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109 results for “Deployment”
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Research ArticleOpen accessIn the abstractHybrid Pipelines for Intelligent Human Resources Text Classification: LLMs, RAG, and Generative AISoumia Chafi, Mustapha Kabil, Abdessamad KamoussThe digital transformation of Human Resources Information Systems (HRIS) requires advanced approaches to process unstructured textual data originating from Curriculum Vitae (CVs), cover letters, and job postings. Traditional text classification methods exhibit limitations when faced with current needs for contextual understanding and fine-grained skill detection. This paper proposes a hybrid pipeline combining advanced text classification, contrastive learning (SimCSE, Contriever), Retrieval-Augmented … …Journal of Computer Science, Vol. 22, Issue 4 · 22 Apr 2026 · 1,513 accessesView PDFCite
Research ArticleOpen accessIn the abstractPredictive Mathematical Modeling and Classification of Retail Sales Orders Using AI Machine Learning TechniquesMohammad Subhi Al-Batah, Mowafaq Salem Alzboon, Hamzeh ZureigatThis study presents a systematic mathematical model known as a low-code approach to classifying retail sales orders by size using AI machine learning techniques within the Orange Data Mining platform. Leveraging a real-world sales dataset sourced from Kaggle, we implemented and evaluated ten classification models, including ensemble learners (AdaBoost, Gradient Boosting), probabilistic classifiers (Naïve Bayes), distance-based methods (kNN), and interpretable … …Journal of Computer Science, Vol. 22, Issue 3 · 10 Mar 2026 · 1,573 accessesView PDFCite
Research ArticleOpen accessIn the abstractCascaded MNetV3UNet: A Lightweight Two-Stage Architecture for High-Precision Brain Tumor Segmentation in MRIMayuri Popat, Sanskruti PatelPrecise brain tumor segmentation is an essential but quite challenging process in MRI images because of their irregular shapes, heterogeneous appearance, and low contrast with surrounding tissues. While U-Net-based architectures have achieved significant success, their high computational complexity limits deployment on resource-constrained systems. In this study, a Novel two-stage cascaded architecture, MNetV3UNet, is introduced, which employs the light-weight MobileNetV3-Large as … …Journal of Computer Science, Vol. 22, Issue 2 · 23 Feb 2026 · 1,793 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Safe Method of Storing and Exchanging Electronic Health Records Using Smart Contracts and Blockchain Technology Using Fully Hashed Menezes-Qu-Vanstone AlgorithmMeenakshi Vashisth, Raju RanjanElectronic Health Records (EHRs) are essential for clinicians, patients, and researchers because they support timely care and informed decision-making. For this reason, digital health information must be collected, managed, and stored with strong protections to preserve privacy and prevent tampering. One approach to strengthening security is to use blockchain-based storage alongside smart contracts and controlled data sharing, which can help … …Journal of Computer Science, Vol. 22, Issue 2 · 21 Feb 2026 · 1,644 accessesView PDFCite
Research ArticleOpen accessIn the abstractIntelligent Traffic Light System Using Convolutional Neural Network to Optimize Vehicle Flow in IndonesiaBhustomy Hakim, Fergie Joanda Kaunang, Yemima Monica Geasela, Regina HillaryTraffic congestion remains a persistent challenge in major Indonesian cities due to rapidly increasing vehicle density and the continued reliance on fixed-time traffic signal scheduling. This study aims to develop an intelligent traffic light system that dynamically adjusts sequencing based on real-time road conditions. A dataset of 902 CCTV images was collected from intersections in six large cities across Indonesia, … …Journal of Computer Science, Vol. 22, Issue 2 · 17 Feb 2026 · 2,167 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Hybrid Grey Wolf Optimizer and Deep Transfer Learning-Based Intrusion Detection System for IoTKapil Shrivastava, Manish Tiwari, Prasun ChakrabartiThe rapid proliferation of Internet of Things (IoT) devices has driven significant advancements in connectivity and automation, but it has also introduced substantial cybersecurity risks, including intrusions and cyberattacks. To address these challenges, this study proposes a hybrid intrusion detection framework that combines advanced optimization techniques with ensemble deep learning to enhance detection accuracy and computational efficiency. The proposed framework … …Journal of Computer Science, Vol. 22, Issue 2 · 17 Feb 2026 · 1,512 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Novel Deep Learning Approach for Tomato Leaf Disease Detection Using Optimized CNN ArchitectureSunil K. Vithalani, Vipul K. DabhiEarly disease detection in plants is essential for sustaining agricultural yield and guaranteeing food security. A comparative analysis of transformer-based and convolutional based deep learning models for classifying tomato leaf diseases is presented. Specifically, it examines the performance of a Vision Transformer (ViT), tested both in a form of scratch training setup and through transfer learning, against well-known CNN architectures … …Journal of Computer Science, Vol. 22, Issue 1 · 7 Feb 2026 · 3,924 accessesView PDFCite
Research ArticleOpen accessIn the abstractOptimized YOLOv8 for Insect Detection in Agricultural Farms Using Edge Vision SystemsDeebalakshmi R., Adhithyaa S., Yoga Vignesh V., Balaji Ganesh RajagopalFarmers started to adopt smart gadgets like automated pest detection and kiosks for their work in light of the AI revolution in agriculture. These kinds of technologies help farmers identify pest infestations early, which allows the farmers to take action accordingly and prevent crop loss. This results in improvement in both yield and sustainability. However, running an advanced model such … …Journal of Computer Science, Vol. 21, Issue 11 · 28 Jan 2026 · 2,655 accessesView PDFCite
Research ArticleOpen accessIn the abstractRecognizing Sign Language Gestures Using a Hybrid Spatio-Temporal Deep Learning ModelMeryem Cherrate, My Abdelouahed Sabri, Ali Yahyaouy, Abdellah AarabRecognizing gestures in American Sign Language (ASL) from video data presents significant challenges due to the intricate combination of hand gestures, facial cues, and body motion. In this work, we introduce a hybrid deep learning framework that integrates Convolutional Neural Networks (CNNs) for extracting spatial characteristics with Long Short-Term Memory (LSTM) networks for capturing temporal sequences. The model was trained … …Journal of Computer Science, Vol. 21, Issue 12 · 23 Jan 2026 · 2,056 accessesView PDFCite
Research ArticleOpen accessIn the abstractAdvancements In Precision Agriculture: A Review on Image-Based Stress Detection and Predictive Yield Loss ModelingA. Josephine, A. SubhashiniPrecision agriculture utilizes cutting-edge technologies to maximize the management of crops, enhance utilization of resources, and maximize yield forecasting. This study critically analyzes 53 peer-reviewed articles to evaluate advancements in image-based stress detection and yield prediction techniques for precision agriculture. The review enumerates main issues, such as image-based analysis methods, different crop stress aspects (biotic, environmental, and abiotic), and remote … …Journal of Computer Science, Vol. 21, Issue 11 · 28 Dec 2025 · 2,520 accessesView PDFCite