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Author

Ruqiya Fatima

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Open access Aug 2026

NEUROIMAGING-BASED MCI PREDICTION USING DEEP LEARNING

An improved model based on the Xception architecture is created, building on previous deep learning techniques that use convolutional neural networks (CNNs) with channel attention mechanisms, to offer a dependable, accessible diagnostic tool to assist medical professionals in the early detection of Alzheimer's disease.

M. Misba, Afshan Fatima, Ruqiya Fatima · 0 citations
Open access Aug 2026

AN INTERPRETABLE SPEECH ANALYTICS FRAMEWORK FOR EARLY PARKINSON'S DISEASE IDENTIFICATION USING K-NEAREST NEIGHBORS

A prediction framework for Parkinson's disease identification based on speech data that makes use of the K-Nearest Neighbours (KNN) algorithm, a non-parametric and instance-based learning method that can achieve high accuracy in differentiating PD patients from healthy persons.

Ayesha T. Fathima, Safia Khanum, Ruqiya Fatima · 0 citations
Open access Aug 2026

A BLOCKCHAIN-BASED DECENTRALIZED FRAMEWORK FOR CERTIFICATE AUTHENTICATION AND ISSUER TRUST

A decentralized, blockchain-based issuer validation and certificate verification solution to overcome drawbacks of conventional verification techniques, which ensures data immutability and tamper resistance by storing certificate hashes on the blockchain using Ethereum.

Madiha Sadaf, Afshan Fatima, Ruqiya Fatima · 0 citations
Open access Aug 2026

PRIVACY-FOCUSED REDACTABLE BLOCKCHAIN WITH RESTRICTED ACCESS IN DECENTRALIZED ECOSYSTEMS

PriChain gives data owners the authority to manage who may access and alter their on-chain data, guaranteeing that redaction can only be carried out by authorized users while maintaining data confidentiality.

S. Kulsum, Lalitha Saroja Ch, Ruqiya Fatima · 0 citations
Open access Aug 2026

HIGH-PRECISION AERIAL OBJECT DETECTION MODEL UTILIZING YOLO V10 DEEP NEURAL NETWORK

The installation of a real-time visual tracking system with an active pan-tilt camera for indoor human motion detection is presented, which shows that the inclusion of YOLOv10 significantly improves detection precision and temporal consistency.

Ayman Javid Hussain, Lalitha Saroja Ch, Ruqiya Fatima · 0 citations
Review Open access Aug 2026

AUTOMATED DETECTION OF TUBERCULOSIS FROM CHEST X-RAY IMAGES USING DEEP LEARNING

A deep learning-based system that uses chest X-ray pictures to automatically detect tuberculosis, using transfer learning using MobileNetV2 and DenseNet architectures to classify chest Xrays as either TB-positive or Healthy, reaching notable accuracy.

Zoya Nasreen, Afshan Fatima, Ruqiya Fatima · 0 citations
Open access Aug 2026

REAL-TIME WEAPON AND THREAT DETECTION USING YOLOV12 WITH MULTI-SENSOR FUSION FOR ENHANCED SURVEILLANCE SYSTEMS

This study proposes an Advanced Surveillance Framework that makes use of YOLOv10, a next-generation real-time object detection algorithm that greatly outperforms conventional single-sensor approaches in precision, recall, and real-time responsiveness.

Sadiya Begum, Lubna Nausheen, Ruqiya Fatima · 0 citations

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