… In this work, it has been made image classification process using deep learning that often …
as image processing, signal processing, natural language processing and speech recognition …

… data projection and has been used widely in pattern recognition, signal processing, image
processing, and data analysis. Points in an -dimensional input space are projected into an …

… to the forefront of a neural network renaissance that has seen rapid … image classification
tasks, we cover their development, from their predecessors up to recent state-of-the-art deep …

… Furthermore, we use Convolutional Neural Networks in the proposed method. In this study,
the image classification process is performed by using like a LeNet network model. The caffe …

… A modified deep convolutional neural network is proposed in this work for MR brain image
classification. The proposed approach is analyzed in terms of accuracy and computational …

… The convolution neural network model trained by the deep learning algorithm … of deep
learning and convolution neural network, and summarizes the basic model structure, convolution …

… , we utilize deep learning and present Convolutional Neural Network (CNN) approaches. In
this study, … and three-dimensional convolution model approaches that can present efficient …

… to apply neural networks in gender classification, one was … with a large number of image
processing modules, the average … hybrid approach proposed in [10] processed the face image …

… Since artificial neural networks have shown a performance … scene classification, specially
convolutional neural networks (CNN)[4] [5] [6], this work focuses on identifying the best network …

… In the application of deep neural network, when we are faced with a large amount of data, it
… and optimize the parameters after building the deep neural network model. If a model that …