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147 results for “Deep Learning Models”
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Research ArticleOpen accessIn the abstractAnomaly Detection Based on Vision Transformer Model and Texture FeaturesMohammed Lahraichi, Abdelhafid Berroukham, Khalid HousniAnomaly detection is one of the video surveillance applications,which aims to detect and analyze abnormal behaviors and risky situations inorder to prevent accidents. Various deep learning models have beenpreviously developed for this purpose, such as CNN, RNN, and VisionTransformer, each one has its strengths and weaknesses based on the qualityof input data. This paper proposes a novel approach based on … …Journal of Computer Science, Vol. 21, Issue 7 · 10 Jul 2025 · 3,689 accessesView PDFCite
Review ArticleOpen accessIn the abstractWeb Scraping for Product Recommendations: A Review of Techniques and ApplicationsAmarinder Kaur, Deepak PrasharA comprehensive method for developing a reliable product recommender system leveraging sophisticated web scraping technologies, machine learning, and natural language processing techniques. The proposed system addresses key challenges in personalized product recommendation, including the difficulty of integrating diverse data from multiple e-commerce platforms, ensuring data quality, and improving recommendation accuracy to enhance user experience. Specifically, this research tackles issues related … …Journal of Computer Science, Vol. 21, Issue 6 · 21 Jun 2025 · 4,234 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Vertical Stacking-Based Ensemble Deep Learning Model for Early Diagnosis of Alzheimer's Disease Using Multimodal MRI ScansParvatham Niranjan Kumar, Lakshmana Phaneendra MaguluriEarly detection of Alzheimer's Disease (AD) is crucial for timely interventions that can slow disease progression, enhance quality of life, and assist with future planning. Convolutional Neural Networks (CNNs) are an efficient method for processing image-based data. In this work, we used CNN-based deep learning models to extract structural information from structural MRI (sMRI) and brain neuron connectivity patterns from … …Journal of Computer Science, Vol. 21, Issue 6 · 14 Jun 2025 · 3,106 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Enhanced Algorithm for Small Object Detection based on Thermal Imaging Using YOLOv8-EPBRavina Gupta, Sarika Jain, Manoj KumarObject detection is one of the most important and challenging problems in the computer vision domain. Using the power of deep models, researchers have carefully explored and made significant contributions to increasing the effectiveness of object detection and related tasks, such as object identification, localization, and segmentation. This progress is due to the rapid progress of deep learning in the … …Journal of Computer Science, Vol. 21, Issue 6 · 13 Jun 2025 · 4,218 accessesView PDFCite
Research ArticleOpen accessIn the abstractA 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 · 3,257 accessesView PDFCite
Review ArticleOpen accessIn the abstractA Succinct Review on Identification of Network Anomalies and Protection in Cyber-Physical SystemsShalini Kumari, Chander Prabha, Prakash Srivastava et al.Advanced cyberattacks outperform traditional threat detection methods in the rapidly expanding cybersecurity field. Advanced Machine Learning (ML) algorithms can detect network traffic and system problems using AI-based Anomaly Detection (AD) for cybersecurity in real-time. Signature-based systems may overlook new and subtle threats. This paper examines Artificial Intelligence (AI) driven AD systems' design, methodology, and efficacy. The process includes data preprocessing … …Journal of Computer Science, Vol. 21, Issue 6 · 29 May 2025 · 5,247 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhancing Indian Language Speech Recognition Systems with Language-Independent Phonetic Script: An Experimental ExplorationJose Stephan, Muthayyan Kamalam JayakumarIndia has a distinct linguistic profile that makes it extremely challenging to train Automatic Speech Recognition (ASR) systems correctly because most Indian languages have limited training material and are generally low-resource in nature. However, due to their similarity in phonemes, these languages offer an opportunity to create a single speech recognition technology. This study proposes an optimized phonetic script which … …Journal of Computer Science, Vol. 21, Issue 5 · 9 May 2025 · 6,545 accessesView PDFCite
Research ArticleOpen accessIn the abstractIntelligent Software Testing for Test Case Analysis Framework Using ChatGPT with Natural Language Processing and Deep Learning IntegrationAlaa Najmi, Mohamed El-DosukyEffective testing scenarios are necessary to guarantee the dependability and Caliber of software. Conventional techniques for creating these scenarios frequently involve a great deal of manual labor and might not fully cover all software requirements. In order to improve the automation and Caliber of software testing scenario development, this study investigates the combination of Natural Language Processing (NLP) and Deep … …Journal of Computer Science, Vol. 21, Issue 5 · 1 May 2025 · 98,043 accessesView PDFCite
Review ArticleOpen accessIn the abstractCybercrime in the AI Era: Definitions, Classification, Severity Assessment and the Role of AI in Combating ThreatsNorah Sultan Alshahrani, Fahd Saleh Alotaibi, Khaled Hamed Alyoubi, Muhammad Sher RamzanThe growing prevalence, complexity and financial impact of cybercrimes pose significant challenges for law enforcement agencies worldwide. Many organizations are utilizing different technologies such as cloud technology to improve speed, accuracy, and reliability. However, without proper security measures, the risk is still vital against cyberattacks. Cybercrime can lead to various negative outcomes, including theft, fraud, financial losses, a decline in … …Journal of Computer Science, Vol. 21, Issue 3 · 12 Feb 2025 · 7,164 accessesView PDFCite
Research ArticleOpen accessIn the abstractClassification of Arabic Comments to Detect Cyberbullying from Social Media Using Convolutional Neural Network and Meta-LearningSarah Mansour Elgaud, Mustafa Ali Abuzaraida, Abdullah AlshehabAs a result of the proliferation of social media, cyberbullying has become widespread in the Arab community on social media and cyberbullying has become a concern targeting individuals and may cause some serious side effects. The problems of Natural Language Processing (NLP) for the Arabic language and its complexity make it difficult to classify texts accurately. In recent years, deep … …Journal of Computer Science, Vol. 21, Issue 3 · 10 Feb 2025 · 6,288 accessesView PDFCite