مقایسهٔ روش‌ها

	شبکه عصبی کانولوشنی (طبقه‌بندی)	ماشین بردار پشتیبان (طبقه‌بندی)
حوزه	یادگیری عمیق	یادگیری ماشین
خانواده	Machine learning	Machine learning
سال پیدایش	1998	1995
پدیدآور	LeCun, Y. et al.	Cortes, C. & Vapnik, V.
نوع	Deep neural network (convolutional)	Maximum-margin classifier (kernel method)
منبع بنیادین	LeCun, Y., Bottou, L., Bengio, Y. & Haffner, P. (1998). Gradient-Based Learning Applied to Document Recognition. Proceedings of the IEEE, 86(11), 2278–2324.	Cortes, C. & Vapnik, V. (1995). Support-Vector Networks. Machine Learning, 20, 273–297.
نام‌های دیگر	CNN (Evrişimli Sinir Ağı — Sınıflandırma), CNN classification, ConvNet, convolutional network classifier	Destek Vektör Makinesi (SVM — Sınıflandırma), support-vector network, SVM classifier, maximum-margin classifier
مرتبط	5	5
خلاصه	A Convolutional Neural Network (CNN) is a deep learning model, established by LeCun and colleagues in 1998, that learns local patterns directly from images and structured data to classify them. Stacks of convolutional filters discover increasingly abstract features, so manual feature engineering can be largely reduced.	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.