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Research ArticleOpen accessIn the keywordsAdaptive Resonance Theory 1 (ART1) Neural Network Based Horizontal and Vertical Classification of 0-9 Digits RecognitionMbaitiga ZacharieThis study describes the Adaptive Resonance Theory 1 (ART1), an efficient algorithm that emulates the self-organizing pattern recognition and hypothesis testing properties of the ART neural network architecture for horizontal and vertical classification of 0-9 digits recognition. In our approach the ART1 model can self-organize in real time producing stable and clear recognition while getting input patterns beyond those originally … …Journal of Computer Science, Vol. 3, Issue 11 · 30 Nov 2007 · 7,346 accessesView PDFCite
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 · 3,682 accessesView PDFCite
Research ArticleOpen accessIn the abstractConvolution Neural Networks of Dynamically Sized Filters with Modified Stochastic Gradient Descent Optimizer for Sound ClassificationManu Pratap Singh, Pratibha RashmiDeep Neural Networks (DNNs), specifically Convolution Neural Networks (CNNs) are found well suited to address the problem of sound classification due to their ability to capture the pattern of time and frequency domain. Mostly the convolutional neural networks are trained and tested with time-frequency patches of sound samples in the form of 2D pattern vectors. Generally, existing pre-trained convolutional neural … …Journal of Computer Science, Vol. 20, Issue 1 · 13 Dec 2023 · 5,781 accessesView PDFCite
Research ArticleOpen accessIn the abstractCascade-Based Non-Linear Feedforward Neural Networks for Bi-Directional MemoryThipendra Pal Singh, Tanupriya Choudhury, Rohini AIn today's world, efficient computation is the key to success in many fields. Pattern association plays an influential role in many areas of life, such as learning and memory. In complex dynamics, bidirectional associative memory has been effectively demonstrated by neural networks. However, these neural networks face challenges in terms of performance, such as computational time. A random bipolar input … …Journal of Computer Science, Vol. 19, Issue 4 · 28 Feb 2023 · 5,640 accessesView PDFCite
Research ArticleOpen accessIn the abstractBlockchain-Enabled Decisive Red Fox Optimizer-Based Feature Selection With Deep Learning-Based Intrusion Detection SystemC. Ananth, S. Sathiyarani, N. MohananthiniRecently, Intrusion Detection Systems (IDS) using Deep Learning (DL) models become useful in accomplishing network security. The selected features serve as input to the DL model, which is trained on labelled datasets to learn intrinsic patterns distinguishing malicious from normal network behaviour. DL techniques like Convolutional Neural Networks (CNN) are usually utilized. The seamless combination of Public Blockchain (BC) technology … …Journal of Computer Science, Vol. 21, Issue 12 · 20 Jan 2026 · 1,714 accessesView PDFCite
Research ArticleOpen accessIn the abstractLT-LBP-Based Spatial Texture Feature Extraction with Deep Learning for X-Ray ImagesPankaja Lakshmi P., Sivagami M.The novel logarithmic transformation of Local Binary Pattern (LT-LBP) for texture feature extraction is used with Deep Learning (DL) models. The Computational complexity in the DL models asymptotically increases with the data sesssst and the depth of the layers in Convolutional Neural Networks (CNN). Pre-processing the images before training the DL model holds a strong impact on the operation speed … …Journal of Computer Science, Vol. 20, Issue 1 · 18 Dec 2023 · 7,190 accessesView PDFCite
Research ArticleOpen accessIn the abstractLocal Binary Pattern for the Evaluation of Surface Quality of Dissimilar Friction Stir Welded Ultrafine Grained 1050 and 6061-T6 Aluminium AlloysAkshansh Mishra, Rajat SarawagiFriction Stir Welding process is an advanced solid-state joining process which finds application in various industries like automobiles, manufacturing, aerospace and railway firms. Input parameters like tool rotational speed, welding speed, axial force and tilt angle govern the quality of Friction Stir Welded joint. Improper selection of these parameters further leads to fabrication of the joint of bad quality resulting … …Journal of Mechatronics and Robotics, Vol. 4, Issue 1 · 27 Jul 2020 · 6,228 accessesView PDFCite
Research ArticleOpen accessIn the abstractSymbolic Aggregate approXimation-Local Binary Pattern Feature Descriptor Combination for Automatic Facial Expression RecognitionSumithra M.D., M. Abdul RahimanAutomatic identification of facial expression is a significant research area which is anticipated for real time processing in Human-Computer Interaction domain. Along with an efficient classifier for assigning the class label to each of the input face image, it is very necessary to have a strong feature vector for training the classifier. This paper proposes an effectual combination of Local … …Journal of Computer Science, Vol. 15, Issue 1 · 8 Jan 2019 · 7,513 accessesView PDFCite
Research ArticleOpen accessIn the abstractExplainability Aware Heterogeneous Temporal Graph Transformer for Automated Genetic Disorder Detection from Genomic DataPuvaneswari Subramaniapillai, Indirani Govindasamy, Revathy GurumurthyGenetic disorders affect millions worldwide, posing major challenges for accurate diagnosis and effective treatments. New developments in genomic technologies, especially Next-Generation Sequencing (NGS), have enhanced the classification of genetic modification and improved diagnostic abilities. Moreover, the Machine Learning (ML) and Deep Learning (DL) methods emerged as efficient tools for evaluating the intricate genomic data and determining the patterns, which can … …Journal of Computer Science, Vol. 22, Issue 11 · 14 Oct 2026 · 566 accessesView PDFCite
Research ArticleOpen accessIn the abstractSenior Expertise and Peer Consensus: A Comparative Analysis of AI and Clinician Measurements in Multi-Curve Scoliosis AssessmentFrank Ibañez Elijorde, Joselito F. Villaruz, Ma Beth S. Concepcion, Mylo N. SoriasoGiven the scarcity in the literature, this study explored the use of AI for multi-curve scoliosis assessment. Its performance was analyzed through comparison against a group of clinicians composed of one senior and five non-senior orthopedic surgeons. The analysis focused on Cobb angle measurement and identification of vertebral endplates across three curve regions, namely Main Thoracic (MT), Proximal Thoracic (PT), … …Journal of Computer Science, Vol. 22, Issue 3 · 9 Mar 2026 · 1,390 accessesView PDFCite