Putra Sumari

Investigation of brain connectivity alteration in the non-severe traumatic brain injury: an emotional condition study

Hazim Omar, Aini Ismafairus Abd Hamid, Muhammad Abdul Rahman, Nor Azila Noh et autres

Background: Traumatic brain injury (TBI) frequently results in persistent emotional and cognitive dysfunction, yet the neural mechanisms underlying these deficits remain incompletely understood. This study examined the impact of non-severe TBI (nTBI) on emotional processing, with a focus on brain activation, functional …

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Advanced and Classical Selection Methods in Genetic Algorithms: A Comprehensive Comparative Analysis

Husam S. Mashaqbeh, Putra Sumari, Hamza A. Mashagba, Mohammed Hashem Almourish et autres

Selection mechanisms critically influence the convergence behavior and solution quality of Genetic Algorithms (GAs). This study presents a rigorous empirical comparison of six selection methods: three classical methods—Random Selection, Roulette Wheel Selection (RWS), and Tournament Selection (TS)—and three adaptive methods: Fitness-Distance Balance …

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Image2Recipe Classifier: Malaysia Fish Delicacies Image Classification Using Deep Learning Methods

Valliappan Raman, Putra Sumari, M. Prabhavathy, M. Karthiga

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Deep Special Food Classifier: Malaysian Special Food Recognition and Classification Using Convolution Neural Network

Putra Sumari, Valliappan Raman, M. Prabhavathy, K. R. Shanmugapriyaa

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CAD System Utilizing UNet and Hough Transform for Automated Measurement of Fetal Head Circumference and Age in 2D Ultrasound Images

Hamzah Jaber, Ahmed Abed Mohammed, Bo Zhang, Mustafa M. Abd Zaid et autres

Two-dimensional (2D) medical ultrasound is a widely used imaging modality for the anatomical and functional assessment of fetal development due to its low cost, availability, real-time capability, and the absence of radiation hazards. Head circumference (HC) is an essential biometric to measure …

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Optimizing Lemongrass Disease Detection: A Comparative Analysis of Neural Architecture Search (NAS) with convolutional neural network (CNN) and Transfer Learning models

Putra Sumari, Ahmed Abed Mohammed, Mustafa M. Abd Zaid, Wenjing Wu et autres

Lemongrass is an economically important crop that faces significant disease challenges, making timely and accurate detection crucial for enhancing crop yield and quality. Traditional detection methods rely on manual observation, which can be subjective and inefficient. This study uses convolutional neural network …

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Recurrent Neural Networks and its Applications in Time Series Data

Muhannad Akram Nazzal, Nada Khalil Al-Okbi, Canan Batur Şahin, Gang Hu et autres

Recurrent Neural Networks (RNNs) have been extensively embraced for sequencing analysis and sequential data modelling, especially time series data. This paper delves into the principles and applications of the RNNs concentrically time series analysis. The advantages of time series RNNs, including long …

Understanding the Role of Data in Deep Learning

Mohammad H. Almomani, Putra Sumari, Davut İzci, Hung Vo Thanh et autres

The purpose of this paper is to discuss the importance of data in deep learning and to describe the process of finding and preparing instructive deep learning datasets. The process of building the dataset and enhancing the quality of data relevant to …

Introduction to Artificial Intelligence and Deep Learning

Saleh Ali Alomari, Putra Sumari, Raed Abu Zitar, Faiza Gul et autres

Artificial intelligence (AI) is a game-changing technology that is revolutionizing numerous sectors and domains through automation, enhanced decision-making, and advanced data processing. A significant milestone in AI development has been the achievement of deep learning, a branch of machine learning that employs …

Future Computational Power of AI Hardware: A Comparative Analysis of GPUs and TPUs

Nada Khalil Al-Okbi, Mahmoud Abdel-Salam, Haming Jia, Peiying Zhang et autres

In order to enhance artificial intelligence, as it is being developed further, more powerful computational resources are required. Within the scope of the hardware solutions for AI training and inference, the use of graphical processing units and tensor processing units has gained …

A semi‐supervised multi‐connection contrastive learning framework for x‐ray lung segmentation based on mutual distillation

Xiangrui Zeng, Nhayan Abdulla, Baixue Liang, Ola A. Al-wesabi et autres

BACKGROUND: Deep learning techniques have demonstrated impressive results in medical image segmentation tasks. However, building labeled data for fully supervised models requires significant labor, which can be costly. Additionally, medical devices often prioritize higher data security, smaller size, and improved portability, which …

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Non-overlapping Patch-Based Pre-trained CNN for Breast Cancer Classification

Lamyaa Sabeeh Ashour, Ahmed Abed Mohammed, Mustafa M. Abd Zaid, Putra Sumari et autres

Breast cancer (BC) significantly impacts women's mortality rates and requires early detection to improve survival chances and enable appropriate treatment. Thus, a computer-aided system with high performance can speed up this process. A convolutional neural network (CNN) is considered sensitive to insufficient, …

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