Tag: feature extraction

An Enhancement over Texture Feature Based Multiclass Image Classification Under Unknown Noise

In this paper we deal with classification of multiclass images using statistical texture features with two approaches. One with statistical texture feature extraction of the whole image, another with feature extraction of image blocks. This paper presents an experimental assessment of classifier in terms of classification accuracy under different constraints

Classification of Human Emotion from Deap Eeg Signal Using Hybrid Improved Neural Networks with Cuckoo Search

Emotions are very important in human decision handling, interaction and cognitive process. In this paper describes that recognize the human emotions from DEAP EEG dataset with different kind of methods. Audio – video based stimuli is used to extract the emotions. EEG signal is divided into different bands using discrete wavelet transformation with

Automatic Anthropometric System Development Using Machine Learning

The contactless automatic anthropometric system is proposed for the reconstruction of the 3D-model of the human body using the conventional smartphone. Our approach involves three main steps. The first step is the extraction of 12 anthropological features. Then we determine the most important features. Finally, we employ these features to