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297 results for “Deep Learning (DL)”
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Research ArticleOpen accessEvery word in the titleEnhancing Fleet Management with GPS Data in Port Terminals: A Deep Learning Architecture for Truck Position PredictionMohammed El Karkraoui, Hicham AttariuasEffective truck fleet management in port terminals is crucial for improving operational efficiency and reducing delays. However, GPS-based positioning systems often face limitations in port environments due to signal obstructions and network issues. This study explores the utilization of advanced methods for deep learning, particularly Recurrent Neural Networks (RNNs) for predicting truck positions when GPS signals are unavailable or unreliable. … …Journal of Computer Science, Vol. 21, Issue 10 · 16 Dec 2025 · 2,271 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleDeep Sense: Deep Learning for Early Staging the Onset of Diabetes Emanating Recognition of Activity PatternsMohammed Shamsul Alam, Erfanul Hoque Bahadur, Md Fokrul Islam Khan et al.This study presents a comprehensive framework for Human Activity Recognition (HAR) using smartphone sensor data, with a specific focus on identifying activities associated with diabetic risk factors. We investigate the efficacy of two deep learning architectures (Long Short-Term Memory (LSTM) networks and Graph Convolutional Networks (GCNs)) for activity recognition under conditions of limited training data. To address data scarcity, we … …Journal of Computer Science, Vol. 21, Issue 10 · 15 Dec 2025 · 2,268 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleUsing Deep Learning to Support Clinical Decision-Making: The Case of Alzheimer’s Disease DiagnosisNawal Mohamed Bahy Eldin, Ghada A. El Khayat, Abeer A. AmerAlzheimer’s disease is a chronic, progressive brain disorder that leads to a gradual decline in memory and cognitive functions. In this study, N-VGG16, an advanced deep learning model, is proposed. The model builds upon the VGG16 architecture, incorporating key enhancements to improve its ability to classify neurodegenerative conditions. The model processes structural neuroimaging data using a refined pipeline that applies … …Journal of Computer Science, Vol. 21, Issue 10 · 11 Dec 2025 · 3,383 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleRefining Chest X-ray Interpretation with Deep Transfer Learning TechniquesR. Sriramkumar, K. Selvakumar, J. JeganChest X-rays are essential diagnostic tools for thoracic diseases, but different doctors' interpretations can differ greatly, which frequently results in inconsistent diagnoses. By using deep transfer learning techniques, this study seeks to improve the accuracy of Chest X-ray interpretations. More accurate and effective analysis can be accomplished with the growing potential of artificial intelligence (AI) in medical imaging, especially through … …Journal of Computer Science, Vol. 21, Issue 10 · 27 Nov 2025 · 2,644 accessesView PDFCite
Review ArticleOpen accessEvery word in the titleUnveiling Skin Cancer: A Review of Deep Learning Techniques for DetectionGoutham Lal Shanmughamadom Harilal, Tamilselvi PanneerselvamEarly identification is essential for successful treatment and better patient outcomes since skin cancer is caused by damage to DNA in skin cells, which can result in genetic abnormalities and the possibility of metastasis. The present systematic review scrutinizes the efficacy and obstacles of early detection techniques, which differentiate between benign and malignant lesions by examining lesion attributes such as … …Journal of Computer Science, Vol. 21, Issue 9 · 23 Oct 2025 · 2,602 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleHybrid Deep Learning Models for Text Classification: Performance Evaluation of TriDistilBERT and BiGRU ArchitecturesAmira Samy TalaatText can be a valuable source of information, but its unstructured nature makes analysis challenging and time-consuming. Machine Learning (ML) algorithms can efficiently analyze and structure text, enabling organizations to automate processes and uncover insights that support better decision-making. This study focuses on applying ML to a classification problem using two datasets. Four deep learning models are introduced, combining Bi … …Journal of Computer Science, Vol. 21, Issue 9 · 10 Oct 2025 · 2,792 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleTwitter Sentiment Analysis Using Machine Learning and Deep Learning TechniquesSafa Khalid Al Sarayrah, Noor Mahmoud Alkudah, Hesham Yousef Al-kharabshehThis research investigates the use of Machine Learning (ML) and Deep Learning, including BiLSTM approaches, for Sentiment Analysis (SA) of consumer reviews on social media sites. Businesses are increasingly depending on online reviews to determine customer satisfaction due to social media's explosive growth. We used three classification models, the assessment of these attitudes uses Naive Bayes (NB), Support Vector Machine … …Journal of Computer Science, Vol. 21, Issue 8 · 1 Sep 2025 · 6,813 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA Combined Deep Learning Model with Attention Mechanism for Detection of Implant Manufacturer Using X-Ray ImagesAttar Mahay Sheetal, K. SreekumarShoulder replacement surgery is one of the invasive techniques in orthopedic disciplines that replaces dead shoulder joints with prostheses made from polyethylene and metal components. To perform the surgery, there is a need to know the implant accessories and manufacturer of the implant. Some problems arise in a situation where the patient experiences pain and shoulder malfunctions that need replacement, … …Journal of Computer Science, Vol. 21, Issue 6 · 12 Jun 2025 · 3,252 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleImproving the Eastern Arabic Hand Written Digits Recognition Using Deep LearningHamdy Morsy, Hashim M. Hasanien et al.Convolutional neural networks CNNs or simply deep learning was designed for the challenging of object recognition such as digits, characters and even objects that can be classified. The deep convolutional networks are designed to be trained through using a large dataset of the classes. The degree of complexity of recognizing handwritten digits are different from person to person and even … …Journal of Computer Science, Vol. 21, Issue 6 · 27 May 2025 · 4,930 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleDeep Learning-Based Approach for Identification of Potato Leaf Diseases Using Wrapper Feature Selection and Feature ConcatenationMuhammad Ahtsam Naeem, Muhammad Asim Saleem, Jarrar Amjad et al.The potato is a widely grown crop in many regions of the world. In recent decades, potato farming has gained incredible traction in the world. Potatoes are susceptible to several illnesses that stunt their development. This plant seems to have significant leaf disease. Early Blight and Late Blight are two prevalent leaf diseases that affect potato plants. The early detection … …Journal of Computer Science, Vol. 21, Issue 5 · 12 May 2025 · 5,171 accessesView PDFCite