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Krahasoni metodat

Shqyrtoni metodat e zgjedhura krah për krah; rreshtat që ndryshojnë janë të theksuar.

Klasifikimi i imazheve me CNN×Makineria e Vektorëve Mbështetës (Klasifikimi)×
FushaMësimi i thellëMësimi i makinës
FamiljaMachine learningMachine learning
Viti i origjinës20161995
KrijuesiHe, K. et al. (ResNet); Tan, M. & Le, Q.V. (EfficientNet)Cortes, C. & Vapnik, V.
LlojiDeep convolutional neural network (supervised)Maximum-margin classifier (kernel method)
Burimi themeluesHe, K., Zhang, X., Ren, S. & Sun, J. (2016). Deep Residual Learning for Image Recognition. CVPR. DOI ↗Cortes, C. & Vapnik, V. (1995). Support-Vector Networks. Machine Learning, 20, 273–297. DOI ↗
Emërtime të tjeraCNN — Görüntü Sınıflandırma (ResNet / VGG / EfficientNet), convolutional neural network image classifier, deep image classification, ResNet / VGG / EfficientNetDestek Vektör Makinesi (SVM — Sınıflandırma), support-vector network, SVM classifier, maximum-margin classifier
Të lidhura55
PërmbledhjaCNN image classification uses deep convolutional architectures such as ResNet (He et al., 2016), VGG and EfficientNet (Tan & Le, 2019) to sort images into categories. Stacked convolutional layers learn a hierarchy of visual features directly from pixels, and skip (residual) connections prevent the vanishing-gradient problem in very deep networks.The Support Vector Machine, introduced by Corinna Cortes and Vladimir Vapnik in 1995, is a classifier that finds the optimal separating hyperplane between classes in a high-dimensional space. It chooses the boundary that leaves the widest possible margin to the nearest training points, which makes its decisions robust on new data.
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ScholarGateKrahasoni metodat: CNN Image Classification · Support Vector Machine. Marrë më 2026-06-15 nga https://scholargate.app/sq/compare