IEEE

Attention-Based Convolutional Neural Network for Anomaly Detection in Multispectral Images of Semi-Natural Ecosystems

Abstract: The monitoring of semi-natural ecosystems has become increasingly critical due to the rising impact of ecological disturbances, including natural disasters and unauthorized human-made ...
Edex Live

Listening to the Forest: An AI innovator’s mission to protect humans and wildlife

By Atharva Agrawal Growing up in the Tiger Capital of India, Nagpur, a city surrounded by some of the country’s most eminent wildlife sanctuaries, including Pen ...
TMCnet

Bridging Silence: A Real-Time Sign Language to English Text Translation System Using Python, OpenCV, and Convolutional Neural Networks

Bridging communication gaps between hearing and hearing-impaired individuals is an important challenge in assistive technology and inclusive education. In an attempt to close that gap, I developed a ...
TMCnet

MicroCloud Hologram Inc. Develops Quantum-Enhanced Deep Convolutional Neural Network Image 3D Reconstruction Technology

SHENZHEN, China, Dec. 18, 2025 /PRNewswire/ -- MicroCloud Hologram Inc. (NASDAQ: HOLO), ("HOLO" or the "Company"), a technology service provider, innovatively launches a quantum-enhanced deep ...
Scientific Research Publishing

Damage Detection in Simply Supported Beams Using 1D Convolutional Neural Networks with Vibration Signals ()

1 Guangzhou Railway Polytechnic, Guangzhou, China. 2 School of Intelligent Construction and Civil Engineering, Zhongyuan University of Technology, Zhengzhou, China. 3 Research Center for Wind ...
Frontiers

A vision-based drowsiness detection system for railway operators using lightweight convolutional neural networks

This research addresses the challenge of monitoring railway driver drowsiness using a real-time, vision-based system powered by convolutional neural networks, specifically the YOLOv8 architecture ...
Frontiers

Image steganalysis using LSTM fused convolutional neural networks for secure telemedicine

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 ...
IEEE

Integration of Convolutional Neural Network and Image Processing for Pulp Fibril Detection and Measurement

Abstract: The fibrillation index is a critical metric in paper manufacturing, quantifying the degree of fibrillation achieved during the pulp refining process. Optimizing this metric enhances both ...