Yoshua Bengio talks about his efforts to identify — and address — the risks posed by AI.
The research aim is to develop an intelligent agent for cybersecurity systems capable of detecting abnormal user behavior ...
Abstract: Automated retinal disease detection, particularly in Diabetic Retinopathy (DR) classification, has received significant attention. While Convolutional Neural Networks (CNNs) have been the ...
Awurum, N.P. (2025) Next-Generation Cyber Defense: AI-Powered Predictive Analytics for National Security and Threat Resilience. Open Access Library Journal, 12, 1-17. doi: 10.4236/oalib.1114210 .
Abstract: In recent years, deep neural networks have shown promising results in modern fault diagnosis. This paper focuses on diagnosing actuator faults in quadcopters using a deep learning strategy.
Abstract: In today's world, the most popular technology used is Artificial Intelligence along with machine learning and deep learning depending upon the applications. Although, Artificial Intelligence ...
Abstract: Deep learning-based object identification technology has numerous uses, including facial recognition, commercial analytics, and medical imaging analysis. An object detector has a backbone ...
Abstract: Major deaths (55% or 1.5 million) of LRI (Lower Respiratory Infections) are caused due to Pneumococcal pneumonia. LRI is the 5th highest cause of demise as mentioned by the Global Burden of ...
Abstract: Against the backdrop of the increasing trend of aging population in China and even globally, the demand for hand function rehabilitation is growing day by day, and human-machine interaction ...
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Abstract: Recent improvements in Convolution Neural Networks (CNN) have demonstrated extraordinary performance in solving real-world problems. However, the performance of CNN depends purely on its ...
Abstract: Landslides inflict substantial societal and economic damage, underscoring their global significance as recurrent and destructive natural disasters. Recent landslides in northern parts of ...