Short-term course on deep learning techniques, AI begins at NIT-Kurukshetra

The Department of Electronics and Communication Engineering, National Institute of Technology (NIT), Kurukshetra, inaugurated ...
Tech Xplore

A novel deep learning architecture for multi-source data fusion

Recent years have witnessed the unprecedented development of Industry 4.0 and the Industrial Internet of Things. These two ...
Analytics Insight

Top Web Development Books Every Developer Should Read in 2026

Overview:  AI coding tools are transforming software development, but strong programming fundamentals and system design ...
Saudi Press Agency

SDAIA Issues Deepfakes Guidelines to Regulate Responsible AI Use

To address the rapid evolution of artificial media, the Saudi Data and Artificial Intelligence Authority (SDAIA) has issued ...
IEEE

Deep Learning for Ocean Forecasting: A Comprehensive Review of Methods, Applications, and Datasets

Abstract: As a longstanding scientific challenge, accurate and timely ocean forecasting has always been a sought-after goal for ocean scientists. However, traditional theory-driven numerical ocean ...
AZoOptics

Deep Learning in Optical Microscopy: Advancements and Applications

In a recent review article published in the journal Microscopy Research & Technique, researchers focused on the integration of DL into optical microscopy, exploring its application in image ...
IEEE

Survey on Backdoor Attacks on Deep Learning: Current Trends, Categorization, Applications, Research Challenges, and Future Prospects

Abstract: Deep Neural Networks (DNNs) have emerged as a prominent set of algorithms for complex real-world applications. However, state-of-the-art DNNs require a significant amount of data and ...
C&EN

Deep Learning Applications in the Analysis of Wear Mechanisms in Metallic Materials: A Review

Article Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to ...
C&EN

Historical Data Mining Deep Dive into Machine Learning-Aided 2D Materials Research in Electrochemical Applications

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