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176 results for “Image Classification”
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Research ArticleOpen accessIn the abstractObject Detection and Classification from Thermal Images Using Region based Convolutional Neural NetworkUsha Mittal, Sonal Srivastava, Priyanka ChawlaIn recent years, object detection and classification has gained so much popularity in different application areas like face detection, self- driving cars, pedestrian detection, security surveillance systems etc. The traditional detection methods like background subtraction, Gaussian Mixture Model (GMM), Support Vector Machine (SVM) have certain drawbacks like overlapping of objects, distortion due to smoke, fog, lightening conditions etc. In this … …Journal of Computer Science, Vol. 15, Issue 7 · 18 Jul 2019 · 9,454 accessesView PDFCite
Research ArticleOpen accessIn the abstractRefining Chest X-ray Interpretation with Deep Transfer Learning TechniquesR. Sriramkumar, K. Selvakumar, J. JeganChest X-rays are essential diagnostic tools for thoracic diseases, but different doctors' interpretations can differ greatly, which frequently results in inconsistent diagnoses. By using deep transfer learning techniques, this study seeks to improve the accuracy of Chest X-ray interpretations. More accurate and effective analysis can be accomplished with the growing potential of artificial intelligence (AI) in medical imaging, especially through … …Journal of Computer Science, Vol. 21, Issue 10 · 27 Nov 2025 · 2,655 accessesView PDFCite
Research ArticleOpen accessIn the abstractAnomaly Detection Based on Vision Transformer Model and Texture FeaturesMohammed Lahraichi, Abdelhafid Berroukham, Khalid HousniAnomaly detection is one of the video surveillance applications,which aims to detect and analyze abnormal behaviors and risky situations inorder to prevent accidents. Various deep learning models have beenpreviously developed for this purpose, such as CNN, RNN, and VisionTransformer, each one has its strengths and weaknesses based on the qualityof input data. This paper proposes a novel approach based on … …Journal of Computer Science, Vol. 21, Issue 7 · 10 Jul 2025 · 3,689 accessesView PDFCite
Research ArticleOpen accessIn the abstractEmpirical Study on Modified Pre-Trained CNN Architectures for Fitzpatrick17k Skin Diseases Prediction ModellingSteven Matthew, Nur Afny Catur Andryani, Rojali et al.Preventing missed diagnosis of skin diseases is critical for enhancing patient outcomes. Technology support empowered by AI based algorithms have been recently developed to minimize the burden. Convolutional Neural Networks (CNNs) are increasingly utilized for image classification tasks including skin's diseases prediction modelling. Its advancement architectures such as pre-trained models, VGG16 andResNet50 provide a strong foundation to up-skill the prediction … …Journal of Computer Science, Vol. 21, Issue 7 · 8 Jul 2025 · 3,938 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Deep Convolutional Neural Wavelet Network for Classification of Medical ImagesRamzi Ben Ali, Ridha Ejbali, Mourad ZaiedThis work present a new solution for medical image classification using the Neural Network (NN) and Wavelet Network (WN) based on the Fast Wavelet Transform (FWT) and the Adaboost algorithm. This method is divided in two stages: The learning stage and the classification stage. The first consists to extract the features using the FWT based on the MultiResolution Analysis (MRA). … …Journal of Computer Science, Vol. 14, Issue 11 · 11 Nov 2018 · 7,627 accessesView PDFCite
Research ArticleOpen accessIn the abstractPerformance Analysis of LDA, AdaBoost and Ensemble Bag Classifiers for Automatically Recognizing Nine Common Facial ExpressionsM.D. Sumithra, M. Abdul RahimanFacial expression recognition holds a prominent role in today’s digital world with more Human –Computer Interaction happening in day to day life. Successful identification of facial expressions needs extraction of descriptive attributes from the active facial patches and accurate classification. This paper is presented with the comparison of three multi class classifiers namely Linear Discriminant Analysis, AdaBoost and Ensemble bag. … …Journal of Computer Science, Vol. 14, Issue 9 · 27 Sep 2018 · 7,791 accessesView PDFCite
Research ArticleOpen accessIn the abstractA CNN-KNN Based Recognition of Online Handwritten Symbols within Physics Expressions Using Contour-Based Bounding Box (CBBS) Segmentation TechniqueUjwala Kolte, Sachin Naik, Vidya KumbharArtieres, T., Marukatat, S., & Gallinari, P. (2007). Online Handwritten Shape Recognition Using Segmental Hidden Markov Models. IEEE Transactions on Pattern Analysis and Machine Intelligence, 29(2), 205–217. https://doi.org/10.1109/tpami.2007.38 Baró, A., Riba, P., Calvo-Zaragoza, J., & Fornés, A. (2019). From Optical Music Recognition to Handwritten Music Recognition: A baseline. Pattern Recognition Letters, 123, 1–8. https://doi.org/10.1016/j.patrec.2019.02.029 Bresler, M., Prua, D., & Hlavác, … …Journal of Computer Science, Vol. 20, Issue 7 · 7 May 2024 · 6,282 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhancing Pedestrian Detection Using Context InformationJorge Candido, Mauricio MarengoniDetecting pedestrians among other objects in a digital image is a relevant task in the field of computer vision. This paper presents a method to improve the performance of a pedestrian detection algorithm using context information. A neural network is used to classify the region below pedestrian candidates as being floor or non-floor. We assume that a pedestrian must be … …Journal of Computer Science, Vol. 14, Issue 7 · 6 Aug 2018 · 7,224 accessesView PDFCite
Research ArticleOpen accessIn the abstractImage Binarization Using Block Boundary Pixels MeanO. Imocha Singh, T. Romen SinghInput image pixels classification into two intensities like black and white as foreground and background respectively refers to image binarization. Binarization with a local threshold value is termed as adaptive image binarization. Locally adaptive thresholding techniques are local pixels dependent process. Local environment dependent process is normally time consuming one and hence its computational time complexity is also local region … …Journal of Computer Science, Vol. 13, Issue 11 · 28 Nov 2017 · 7,816 accessesView PDFCite
Research ArticleOpen accessIn the abstractDetermination of SVM-RBF Kernel Space Parameter to Optimize Accuracy Value of Indonesian Batik Images ClassificationAvinanta Tarigan, Dewi Agushinta, Adang Suhendra, Fikri BudimanImage retrieval using Support Vector Machine (SVM) classification verydepends on kernel function and parameter. Kernel function used by dot productsubstitution from old dimension feature to new dimension depends on imagedataset condition. In this research, parameter of Gaussian /Radial BasisFunction (RBF) kernel function is optimized using multi class non-linear SVMmethod and implemented to training and test datasets of traditional Indonesian batik … …Journal of Computer Science, Vol. 13, Issue 11 · 23 Oct 2017 · 7,535 accessesView PDFCite