Ali Raza

A hierarchical BYOL-based deep learning framework for explainable leaf disease recognition utilizing self-supervised learning and symptom preserving

Ali Raza, Heba Abdelgader Mohammed, Fareeha Hanif

Accurate leaf disease recognition remains challenging because supervised deep learning models require substantial labeled data and may struggle to distinguish diseases with overlapping color, texture, and lesion patterns. This study proposes a hierarchical self-supervised learning framework that combines Bootstrap Your Own Latent …

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Relationship between Anthropometric Measures and Physical Performance in Cricketers: A Cross-Sectional Analysis

Umnah Ahmed, Amenah Ghaffar, Muhammad Omer Rehman, Ali Raza et autres

Background: Cricket requires coordinated movement, strength, agility, and physical conditioning, while anthropometric characteristics may provide useful contextual information for athlete profiling. However, the relationship between anthropometric characteristics and functional movement performance in cricketers remains insufficiently characterized. Objective: To determine the associations between …

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COOT-CNN: joint architecture and training-strategy optimization for binary colorectal histology patch classification

Ali Raza, Amira Elsir Tayfour Ahmed, Mohamed Kentour, Fareeha Hanif

Colorectal histology classification remains challenging because subtle morphological differences, staining variability, and inappropriate model configurations can reduce generalization. This study proposes COOT-CNN, a lightweight convolutional neural network in which architectural design and training strategy are optimized jointly through the COOT metaheuristic. The …

pk, cy, sa, gb (code pays fourni par la source)

COOT-CNN: A metaheuristic-optimized deep learning framework based on lightweight convolutional architectures for multi-class robust crack detection in concrete infrastructures

Ali Raza, Fareeha Hanif

Efficient colorectal cancer classification from histopathological images utilizing lightweight convolutional neural networks

Ali Raza, Fareeha Hanif, Heba Abdelgader Mohammed

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Chronological Review and Performance Analysis of YOLO-Based Deep Learning Frameworks in Complex Geospatial Environments

Ali Raza, Fareeha Hanif

The rapid evolution of YOLO (You Only Look Once) models has transformed object detection into a real-time, scalable solution across a variety of domains. This article presents a comprehensive and chronological review of YOLO-based frameworks, emphasizing their adoption in remote sensing applications. …

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Mathematical modeling and symmetry analysis of the impact of vaccination on the dynamics of influenza virus disease

Ali Raza, Ibtehal Alazman, Syed T. R. Rizvi, Kashif Ali et autres

pk, sa, Ghana (code pays fourni par la source)

Modeling global asymptotic stability of malaria dynamics with structured infectious population

Kashif Ali, Mohamed A. A. Abdelkawy, Ali Raza, Sulaimon F. Abimbade et autres

pk, sa, Nigéria (code pays fourni par la source)

Corporate Digital Responsibility and Artificial Intelligence Ethics: A Multi-Study Approach

Asifa Younas, Muhammad Ishtiaq Ishaq, Ali Raza

Over the past two decades, advances in digital technology have made it possible to create a wide range of systems with a wide range of capabilities. According to (Brynjolfsson & McAfee, 2017), however, these unprecedented opportunities for empowerment come with ethical and …

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Laplacian spectra and structural insights: applications in chemistry and network science

Ali Raza, Mobeen Munir

This paper presents the practical applications of Laplacian and signless Laplacian spectra across various fields including theoretical chemistry, computer science, electrical engineering, and complex network analysis. By focusing on the spectrum-based evaluation of generalized mesh network and ladder graphs, the research aims …

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Investigating Signless Laplacian Spectra and Network Topology in Helical Phenylene‐Quadrilateral Structures

Fareeha Hanif, Ali Raza, Md. Shajib Ali

This study investigates the spectral and topological properties of rounded knot networks , a helical extension of phenylene quadrilateral structures, through signless Laplacian spectral analysis. Motivated by the need to understand how helical topology influences network dynamics and robustness, we derive exact …

pk, bd (code pays fourni par la source)

Neighborhood Face Index: A New Quantitative Structure Property Relationship ( QSPR ) Approach for Predicting Physical Properties of Polycyclic Chemical Compounds

Ali Raza, Muhammad Waheed Rasheed, Abid Mahboob, Mishal Ismaeel

ABSTRACT Topological indices (TIs) are numerical parameters that characterize the biochemical and physio‐chemical properties of compounds. These graph‐based descriptors are valuable tools for predicting key attributes, such as melting points, boiling points, bond energies, and bond lengths, based on the molecular structures …

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