Fingerprint identification and verification are one of the well established methods for implementing security aspects. This technique has become mature due to lots of research in this area. One more feature of artificial intelligence is clubbed with image processing for fingerprint that is artificial neural network. ANN is used at different levels in fingerprint recognition. In this paper we wi...

Vehicle license plate recognition is one of the techniques that can be used for the identification of vehicles. It is useful to be applied to many applications such as entrance admission, security, parking control, airport or harbour cargo control, road traffic control, speed control and so on. In this paper, we present an approach of recognising vehicle license plate using the Fuzzy ARTMAP neu...

Face recognition is one of the most important image processing research topics which is widely used in personal identification, verification and security applications. In this paper, a face recognition system, based on the principal component analysis (PCA) and the feedforward neural network is developed. The system consists of two phases which are the PCA preprocessing phase, and the neural ne...

Artificial Neural Network (ANN) can be used to simulate the human nervous cells in the processing system. The advantage of ANN is constantly training to gain the accurate results. Structure Similarity (SSIM) expresses the quality of the images comprehensively by the image brightness, contrast, and structure. This research combines the Artificial Neural Network perceptrons and Structure Similari...

The main focus of this thesis is to develop biologically-based computationalmodels for object recognition. A series of models for attention and objectrecognition were developed in order of increasing functionality and complex-ity. These models are based on information processing in the primate brain,and especially inspired from the theory that visual information processingoc...

Abstract Scientific and methodological foundations of identification, recognition, classification micro-objects using redundant information structures - morphometric, histological, fractal characteristics images have been developed. Mechanisms for extracting statistical, dynamic, specific rarefaction are proposed. Dynamic models developed, combined with the capabilities neural networks. Computa...

Convolutional neural networks are a technology that combines artificial neural networks and recent deep learning methods. They have been applied to many image recognition tasks and have attracted the attention of the researchers of many countries in recent years. This paper summarizes the latest development of convolutional neural networks and expounds the relative research of image recognition...

Recognition of visual patterns is one of significant applications of Artificial Neural Networks, which partially emulate human thinking in the domain of artificial intelligence. In the paper, a simplified neural approach to recognition of visual patterns is portrayed and discussed. This paper is dedicated for investigators in visual patterns recognition, Artificial Neural Networking and related...

Invariant visual object recognition and the underlying neural representations are fundamental to higher-level human cognition. To understand these neural underpinnings, we combine human and monkey psychophysics, large-scale neurophysiology, neural perturbation methods, and computational modeling to construct falsifiable, predictive models that aim to fully account for the neural encoding and de...