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135 results for “early detection”

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Research ArticleOpen accessEvery word in the titleRadial Basis Function Networks and Contrast-Limited Adaptive Histogram Equalization Filter Based Early-Stage Breast Cancer Detection TechniquesAnitha Ponraj, Aroul CanessaneBreast cancer is one of the most common types of cancer that kills women. When cells become uncontrollably large, cancer develops. As a result, detecting and classifying breast cancer in its early stages is essential so that patients can take the appropriate precautions. On the other hand, mammography images have relatively low sensitivity and effectiveness in detecting breast cancer. Furthermore, … …Journal of Computer Science, Vol. 19, Issue 6 · 25 May 2023 · 5,613 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleDetection of Antibodies Against Bovine Herpes Virus 1, Bovine Viral Diarrhea Virus and Bovine Respiratory Syncytial Virus in Early and Ultra-Early Weaned Beef CalvesDiego Daniel Gonzalez, Juan Sebastian Vittone, Martin Lado et al.Bovine respiratory disease is the leading cause of morbidity and mortality in weaned calves. In Argentina, two weaning practices have been implemented. In the early weaning, the calf is removed from the cow at 60-70 days of age while in ultra-early weaning the calf is weaned at 30-45 days of age. The purposes of both systems is to improve cow … …American Journal of Animal and Veterinary Sciences, Vol. 8, Issue 4 · 29 Oct 2013 · 8,384 accessesView PDFCite
Research ArticleOpen accessIn the keywordsClassification of Thoracic X-Ray Images of COVID-19 Patients Using the Convolutional Neutral Network (CNN) MethodRamacos Fardela, Dian Milvita, Mawanda Almuhayar et al.Recently, radiology modalities have been widely used to detect COVID-19. Thoracic X-rays and CT scans are the primary radiological tools utilized in the diagnosis and treatment of individuals with COVID-19. In addition, chest CT scans are more accurate and sensitive in early COVID-19 identification. A new problem arises in diagnosing the results of CT scan images of COVID-19 by radiologists … …Journal of Computer Science, Vol. 20, Issue 4 · 1 Feb 2024 · 5,753 accessesView PDFCite
Review ArticleOpen accessIn the keywordsAdvances in Forest Fire Detection, Prediction and Behavior: A Comprehensive SurveyAhmad Alkhatib, Khalid JaberForest fires are a major environmental challenge that poses a threat to both human life and ecological health. To effectively prevent and manage forest fires, it is crucial to have reliable detection, prediction and behavior analysis systems in place. This study provides a comprehensive survey of the different approaches and techniques used for forest fire detection, prediction and behavior analysis. … …Journal of Computer Science, Vol. 20, Issue 4 · 7 Feb 2024 · 6,419 accessesView PDFCite
Research ArticleOpen accessIn the keywordsCongestion Free Routing in Adhoc NetworksT. Senthil Kumaran, V. SankaranarayananProblem statement: A Mobile Ad-Hoc Network (MANET) is a temporary network; the mobile devices in an ad-hoc network are communicating through wireless links without any pre-existing infrastructure. The one major problem of this network is network congestion, it may take place at any intermediate nodes when data packets are traveling from source to destination. The major problems of congestion or … …Journal of Computer Science, Vol. 8, Issue 6 · 4 Apr 2012 · 7,236 accessesView PDFCite
Research ArticleOpen accessIn the abstractRIA-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 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 PDFCite
Research ArticleOpen accessIn the abstractHybrid CNN-Based Transformer Pipeline With Radiomic Fusion for Multi-Class Lung Cancer DetectionAanchal Vij, Kuldeep Singh Kaswan, Anand NayyarEarly detection of lung cancer remains challenging due to high intra-class variation and inter-class similarity in Computed Tomography (CT) images. In this paper, we propose a hybrid deep learning model that combines convolutional, attention-based, and transformer-guided representations to address these challenges in multi-class lung cancer classification. For deep feature extraction, we use the EfficientNetV2-S architecture augmented with a Convolutional Block … …Journal of Computer Science, Vol. 22, Issue 6 · 3 Jun 2026 · 1,528 accessesView PDFCite
Research ArticleOpen accessIn the abstractImplementation and Performance Evaluation of YOLOv8 for Wheat Fungal Disease DetectionShivani Sood, Shallu Duggal, Monika Sethi et al.Among the many difficulties in producing wheat, a vital food source for the world, there are biotic variables like fungal diseases, which drastically lower crop output. Around the world, biotrophic fungi particularly, leaf rust, powdery mildew, and yellow rusts-have become a constant threat to wheat production. Traditional methods of identification and mitigation are labor-intensive, slow, and imprecise, limiting therefore early … …Journal of Computer Science, Vol. 22, Issue 4 · 2 May 2026 · 1,599 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Intelligent Hybrid Machine Learning Model for Paddy Disease DetectionS. Hrushikesava Raju, S. Adinarayna, U. Sesadri et al.Most countries rely on paddy/rice as a preferred staple crop due to its desirable agronomic characteristics. However, during the growth cycle, undetected or delayed identification of diseases can significantly reduce crop yield. To address this, machine learning approaches are increasingly employed for early-stage disease detection. Traditional Recurrent Neural Networks (RNNs), while useful for sequential data, suffer from limitations such as … …Journal of Computer Science, Vol. 22, Issue 4 · 29 Apr 2026 · 1,747 accessesView PDFCite