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53 results for “Hybrid Architecture”
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Research ArticleOpen accessIn the abstractRoute Optimization using Hybrid GRU Learning Model for SDN and Edge-Based VANET TopologySavitha Kumar, Chandrasekar ChinnasamyIntelligent Transportation System (ITS) offersoutstanding features, including security applications and emergency alerts.Unfortunately, ITS limits traffic control services, adaptability, andadjustability due to the traffic volume. Hence, expanding the standard VehicularAd hoc Networks (VANET) framework is a requirement. As a result, in the latestdays, the concept of Software-Defined Networking based Vehicular Ad hocNetworks (SDN-VANETs) has drawn considerable attention, creating VANETssmarter. The SDN-VANETs … …Journal of Computer Science, Vol. 18, Issue 8 · 26 Aug 2022 · 6,160 accessesView PDFCite
Research ArticleOpen accessIn the abstractAdvanced Facial Emotion Recognition Using DCNN-ELM: A Comprehensive Approach to Preprocessing, Feature Extraction and Performance EvaluationBoopalan K., Satyajee Srivastava, K. Kavitha et al.As a subfield of affective computing, Facial Emotion Recognition (FER) teaches computers to read people's facial expressions to determine their emotional state. Because facial expressions convey 55% of an individual's emotional and mental state in the whole range of face-to-face communication, Facial Emotion Recognition is crucial for connecting humans and computers. Improvements in the way computer systems (robotic systems) interact … …Journal of Computer Science, Vol. 21, Issue 1 · 30 Nov 2024 · 5,899 accessesView PDFCite
Review ArticleOpen accessIn the abstractA Survey of Methods for Managing the Classification and Solution of Data Imbalance ProblemKhan Md. Hasib, Md. Sadiq Iqbal, Faisal Muhammad Shah et al.The problem of class imbalance is extensive for focusing on numerous applications in the real world. In such a situation, nearly all of the examples are labeled as one class called majority class, while far fewer examples are labeled as the other class usually, the more important class is called minority. Over the last few years, several types of research … …Journal of Computer Science, Vol. 16, Issue 11 · 13 Nov 2020 · 10,120 accessesView PDFCite
EditorialOpen accessIn the abstractVolume 2: and SGAMR Goes!Chiara Bedon, Mario D’Aniello, Flavio StochinoThe year 2018 starts with a great confirmation for SGAMR! The journal has been selected to host the extended version of some selected papers presented during the 6th International Workshop on Design in Civil and Environmental Engineering (DCEE2017), held at the University of Cagliari (Italy) during November 2017. A summary of selected papers from highly ranked, international scientists can be … …International Journal of Structural Glass and Advanced Materials Research, Vol. 4, Issue 1 · 28 Aug 2020 · 5,737 accessesView PDFCite
Review ArticleOpen accessIn the abstractEvaluating Common Reconnaissance Tools and Techniques for Information GatheringIsaac Odun-Ayo, Emmanuel Owoka, Otavie Okuoyo et al.A reconnaissance attack is a commonly overlooked step in penetration testing but a critical step that could help increase the effectiveness of an attack on a target. However, it is a common attack faced by companies and institutions, among others. It enables the attacker or penetration tester to gain valuable information on the target and select the best tools and … …Journal of Computer Science, Vol. 18, Issue 2 · 16 Mar 2022 · 7,805 accessesView PDFCite
Research ArticleOpen accessIn the abstractDiagnosing Alzheimer’s Disease using Convolution Neural NetworksSarita, Saurabh Mukherjee, Tanupriya Choudhury et al.Alzheimer’s is a disease wherein constant degeneration of neurons and their synapses result in impaired brain functioning which leads to personality changes, memory loss, thinking and speech disorder. So, there is a requirement of an automated and early diagnosis of this disease to decrease the death rate. The proposed work is coupled with deep learning techniques to predict the Alzheimer’s … …Journal of Computer Science, Vol. 18, Issue 2 · 21 Feb 2022 · 7,344 accessesView PDFCite
Review ArticleOpen accessIn the abstractA Systematic Review of Artificial Intelligence and Deep Learning Approaches for Cocoa Pod Disease DetectionHenry Techie-Menson, Michael Asante, Yaw Marfo Missah et al.Cocoa pod diseases destroy an estimated 700,000 metric tons of cocoa annually, threatening 40–50 million smallholder farmers across tropical regions. Accurate field diagnosis remains constrained by symptom similarity, labour-intensive scouting, and limited specialist access in remote communities. This paper presents a PRISMA-guided systematic review of 25 peer-reviewed studies on automated cocoa pod disease detection and classification (2016–2026), addressing architectural approaches, … …Journal of Computer Science, Vol. 22, Issue 8 · 8 Sep 2026 · 733 accessesView PDFCite
Research ArticleOpen accessIn the abstractUzNER: A Human-Reviewed Benchmark for Uzbek Named Entity Recognition With Gazetteer-Augmented Transformer ModelsBobur Saidov, Vladimir Barakhnin et al.UzNER-100K is a large-scale human-reviewed benchmark for Uzbek named entity recognition with 100,000 training sentences, 18 fine-grained entity types and 200,083 entity mentions across 114,269 sentences in total. The corpus was constructed through an LLM-assisted, expert-reviewed annotation pipeline that achieved strong reliability on the main audit subset while substantially reducing corpus-construction effort. The benchmark includes a standard test split, a … …Journal of Computer Science, Vol. 22, Issue 6 · 22 Jun 2026 · 1,308 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Comprehensive Review of Medical Image Denoising: Techniques, Challenges, Applications and Future DirectionsMohit Sharma, Ayush Dogra, Anita Gupta et al.The concept of noise reduction in medical images plays a vital role in improving image quality and accuracy associated with diagnosis, and facilitating reliable automated analysis. This survey presents a structured overview of medical image denoising, beginning with foundational definitions and noise models for modalities such as MRI and CT. We critically evaluate persistent gaps, including the limited generalizability of … …Journal of Computer Science, Vol. 22, Issue 3 · 28 Mar 2026 · 1,849 accessesView PDFCite
Research ArticleOpen accessIn the abstractSystematic Literature Review of Graph Neural Networks in Disaster Management: Methods, Applications, and Future DirectionsSularno, Wendi Boy, Putri Anggraini et al.The increasing frequency and complexity of natural disasters underscore the urgent need for intelligent systems that support timely and effective decision-making. Graph Neural Networks (GNNs) have emerged as a powerful deep-learning paradigm for modeling spatial and relational data, offering distinct advantages for disaster management. This study presents a Systematic Literature Review (SLR) of GNN-based approaches for disaster mitigation, emergency response, … …Journal of Computer Science, Vol. 22, Issue 2 · 17 Feb 2026 · 2,036 accessesView PDFCite