54 articles for “Long Short-Term Memory”

Research ArticleOpen accessIn the keywordsEmploying Hybrid Serial Cascaded Adaptive Network for Anomaly Detection and Prevention in IoT Time Series Data With Optimal Interdomain RoutingKante Satyanarayana, K. VenkateshNowadays, emerging Internet of Things (IoT) in data processing becomes interested research topic and is used for various applications. This varies from big data processing and analytics for accumulating entire sensor data to detect and generate long-term trends. Nevertheless, this results in the requirement for resources like the execution of power, memory, and bandwidth, in which resource-constrained IoT tools suffers … …Journal of Computer Science, Vol. 22, Issue 1 · 21 Feb 2026 · 1,466 accessesView PDF Cite

Research ArticleOpen accessIn the keywordsA Dynamic Lifelong Learning Network for Real-Time Stock Prediction With Reinforcement TuningTalent Mawere, Selvaraj Rajalakshmi, Venu Madhav Kuthadi, Otlhapile DinakanyaneCompanies and investors require accurate market forecasting to make more informed decisions. Traditional methods for predicting stock market performance have become less useful considering the dynamic and volatile nature that characterizes stock markets today. In this paper, we propose an innovative Dynamic Lifelong Learning Network for stock market prediction. The model incorporates a hybrid convolutional long short-term memory with an … …Journal of Computer Science, Vol. 22, Issue 2 · 20 Feb 2026 · 1,822 accessesView PDF Cite

Research ArticleOpen accessIn the keywordsDeep 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 PDF Cite

Research ArticleOpen accessIn the keywordsA Deep Learning Approach for Telugu Domain Identification with Multichannel LSTM-CNNBuddha Hari Kumar, Chitra Perumal, Inakoti Ramesh Raja et al.The vast growth of textual data has ushered into the limelight, a plethora of applications in information retrieval and natural language processing (NLP). Proper extraction of information from text is heavily dependent on recognizing the thematic content, which becomes crucial in the tasks of document summarization, information extraction, question answering, machine translation, and sentiment analysis. The great complexity of this … …Journal of Computer Science, Vol. 21, Issue 9 · 26 Nov 2025 · 2,395 accessesView PDF Cite

Research ArticleOpen accessIn the keywordsA 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 PDF Cite

Research ArticleOpen accessIn the keywordsOnline Handwritten Physics Expression Recognition Using a CRNN-LSTM ApproachUjwala Pritam Kolte, Sachin Arun NaikOptical Character Recognition (OCR) is crucial for identifying and extracting information from scientific documents. However, recognizing online handwritten physics expressions remains a relatively unexplored area of research. In the existing literature, most of the researchers worked on CNN classification to identify mathematical expressions. The traditional Convolution Neural Network (CNN) has limitations for extracting sequential data. This study proposes a CRNN … …Journal of Computer Science, Vol. 21, Issue 2 · 31 Dec 2024 · 4,812 accessesView PDF Cite

Research ArticleOpen accessIn the keywordsProtein Secondary Structure Prediction using Hybrid Recurrent Neural NetworksRomana Rahman Ema, Akhi Khatun, Md. Alam Hossain et al.The most important and challenging problem in bioinformatics is protein secondary structure prediction. The molecules of all protein organisms have three-dimensional (primary, secondary, 3-D) structures which are completely recognized by the sequence of amino acids. Protein secondary structure attributes to the polypeptide backbone of the local configuration of proteins. Most generally, the second-level prediction is indicated such as: If there … …Journal of Computer Science, Vol. 18, Issue 7 · 14 Jul 2022 · 7,332 accessesView PDF Cite

Research ArticleOpen accessIn the keywordsMachine Learning and Deep Learning for Phishing Email Classification using One-Hot EncodingSikha Bagui, Debarghya Nandi, Subhash Bagui, Robert Jamie WhiteRepresentation of text is a significant task in Natural Language Processing (NLP) and in recent years Deep Learning (DL) and Machine Learning (ML) have been widely used in various NLP tasks like topic classification, sentiment analysis and language translation. Until very recently, little work has been devoted to semantic analysis in phishing detection or phishing email detection. The novelty of … …Journal of Computer Science, Vol. 17, Issue 7 · 23 Jul 2021 · 10,936 accessesView PDF Cite

Research ArticleOpen accessIn the keywordsPerformance Evaluation of Deep Learning Networks on Printed Odia CharactersSanjibani Sudha Pattanayak, Sateesh Kumar Pradhan, Ramesh Chandra MalikDeep machine learning includes a series of layers to mimic the working of the human brain for taking a decision. Deep learning networks have shown good results in character recognition in the past. This paper evaluates the performance of different deep learning networks like Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM) based recurrent neural network and Convolutional LSTM on … …Journal of Computer Science, Vol. 16, Issue 7 · 25 Jul 2020 · 6,785 accessesView PDF Cite

Research ArticleOpen accessIn the keywordsAspect Category Detection Using Bi-LSTM-Based Deep Learning for Sentiment Analysis for HindiAshwani Gupta, Utpal SharmaIn the field of sentiment analysis, the notion of aspect category identification lays emphasis on identifying the aspect categories in a specific review phrase. The purpose of this research is to propose a novel approach to the identification of aspect categories in reviews that are published in Hindi. The training and evaluation of a supervised model that is based on … …Journal of Computer Science, Vol. 20, Issue 11 · 18 Sep 2024 · 4,606 accessesView PDF Cite