NEWS
Editor: M. Rehena Sulthana
pISSN: XXXX-XXXXeISSN: XXXX-XXXX
2026 Vol.1 No.1
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|---|---|
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A Transparent Baseline CNN for CIFAR-100: Design and Pilot Evaluation in a Reproducible Learning Framework
Madhan Raj Gopi Akila, Charan Tharak Varma, Sai Charan Reddy, A. Abinay, Prasanna Ranjith Christodoss, Andino Maseleno
CIFAR-100 remains a useful benchmark for image classification because it is small in image size yet challenging in class diversity. In this paper, researchers document the design and pilot evaluation of a compact CNN built for an academic Neural Networks…
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1-10 |
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Comparative Study of Liveness Detection Methods for Mitigating Facial Spoofing Attacks
V. Christy, H. Chandramouli
Despite the success of FRS in security-sensitive scenarios, they are still susceptible to presentation attacks, including printed photos, replayed video and 3D masks, which require a strong liveness detection system. This study categorises approaches to face liveness detection into deep…
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11-21 |
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Adaptive Hybrid Machine Learning Framework for Insider Threat Detection in Cloud-Based Enterprise Environments
K. Selvamani, S. Kanimozhi, S. K. Muthusundar, H. Riasudheen, Rahul Panakkal, Raja Brahmendra Chowdary Veerepalli, Srinath Venkatesan, Varun Kumar Nomula
Insider threats are among the most complex and persistent security issues in cloud-based enterprise systems, as they can be carried out by someone who has legitimate access to the system or network. In this paper, researchers present an Adaptive Hybrid…
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22-32 |
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Quantum Generative Adversarial Networks for Image Generation and Adversarial Image Detection
A. Shyam Sundhar, J. Angelin Jeba, Bhopendra Singh, S. J. Vimal Aravintha, Sureshkumar Somayajula, Ahmed J. Obaid
Adversarial attacks pose a major challenge to classical deep learning systems, often leading to misclassification and reduced model reliability. To address this limitation, researchers propose a hybrid Quantum Generative Adversarial Network (QGAN) that integrates quantum feature extraction with classical adversarial…
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33-48 |
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An AI-Driven Pronunciation Feedback and Exercise Generation System using Real-Time Phoneme Analysis for Language Learning
Sai Vishaal Saibaskar, S. Rubin Bose, P. Taroon, R. S. Gaayathri, Sebastiana Salerno, Anurag Hazarika, Targyn A. Nauryz, Hernández Hernández
In this paper, researchers present a system for generating pronunciation feedback and exercises that aims to improve language acquisition through real-time phoneme analysis. The proposed system is built on advanced speech recognition and Generative Artificial Intelligence (GenAI) techniques to assess…
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49-62 |