قارن الطرق

	الشبكة العصبية التلافيفية (التصنيف)	آلة المتجهات الداعمة (التصنيف)
المجال	التعلم العميق	تعلم الآلة
العائلة	Machine learning	Machine learning
سنة النشأة	1998	1995
صاحب الطريقة	LeCun, Y. et al.	Cortes, C. & Vapnik, V.
النوع	Deep neural network (convolutional)	Maximum-margin classifier (kernel method)
المصدر التأسيسي	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.
الأسماء البديلة	CNN (Evrişimli Sinir Ağı — Sınıflandırma), CNN classification, ConvNet, convolutional network classifier	Destek Vektör Makinesi (SVM — Sınıflandırma), support-vector network, SVM classifier, maximum-margin classifier
ذات صلة	5	5
الملخص	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.