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2,283 papers
This paper presents SecureVision, an evaluation of the use of deep learning to enhance women&s;s safety by detecting visible threats. This will include an in-depth discussion of Convolutional Neural Networks (CNNs) and identifying violent and aggressive behavior based on surveillance videos. The evaluation will explain...
An extended acceptance model that incorporates perceived content quality, trust, perceived risk, self-regulated learning, self-regulated learning, and digital–AI literacy is developed and tested and discusses theoretical and practical implications for platform design and institutional policy.
This invaluable text explains how to compile and structure different forms of writing in occupational therapy, using easy-to-follow templates for capstone projects and publishable manuscripts. Now aligned with the 7th edition of APA standards, the book can be used to help in the writing of needs assessments, case repor...
As ESG principles and cutting-edge digital innovations intersect in the creative economy, strategic leadership is changing in ways never before imaginable. This chapter discusses the role of Explainable Artificial Intelligence (XAI) in supporting ESG-driven decision intelligence by allowing a leader to make transparent...
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This study proposes the HSEL model to improve the accuracy of fire risk predictions based on meteorological data and real-time IoT integration. The main issues with individual models are their susceptibility to bias and overfitting, while conventional stacking methods have not been able to effectively optimize the cont...
The purpose of this study is to examine factors that impact the sustainability of the organizations in the engineering, electrical and information technology in Jordan and examine the moderating role of digital leadership. The data of 396 leaders were collected and analyzed using the quantitative approach and PLS-SEM....
The increasing use of AI-enabled surveillance in policing has created heterogeneous networks integrating IoT sensors, machine learning models, and multi-agency information systems across diverse vendors and jurisdictions. This chapter proposes an ethical, legal, and governance framework for AI-driven smart surveillance...
Artificial intelligence (AI) and machine learning (ML) are increasingly applied to road traffic congestion prediction, but heterogeneous outcomes, models, horizons, and evaluation practices limit comparability. The objective of this study was to synthesize methods, applications, validation, explainability, and reproduc...
This chapter examines the relationship between AI and the UK financial sector, focusing on the opportunities, risks, and regulatory challenges arising from increasing AI adoption. It begins by outlining the significance of the financial sector within the UK economy and society, emphasising its role in supporting econom...
Background/Objectives: Artificial intelligence is increasingly used in medicine, particularly in orthopedics, to support medical image interpretation, diagnosis, clinical decision-making, and treatment selection. Its integration into clinical practice depends largely on doctors’ perceptions and attitudes toward this te...
This review synthesizes the current literature on explainable artificial intelligence and fairness in artificial intelligence applications for acute stroke management, identifies persistent challenges, and outlines recommendations for the development of equitable and trustworthy systems in stroke care.
SAFE–AI (Structured and Automated Framework for Explainable AI), a novel method for clinical decision making that combines the strengths of clinical expert knowledge with LLMs in an ontology–driven model that minimizes hallucinations using strict rules, is presented.
MIT Statistics and Data Science Center Director Alexander (Sasha) Rakhlin shares important considerations for departments and institutions.
GPT-Lab
· gpt-lab.eu
Oct 8, 2026
Exploring how generative AI could make machine vision more accessible to businesses. The post GenEye in a Box: Making Machine Vision Something You Can Just Ask For appeared first on GPT-Lab.
By rethinking how large cloud computing systems operate, Associate Professor Christina Delimitrou seeks to make data centers more energy efficient.
Training AI agents with reinforcement learning can be challenging because their tools, context, and decision-making are managed by complex frameworks. Agent Lightning connects existing agents to RL training, making it easier to improve them without rebuilding them. The post Agent Lightning v1.0: A 3,500-Line Lightweight Agentic RL Framework for Training Agents with Real Harnesses appeared first on Microsoft Research.
An ongoing survey tracks the latest AI accelerator systems to keep hardware relevant for Lincoln Laboratory staff and sponsors.
Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity. The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.
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