and sought-after fields. The ongoing digital ...
Newspoint on MSN

AI Courses: These are the top 5 AI courses that will increase your salary in minutes..

Artificial intelligence is one of the fastest-growing and highest-paying fields today. The continued digitization of ...
Leadership

Nigerian Researcher Develops Deep Learning Model To Transform Brain Cancer Diagnosis

In a groundbreaking development at the intersection of artificial intelligence (AI) and medicine, Tobi Titus Oyekanmi, a ...
C&EN

Development of Coarse-Grained Lipid Force Fields Based on a Graph Neural Network

Department of Materials Science and Engineering, City University of Hong Kong, Kowloon 999077, Hong Kong China Department of Physics, City University of Hong Kong, Kowloon 999077, Hong Kong China ...
IEEE

Bidirectional Multiscale Efficient Dilated Convolutional Recurrent Neural Network Improved by Swarm Intelligence Optimization

Abstract: In recent years, bidirectional convolutional recurrent neural networks (RNNs) have made significant breakthroughs in addressing a wide range of challenging problems related to time series ...
pv magazine International

PV module fault diagnosis uses convolutional neural network

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 ...
Frontiers

The diagnostic value of convolutional neural networks in thyroid cancer detection using ultrasound images

Objective: To extract and analyze the image features of two-dimensional ultrasound images and elastic images of four thyroid nodules by radiomics, and then further convolution processing to construct ...
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 ...