This work uses convolutional neural network (CNN) classification and K-Means clustering methods. This research used two ways to improve the accuracy of the system. The KMeans method identifies emotions based on heart rate and skin conductance, while the CNN method identifies ...
With the aim of developing an approach for machines to produce their own languages, it is aimed to distinguish the sounds of living things by classifying them and to generate new sounds by using convolutional deep neural network (CNN) method. In the study, the applied alpha...
In this study, deep features were extracted from skin lesion images to diagnose whether skin cancer is malignant or not, using cubic-type Support Vector Machine (SVM) classifier and pre-trained Convolutional Neural Network (CNN) based AlexNet and ResNet50 deep architectures, ...
This research aims to develop a keratitis identification model using the convolutional neural network (CNN) method and training data consisting of images produced by smartphones and combined with slitlamp images. The training accuracy of the developed model is 92% with a dropout...