Results 141 to 150 of about 22,071 (254)

AI‐Powered Surveillance Systems: A Comprehensive Review of Technologies, Applications, Challenges, and Deployment Considerations

WIREs Data Mining and Knowledge Discovery, Volume 16, Issue 4, December 2026.
Overview of AI‐powered surveillance technologies, applications, challenges, limitations, and deployment considerations. ABSTRACT Artificial intelligence (AI) has rapidly transformed smart surveillance systems, significantly leveraging technologies such as deep learning, computer vision, and adaptive monitoring.
Tanzila Kehkashan, Abdul Rehman, Ahmad Sami Al‐Shamayleh, Nor Azman Ismail, Adnan Akhunzada, Imran Ashraf, Nikola Ivković, Shahbaz Pervez   +7 more
wiley   +1 more source

AI-Driven Security: Detecting Cyber Attacks in IoT Networks. [PDF]

Sensors (Basel)
Awan JH, Safdar M, Shirazi MA, Kim MY.
europepmc   +1 more source

Too good to be true: Synthetic AI faces are more average than real faces and super‐recognizers know it

British Journal of Psychology, Volume 117, Issue 4, Page 1279-1294, November 2026.
Abstract The AI revolution has produced synthetic faces that often appear more human than photos of real people. We tested whether individual differences in human face recognition ability explain variation in discriminating AI from real faces. Super‐recognizers – people with exceptional ability to recognize human faces (N = 36) – outperformed a typical
James D. Dunn, David White, Clare A. M. Sutherland, Elizabeth J. Miller, Ben A. Steward, Amy Dawel   +5 more
wiley   +1 more source

A segmentation-guided CNN-Vision transformer feature fusion framework for multi-class breast ultrasound image classification. [PDF]

PLoS One
Wu M, Wang J.
europepmc   +1 more source

Few Shot Learning for Flame State Monitoring From Limited Visible and Infrared Images

Expert Systems, Volume 43, Issue 11, November 2026.
ABSTRACT The success of machine learning in image‐based combustion monitoring requires big data, which is costly, and even impossible in industrial applications. To address this, we introduce metric‐based few shot learning for combustion monitoring and classification, to the best of our knowledge, for the first time.
Ruiyuan Kang, Dimitrios C. Kyritsis, Panos Liatsis   +2 more
wiley   +1 more source

Structured Multimodal Deep Learning improves Genomic Prediction in Future Environments. [PDF]

Genetics
Potze A, van Eeuwijk F, Athanasiadis IN.
europepmc   +1 more source

Socio‐Technical Risk‐Informed AI‐Driven Automation Trustworthiness Evaluation (ST‐RATE): Part 1‐Conceptualization

Risk Analysis, Volume 46, Issue 11, November 2026.
ABSTRACT The growing integration of artificial intelligence (AI)‐driven technologies into nuclear power plant (NPP) operations and maintenance holds significant potential to enhance safety, operational efficiency, and reliability. However, deploying such AI‐driven automation technologies in high‐consequence settings requires a rigorous, traceable, and ...
Muhammad Hammad Khalid, Ha Bui, Ahmad Al Rashdan, Zahra Mohaghegh   +3 more
wiley   +1 more source

Optimizing the Cascade Deep Neural Network Parameters Using an Egret Swarm Optimisation Algorithm: An Application to PID Tuning for the AVR with Shallow Controller. [PDF]

Biomimetics (Basel)
Elhawat M, Altınkaya H.
europepmc   +1 more source

Intelligent Distributed Optical Fiber Sensing in Transportation Infrastructures: Research Progress, Applications, and Challenges

Advanced Photonics Research, Volume 7, Issue 10, October 2026.
Distributed optical fiber sensing (DOFS) is reviewed as a transformative technology for intelligent monitoring of transportation infrastructures. Advances in sensing fibers, cable design, and data analytics are summarized alongside representative field applications.
Xin Gui, Fanhao Zeng, Yunchuan Zhang, Yiming Wang, Jiaqi Wang, Changjia Wang, Xuelei Fu, Sheng Li, Fang Liu, Lina Yue, Jinpeng Jiang, Zhengying Li   +11 more
wiley   +1 more source

iDCF: Interpretable deconvolution of cell fractions via biologically-informed deep learning using scRNA-seq data. [PDF]

PLoS Comput Biol
Guo H, Wu T, Wang W, Jiang Y, Li G, Nie L, Jia Y, Quan L, Huang M, Lyu Q.   +9 more
europepmc   +1 more source