54 articles for “Long Short-Term Memory”

Research ArticleOpen accessIn the keywordsAutomated Medical Image Captioning with Soft Attention-Based LSTM Model Utilizing YOLOv4 AlgorithmPaspula Ravinder, Saravanan SrinivasanThe medical image captioning field is one of theprominent fields nowadays. The interpretation and captioning of medical imagescan be a time-consuming and costly process, often requiring expert support. Thegrowing volume of medical images makes it challenging for radiologists tohandle their workload alone. However, addressing the issues of high cost andtime can be achieved by automating the process of medical image … …Journal of Computer Science, Vol. 20, Issue 1 · 16 Dec 2023 · 6,651 accessesView PDF Cite

Research ArticleOpen accessIn the keywordsForecasting of Multistep Multivariate Financial Data Through GSO Algorithm Infused Vanilla LSTM ModelNikhitha Pai, Ilango Velchamy, Nithya B RameshPredicting time series in the financial domain requires using models that can do sequence processing tasks. One such model is the LSTM model which belongs to the family of deep learning networks. The performance measure of LSTM in a regression task is to bring down the error in the predicted values. In this study, a novel fused LSTM model integrating … …Journal of Computer Science, Vol. 19, Issue 7 · 10 Jul 2023 · 6,074 accessesView PDF Cite

Research ArticleOpen accessIn the abstractA Scalable Hybrid CNN-LSTM and SDN Based Architecture for Real-Time DDoS Defence in IoT and Cloud NetworksSujit Sutradhar, Joy Lal Sarkar, Rajesh Kumar VermaDistributed Denial-of-Service (DDoS) is one of the most significant threats to the security of IoT, cloud, and Software-Defined Network (SDN) environments because it can aggravate network unavailability and disrupt the continuity of services. This study presents a hybrid CNN-LSTM-based DDoS detection and mitigation system for real-time DDoS detection in the context of heterogeneous network environments, which is integrated with SDN … …Journal of Computer Science, Vol. 22, Issue 10 · 19 Oct 2026 · 508 accessesView PDF Cite

Research ArticleOpen accessIn the abstractBrain Tumor Segmentation and Classification Using HardNet Transformer With Gated Recurrent Unit ModelSaida D, Srinivas Adepu, Thade Lakshmi Devi et al.The uncontrolled growth of brain tumor cells presents a severe health risk, making early diagnosis and accurate classification essential for improving treatment outcomes. However, the existing approaches used for segmentation fail to delineate the tumor regions accurately due to a lack of global contextual information of brain tumors, resulting in poor classification performance. To overcome this limitation, this research proposes … …Journal of Computer Science, Vol. 22, Issue 9 · 26 Sep 2026 · 630 accessesView PDF Cite

Research ArticleOpen accessIn the abstractA Data Mining Driven Framework for Image-Based Crop Stress Analysis Using IPCA, FP-Growth, ConvLSTM, and Sequential ModelsA. Josephine, A. SubhashiniDetecting crop stress before it becomes serious has a major impact on the food supply. It helps in avoiding the loss of crops, increases productivity and helps farmers to practice precision farming. Most technologies today are designed specifically to either detect crop stress or to predict how well the crop will grow. Many of the technologies do not combine the … …Journal of Computer Science, Vol. 22, Issue 8 · 21 Aug 2026 · 922 accessesView PDF Cite

Research ArticleOpen accessIn the abstractEnhancing DevOps Pipelines With Viral Spread Optimization and Hybrid Deep LearningDileepkumar S R, Juby MathewModern software teams rely on Continuous Integration and Continuous Deployment (CI/CD) pipelines to automate testing and delivery. However, these pipelines often waste resources by running unnecessary tests and failing to predict which builds will fail. This study presents a new framework that addresses three key challenges: (1) deciding which tests to run first, (2) predicting which builds will fail, and … …Journal of Computer Science, Vol. 22, Issue 6 · 3 Jul 2026 · 935 accessesView PDF Cite

Research ArticleOpen accessIn the abstractHybrid BiGRU-BiLSTM Model for Real-Time ECG Arrhythmia Detection Using Wearable SensorsPrem Narayan Singh, Rajendra Prasad MahapatraAccurate and real-time detection of cardiac arrhythmias is essential for timely medical intervention. Advances in wearable devices and deep learning have made it feasible to continuously monitor electrocardiogram (ECG) signals, facilitating early identification of abnormal heart rhythms. For arrhythmia detection, this study presents a hybrid deep learning architecture combining Bidirectional Gated Recurrent Units (Bi-GRU) and Bidirectional Long Short-Term Memory (Bi-LSTM). … …Journal of Computer Science, Vol. 22, Issue 5 · 5 Jun 2026 · 1,331 accessesView PDF Cite

Research ArticleOpen accessIn the abstractAddressing Emergency Communication Challenges: Deep Learning Solutions for the Speech and Hearing- ImpairedPoornima B V, Srinath S et al.Emergency communication plays a very important role in ensuring that help reaches people promptly and safely in case of any emergency. However, the biggest problem faced by those who cannot speak and hear properly is to convey their message clearly and understand others. In this regard, the proposed research work focuses on recognizing emergency gestures made in the Indian Sign … …Journal of Computer Science, Vol. 22, Issue 5 · 1 Jun 2026 · 1,063 accessesView PDF Cite

Research ArticleOpen accessIn the abstractDeep Learning Models for Predicting Stock Closing Prices in the Saudi Stock MarketAreej Alhumaidi, Hoda A. AbdelhafezFinancial time series data are inherently volatile and nonlinear, presenting considerable challenges in accurately forecasting stock market trends. This study aims to predict the closing prices of companies listed on the Saudi stock market by analyzing historical data spanning from 2013 to 2023. To this end, four deep learning models were employed-Long Short-Term Memory (LSTM), Bidirectional LSTM (Bi-LSTM), Gated Recurrent … …Journal of Computer Science, Vol. 22, Issue 4 · 22 Apr 2026 · 1,355 accessesView PDF Cite

Research ArticleOpen accessIn the abstractAn Intelligent System for Cardiovascular Disease Prediction Using Deep LearningDeepika Arora, Deepak Dudeja, B K AgrawalHeart disease remains among the major causes of death in the world. Hence, accurate and reliable prediction schemes are key. To detect the presence of diseases in early stages, data mining and deep learning algorithms offer powerful tools to determine important trends in large and complex data. To enhance the prediction of cardiac diseases, this paper proposes a hybrid deep … …Journal of Computer Science, Vol. 22, Issue 2 · 9 Mar 2026 · 1,607 accessesView PDF Cite