Syed Rameez Naqvi

MolPaQ: Modular Quantum-Classical Patch Learning for Interpretable Molecular Generation

Syed Rameez Naqvi, Lu Peng

Molecular generative models must jointly ensure validity, diversity, and property control, yet existing approaches typically trade off among these objectives. We present MOLPAQ, a modular quantum-classical generator that assembles molecules from quantum-generated latent patches. A \b{eta}-VAE pretrained on QM9 learns a chemically …

CodeT5-RNN: Reinforcing Contextual Embeddings for Enhanced Code Comprehension

Md. Mostafizer Rahman, Ariful Islam Shiplu, Yutaka Watanobe, Md Faizul Ibne Amin et autres

Contextual embeddings generated by LLMs exhibit strong positional inductive biases, which can limit their ability to fully capture long-range, order-sensitive dependencies in highly structured source code. Consequently, how to further refine and enhance LLM embeddings for improved code understanding remains an open …

A novel nature-inspired feature selection algorithm for efficient moisture estimation in fruits using RF-Sensed data

Ali Roman, Youssef N. Altherwy, Syed Rameez Naqvi, Anas Alsuhaibani

We propose a novel hybrid nature-inspired feature selection algorithm that unifies update mechanisms from Grey Wolf Optimizer (GWO), Artificial Bee Colony (ABC), and Bat Algorithm (BA). The resulting framework enables optimized machine learning models for precise grape moisture estimation from radio frequency …

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Theoretical modeling and AI-driven approximation of energy spectrum behavior in nano-engineered films

M. Kamran, Sajjad Ali Haider, Tallha Akram, Syed Rameez Naqvi et autres

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A Hybrid Deep Learning-ViT Model and A Meta-Heuristic Feature Selection Algorithm for Efficient Remote Sensing Image Classification

Bilal Ahmed, Syed Rameez Naqvi, Tallha Akram, Peng Lu et autres

Recent deep learning techniques driven by large datasets demonstrate the significant impact of feature learning in remote sensing for land use and cover classification, particularly exemplified by CNNs. While the pre-trained models showed good classification performance, they struggled to classify remote-sensing images …

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Integrating Feature Selection and Deep Learning: A Hybrid Approach for Smart Agriculture Applications

Ali Roman, Md. Mostafizer Rahman, Sajjad Ali Haider, Tallha Akram et autres

This research tackles the critical challenge of achieving precise and efficient feature selection in machine learning-based classification, particularly for smart agriculture, where existing methods often fail to balance exploration and exploitation in complex, high-dimensional datasets. While current approaches, such as standalone nature-inspired …

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BioSkinNet: A Bio-Inspired Feature-Selection Framework for Skin Lesion Classification

Tallha Akram, Fahdah A. Almarshad, Anas Alsuhaibani, Syed Rameez Naqvi

Melanoma is the deadliest form of skin cancer, with an increasing incidence over recent years. Over the past decade, researchers have recognized the potential of computer vision algorithms to aid in the early diagnosis of mel... | Find, read and cite all …

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Review of: "Adoption of Machine Learning Methods for Crop Yield Prediction-based Smart Agriculture and Sustainable Growth of Crop Yield Production – Case Study in Jordan"

Syed Rameez Naqvi

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Opportunistic eXtemporarY 5G Encrypted Networks (OXYGEN) with Sidelinks

Colin Funai, Christopher VanderValk, Syed Rameez Naqvi, Bishal Thapa

Device-to-device (D2D) communications provide users the means to communicate directly with one another regardless of the presence of existing infrastructure, such as cellular base stations or WiFi access points. This independence provides the flexibility for spatial reuse of license spectrum, allow selected …

Review of: "An Intelligent Analytics for People Detection Using Deep Learning"

Syed Rameez Naqvi

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Dermo‐Optimizer: Skin Lesion Classification Using Information‐Theoretic Deep Feature Fusion and Entropy‐Controlled Binary Bat Optimization

Tallha Akram, Anas Alsuhaibani, Muhammad Attique Khan, Sajid Ullah Khan et autres

ABSTRACT Increases in the prevalence of melanoma, the most lethal form of skin cancer, have been observed over the last few decades. However, the likelihood of a longer life span for individuals is considerably improved with early detection of this malignant illness. …

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A Nonparametric Split and Kernel-Merge Clustering Algorithm

Khurram Shehzad Khan, Atiq Ur Rehman, Adnan Ahamed Khan, Syed Rameez Naqvi et autres

This work proposes a novel Split and Kernel-Merge Clustering (S-KMC), a nonparametric clustering algorithm that combines the strengths of hierarchical clustering, partitional clustering, and density-based clustering. It consists of two main phases: Splitting and Merging. In the Splitting phase, a ranking-based operator …

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