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292 articles for “deep learning”
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Research ArticleOpen accessIn the abstractAutism Detection from 2D Transformed EEG Signal using Convolutional Neural NetworkZahrul Jannat Peya, M. A. H. Akhand, Jannatul Ferdous Srabonee, Nazmul SiddiqueAutism Spectrum Disorder (ASD) is a neurodevelopmental disorder relating to speech complications, nonverbal and social communication, and repetitive behaviors. There is no remedy for ASD but early diagnosis, mediation, and supportive care can aid the development of language, conduct, and communication skills. As the cause of ASD is a neurodevelopmental disorder, its diagnosis based on brain function analyzing different brain … …Journal of Computer Science, Vol. 18, Issue 8 · 31 Jul 2022 · 7,927 accessesView PDFCite
Research ArticleOpen accessIn the abstractAnalyzing Effect on Residual Learning by Gradual Narrowing Fully-Connected Layer Width and Implementing Inception Block in Convolution LayerSaurabh SharmaResearch conducted on the advancement of CNN architecture for computer vision problems focuses on strategically choosing and modifying convolution hyperparameters (kernel, pooling, etc.). However, these research works don't exploit the advantage of employing multi fully-connected layers post the core schema to avail further performance improvements, which have been identified as the first research gap. Studies were also conducted to address … …Journal of Computer Science, Vol. 18, Issue 5 · 24 May 2022 · 6,051 accessesView PDFCite
Research ArticleOpen accessIn the abstractImprovement of Moroccan Dialect Sentiment Analysis Using Arabic BERT-Based ModelsGhizlane Bourahouat, Manar Abourezq, Najima DaoudiThis study addresses the crucial task of sentiment analysis in natural language processing, with a particular focus on Arabic, especially dialectal Arabic, which has been relatively understudied due to inherent challenges. Our approach centers on sentiment analysis in Moroccan Arabic, leveraging BERT models that are pre-trained in the Arabic language, namely AraBERT, QARIB, ALBERT, AraELECTRA, and CAMeLBERT. These models are … …Journal of Computer Science, Vol. 20, Issue 2 · 27 Dec 2023 · 6,549 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Hybrid Metaheuristic Algorithm for Diseases Classification Using UAV ImagesYagnasree Sirivella, Anuj JainRecent advances in technology are very astounding since they have made it possible to manage and monitor systems remotely. Traditional farming is undergoing a transition towards "smart farming" with the assistance of technological breakthroughs, which include the implementation of intelligent irrigation systems and the remote monitoring of the development of crops. In particular, the Unmanned Aerial Vehicle plays a significant … …Journal of Computer Science, Vol. 19, Issue 10 · 11 Sep 2023 · 5,253 accessesView PDFCite
Research ArticleOpen accessIn the abstractFace Verification for Person Re-Identification from Surveillance Camera and Drone-based VideosVimala Mathew, K. Ramesh, Tom Toby, Anu Mary ChackoPerson re-identification in surveillance camera videos is attracting widespread interest due to its increasing number of applications. It is being applied in the field of security, healthcare, product manufacturing, product sales and more. Though there are a variety of methods to do person re-identification, face verification-based methods are very much effective. In this study, a deep learning framework to perform … …Journal of Computer Science, Vol. 17, Issue 7 · 28 Jul 2021 · 7,322 accessesView PDFCite
Research ArticleOpen accessIn the abstractStock price prediction using Generative Adversarial NetworksHungChun Lin, Chen Chen, GaoFeng Huang, Amir JafariDeep learning is an exciting topic. It has been utilized in many areas owing to its strong potential. For example, it has been widely used in the financial area which is vital to the society, such as high-frequency trading, portfolio optimization, fraud detection and risk management. Stock market prediction is one of the most popular and valuable areas in finance. … …Journal of Computer Science, Vol. 17, Issue 3 · 2 Apr 2021 · 17,714 accessesView PDFCite
Research ArticleOpen accessIn the abstractImproved Model Predictive Control System Design and Implementation for Unmanned Ground VehiclesSai Charan Dekkata, Sun Yi, MA Muktadir et al.Autonomous ground robots autonomously are being used inthe places where it is very hazardous for human beings to reach and operate,such as nuclear power plants and chemical industries. The aim of the researchpresented here is to develop a control system that enables such ground robotsnavigate autonomously with various sensors as the depth camera, 2D scanninglaser, 3D Lidar, GPS, and IMU. … …Journal of Mechatronics and Robotics, Vol. 6, Issue 1 · 27 Oct 2022 · 6,004 accessesView PDFCite
Research ArticleOpen accessIn the abstractGrasshopper Optimization Algorithm-Generative Adversarial Network for Lung Cancer Detection and ClassificationSukruth Gowda, A JayachandranLung cancer is one of the most dangerous deadly diseases for individuals worldwide. Thus, the survival rate is low due to the difficulty in detecting lung cancer at advanced stages like symptoms; thus, prominence for early diagnosis is important. The detection and treatment of lung cancer is having great importance for early diagnosis. The existing Convolution Neural Network (CNN) based … …Journal of Computer Science, Vol. 18, Issue 3 · 9 Apr 2022 · 6,579 accessesView PDFCite
Research ArticleOpen accessIn the abstractImage Pre-Processing Techniques to Improve DBT Classification Accuracy With CNN ResNet-50Qodri Aziz, Slamet Riyadi et al.Digital Breast Tomosynthesis (DBT) is a three-dimensional imaging technology that is meant to determine breast cancer more accurately than regular mammograms. But low contrast and noise can make DBT images less clear, which can make deep learning-based classification less accurate. This study seeks to assess the impact of diverse preprocessing techniques on breast cancer classification outcomes utilizing the ResNet-50 Convolutional … …Journal of Computer Science, Vol. 22, Issue 10 · 21 Oct 2026 · 419 accessesView PDFCite
Research ArticleOpen accessIn the abstractOptimization of Non-Technical Electricity Loss Detection Using Artificial Neural Networks: Case of Cameroon Distribution NetworkLekini Nkodo Claude Bernard, Bell Serge Samuel, Nyemb Nsoga Valjacques et al.Non-Technical Losses (NTL) represent a critical challenge for power utilities, particularly in developing countries. This paper proposes an unsupervised deep learning approach based on an autoencoder to detect abnormal electricity consumption patterns in the Cameroonian distribution network. The model learns normal customer behavior using historical consumption data and identifies anomalies through reconstruction error analysis. Statistical thresholds are applied to classify … …American Journal of Engineering and Applied Sciences, Vol. 19, Issue 1 · 23 Jul 2026 · 1,233 accessesView PDFCite