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156 results for “Feature Detection”

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Research ArticleOpen accessIn the abstractA Novel Approach for Diagnosing Diabetic Retinopathy in Fundus ImagesE. Dhiravidachelvi, V. RajamaniIn recent years the medical profession has seen an ever increasing demand for diagnosis and a permanent cure for illnesses caused by climatic-changes, unwholesome food and environmental pollution. Also the appearances of hitherto unknown viral diseases have caused eye diseases, which have prompted surgeons to monitor the health of the eyes. Potential new therapies that may help in preserving sight … …Journal of Computer Science, Vol. 11, Issue 1 · 21 Aug 2014 · 6,520 accessesView PDFCite
Research ArticleOpen accessIn the abstractSPLINE ACTIVATED NEURAL NETWORK FOR CLASSIFYING CARDIAC ARRHYTHMIAY. S. Kumaraswamy, R. Ganesh KumarElectro Cardiogram’s (ECG) biomedical signals characterizing cardiac anomalies are used for identifying cardiac arrhythmia. Irregular heartbeat-Arrhythmia-affects heart rate causing problems. Many methods, trying to simplify arrhythmia monitoring through automated detection, were developed over the years. ECG classification for arrhythmia is investigated in this paper based on soft computing techniques. RR interval are extracted from time series of the ECG and … …Journal of Computer Science, Vol. 10, Issue 8 · 9 Apr 2014 · 6,968 accessesView PDFCite
Research ArticleOpen accessIn the abstractPERFORMANCE ANALYSIS OF BRAIN TUMOR DIAGNOSIS BASED ON SOFT COMPUTING TECHNIQUESP. Shantha Kumar, P. Ganesh KumarComputed tomography images are widely used in the diagnosis of brain tumor because of its faster processing, avoiding malfunctions and suitability with physician and radiologist. This study proposes a new approach to automated detection of brain tumor. This proposed work consists of various stages in their diagnosis processing such as preprocessing, anisotropic diffusion, feature extraction and classification. The local binary … …American Journal of Applied Sciences, Vol. 11, Issue 2 · 27 Dec 2013 · 6,985 accessesView PDFCite
Research ArticleOpen accessIn the abstractMammogram Analysis Based on Pixel Intensity Mean FeaturesR. Nithya, B. SanthiProblem statement: In the recent years, Computer Aided Diagnosis (CAD) can be very useful for detection of breast cancer. Mammography can be used as an efficient tool for breast cancer diagnosis. A computer based diagnosis and classification system can reduce unnecessary biopsy. Approach: This study investigates a new approach to the classification of mammogram images based on pixel intensity mean … …Journal of Computer Science, Vol. 8, Issue 3 · 7 Jan 2012 · 7,666 accessesView PDFCite
Research ArticleOpen accessIn the abstractAdaptive Neuro-Fuzzy Inference System Approach for the Automatic Screening of Diabetic Retinopathy in Fundus ImagesS. Kavitha, K. DuraiswamyProblem statement: Diabetic retinopathy is one of the most significant factors contributing to blindness and so early diagnosis and timely treatment is particularly important to prevent visual loss. Approach: An integrated approach for extraction of blood vessels and exudates detection was proposed to screen diabetic retinopathy. An automated classifier was developed based on Adaptive Neuro-Fuzzy Inference System (ANFIS) to differentiate … …Journal of Computer Science, Vol. 7, Issue 7 · 28 Jun 2011 · 6,785 accessesView PDFCite
Research ArticleOpen accessIn the abstractDWT to Classify Automatically the Placental Tissues Development: Neural Network ApproachMohammad Ayache, Mohamad Khalil, Francois TranquartProblem statement: This study proposed an approach for classification of placental tissues development using ultrasound images. Approach: This approach was based to the selection of tissues, feature extraction by discrete wavelet transform and classification by neural network and especially the Multi Layer Perceptron (MLP). Results: The proposed approach was tested for ultrasound placental images; resulting in 95% success rate. Conclusion/Recommendations: … …Journal of Computer Science, Vol. 6, Issue 6 · 30 Jun 2010 · 6,997 accessesView PDFCite
Research ArticleOpen accessIn the abstractMultimodal Face and Ear ImagesA.A. Darwish, R. Abd Elghafar, A. Fawzi AliProblem statement: The study presented in this study to combined face and ear algorithms as an application of human identification. Biometric system to the detection and identification of human faces and ears developed a multimodal biometric system using eigenfaces and eigenears. Approach: The proposed system used the extracted face and ear images to develop the respective feature spaces via the … …Journal of Computer Science, Vol. 5, Issue 5 · 30 May 2009 · 7,225 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordDeep Learning Approaches for Early Detection of Skin Cancer Disease Detection Using Segmentation and Classification with Severity AnalysisPunam R. Patil, Ritu TandonThe utmost prevalent type of the disease, skin cancer claims millions of lives every year, poses a serious public health threat particularly melanoma, which is often fatal if not detected early. Early diagnosis is crucial, yet traditional methods frequently fall short due to image quality limitations and the complexity of visual differentiation. With an emphasis on severity analysis, this study … …Journal of Computer Science, Vol. 21, Issue 9 · 24 Nov 2025 · 2,051 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordFeature Extraction of Sit-to-Stand Transition Using Vision-Based Pose EstimationAchmad Rizal, Bayu Erfianto, Sugondo Hadiyoso, IstiqomahSit-to-Stand Transition (STS) and vice versa are important indicators of independence and physical health. For normal people, this movement is easy to do but can be difficult for people who have health problems, such as those who have had an injury or stroke. Sit-to-stand assessments can be used to detect spinal disorders. However, spinal kinematic measurements require special instrumentation and … …Journal of Computer Science, Vol. 21, Issue 3 · 21 Feb 2025 · 6,204 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordResearch on Cotton Top Bud Target Detection Algorithm Based on Improved RetinaNetJikui Zhu, Shijie Lin, Fengkui Zhang et al.To solve the problems of low accuracy and high miss rate in the recognition of cotton apical buds during mechanical topping, an enhanced method based on the RetinaNet network is proposed for the accurate identification of cotton apical buds under natural light. The traditional RetinaNet algorithm is validated to improve the recall rate and average accuracy of cotton apical bud … …American Journal of Biochemistry and Biotechnology, Vol. 20, Issue 1 · 17 Apr 2024 · 5,128 accessesView PDFCite