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35 articles for “Residual Network”
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Research ArticleOpen accessPhrase in the titleTowards an Explainable Approach: Hybrid Residual Network and SVM for Automated Brain Tumor Detection and ClassificationKamini Lamba, Shalli RaniThe abnormal growth of brain cells leads to tumor formation, which can be fatal if not detected and treated promptly. Given the complexity of brain tumors, early detection is critical in healthcare. Traditional radiology-based tumor detection is prone to human error and delays. Hence, a computer- assisted method is needed for accurate and efficient diagnosis. With the rapid advancements in … …Journal of Computer Science, Vol. 22, Issue 1 · 11 Feb 2026 · 1,427 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleCrop Disease Detection via an Improved Residual NetworkGuolin Chen, Weifeng Liu, Xinyu Zou, Xiaoxia LiDeep learning has shown substantial potential across many domains, and crop disease detection is no exception. This study investigates the application of deep learning to crop disease detection, systematically evaluating the performance of convolutional neural networks of different depths. Building on the classical ResNet-50 as the base model, we introduce a Squeeze-and-Excitation (SE) attention mechanism to enhance feature extraction. The … …American Journal of Biochemistry and Biotechnology, Vol. 22, Issue 2 · 31 Jul 2026 · 898 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleRobust Adversarial Attack Detection via Generative Adversarial Network With Residual Multi-Layer Aggregation Based Contrastive Loss FunctionAmudha Gopalakrishnan, Nalini JosephAdversarial attacks in medical imaging refer to subtle modifications to images that mislead diagnostic systems, resulting in inaccurate diagnoses and assessments. These attacks exploit vulnerabilities in image processing, leading to misclassification or altered visual features that often go unnoticed. This raises serious concerns about the security and reliability of medical diagnosis, directly impacting clinical decision-making and patient safety. This research … …Journal of Computer Science, Vol. 22, Issue 1 · 10 Feb 2026 · 1,742 accessesView PDFCite
Research ArticleOpen accessIn the keywordsRIA-ViT: A Residual Inception Atrous Vision Transformer for Detection of Gallbladder Cancer from CT ImagesAbhishek Sehrawat, Anita Gupta, Vishnupriya, Varun P. GopiGallbladder Cancer (GBC) is a rare but highly aggressive malignancy of the biliary system. In early-stage gallbladder cancer, there are neither overt symptoms nor specific signs. In most patients, it is diagnosed late, resulting in poor outcomes. Even when imaging is available, diagnosing GBC remains difficult because its features overlap with those of non-neoplastic gallbladder pathologies. Furthermore, the overlap between … …Journal of Computer Science, Vol. 22, Issue 10 · 6 Oct 2026 · 413 accessesView PDFCite
Research ArticleOpen accessIn the keywordsAutism 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 · 7,921 accessesView PDFCite
Research ArticleOpen accessIn the keywordsAnalyzing 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 · 6,044 accessesView PDFCite
Research ArticleOpen accessIn the keywordsLink Stability and Node Energy Conscious Local Route-Repair Scheme for Mobile Ad Hoc NetworksAnuradha Banerjee, Paramartha DuttaProblem statement: A mobile ad hoc network is a self-configuring network of mobile nodes connected by wireless links. As the nodes are free to move randomly, topology of the network may change rapidly and unpredictably. As a result, intermediate nodes in the communication routes tend to lose connection with each other during the communication process. In order to repair a … …American Journal of Applied Sciences, Vol. 7, Issue 8 · 31 Aug 2010 · 6,856 accessesView PDFCite
Research ArticleOpen accessIn the keywordsIoT-Integrated CNN Deep Learning for Automated Breast Cancer Detection and DiagnosisYamini Kalva, R. Ganesh Babu, Sindhu V. et al.Breast cancer continues to be a primary cause of death in women, requiring prompt and accurate diagnosis to enhance treatment results. Traditional diagnostic techniques depend on manual assessment, which leads to possible misclassification, significant inter-observer variability, and delays in decision-making. Current deep learning models, including CNNs, frequently experience feature loss, gradient declining and restricted adaptability to real-time data. To overcome … …Journal of Computer Science, Vol. 22, Issue 4 · 30 Mar 2026 · 1,753 accessesView PDFCite
Research ArticleOpen accessIn the abstractDual-Branch Shape Texture Learning With Pyramid Residual and Sobel Edge Layers for Rice Variety ClassificationM Pradeep, M SiddappaAutomated rice variety classification categorizes rice types based on features, such as grain texture, shape, color, and size. Traditional handcrafted feature-based models fail at rice classification due to lighting variations, background noise, and environmental conditions, leading to overlapping visual characteristics and frequent misclassification. To address these challenges, this research proposes a novel Dual-Branch Convolutional Neural Network with Pyramid Residual Units … …Journal of Computer Science, Vol. 22, Issue 9 · 24 Sep 2026 · 627 accessesView PDFCite
Research ArticleOpen accessIn the abstractDynamic Weighting Technique Based Arctic Puffin Optimization for Energy Efficient Data Transmission in Wireless Sensor NetworksM. Bharathraj Kumar, S. Avinash, Prakash G. Gani, Prathapchandra ShettyWireless Sensor Networks (WSNs) are designed using various sensor nodes, which are employed for communication in diverse applications that include healthcare, industrial areas, and smart cities. Specifically, WSNs demand energy-efficient clustering and routing mechanisms that assist in extending network lifetime due to the limited battery capacity of sensor nodes. However, many existing meta-heuristic-based approaches incorporate fixed objective weights that struggle … …Journal of Computer Science, Vol. 22, Issue 9 · 10 Sep 2026 · 767 accessesView PDFCite