7 Chandigarh University Students Win Prestigious IndiaAI Fellowship Awarded by the Ministry of Electronics & Information Technology

Demonstrating academic excellence and a strong interest in AI-related domains, seven students of Computer Science Engineering ...
The Business & Financial Times on MSN

Combating mobile money/digital fraud in Ghana: Strategies for securing digital payments

By Dr. Richmond Atuahene1.0 Introduction/ BackgroundGlobalization and digitization are two major trends that will shape the future of nations. Despite the many challenges associated with adapting to ...
DATAQUEST

Google Cloud enters AI-native cybersecurity race against Anthropic and OpenAI

Enterprise cybersecurity has shifted from human‑driven patching to autonomous AI warfare. Google Cloud’s Threat Defence initiative redefines contextual triage, remediation, and India’s regulatory edge ...
IEEE

Anomaly Detection in IoT Environment Using Machine Learning: A survey

Abstract: The explosive growth of the Internet of Things (IoT) has introduced vast amounts of data and unprecedented security challenges, making effective anomaly detection in IoT environments a ...
Scientific Research Publishing

An, J. and Cho, S. (2015) Variational Autoencoder Based Anomaly Detection Using Reconstruction Probability. Special Lecture on IE, 2, 1-18.

ABSTRACT: Video-based anomaly detection in urban surveillance faces a fundamental challenge: scale-projective ambiguity. This occurs when objects of different physical sizes appear identical in camera ...
IEEE

Anomaly Detection in IoT Networks: A Deep Learning Approach Using Autoencoders

Abstract: The current fast proliferation of the Internet of Things (IoT) networks has made anomaly detection and security more difficult. Traditional methods are not able to detect hostile activities ...
Scientific Research Publishing

Traffic Object Detection Using YOLOv12 ()

Traffic monitoring plays a vital role in smart city infrastructure, road safety, and urban planning. Traditional detection systems, including earlier deep learning models, often struggle with ...