the quality evaluation of agricultural products is one of the key factors in promoting their quality. in this study, a method based on combined image processing technique and artificial neural network was presented. separation of touching almonds under different positions is a very important step in design of grading devices. in this study, an image processing algorithm based on extracting crit...

With the novel and fast advances in the area of deep neural networks, several challenging image-based tasks have been recently approached by researchers in pattern recognition and computer vision. In this paper, we address one of these tasks, which is to match image content with natural language descriptions, sometimes referred as multimodal content retrieval. Such a task is particularly challe...

Over the past few years, neural networks have re-emerged as powerful machine-learning models, yielding state-of-the-art results in fields such as image recognition and speech processing. More recently, neural network models started to be applied also to textual natural language signals, again with very promising results. This tutorial surveys neural network models from the perspective of natura...

The science of image processing helps to recognize the human gesture for general life applications. Human gestures can be identified by observing the different movements of eyes, mouth, nose and hands. The face is a rich source of information about human behavior. The proposed method of facial expression recognition system is based on PCA and Neural Networks, to recognize the facial expression ...

Particularly in the fields of object identification and picture recognition, deep learning approaches have transformed science computer vision. This abstract provides a summary recent developments cutting-edge methods for applications like recognition. The automated classification objects or patterns inside digital photographs is known as image Convolutional neural networks (CNNs), example, dis...

Object recognition has been the focus of much research in the photogrammetric and image processing communities. The goal of this research is often the quantitative three-dimensional measurement of objects found in two-dimensional image space. Although a multitude of different approaches to the automation of this problem have been developed and thoroughly tested, few could claim that the process...

BACKGROUND Automated cell recognition from histologic images is a very complex task. Traditionally, the image is segmented by some methods chosen to suit the image type, the objects are measured, and then a classifier is used to determine cell type from the object's measurements. Different classifiers have been used with reasonable success, including neural networks working with data from morph...

This paper considers a convolutional neural network transformation that reduces computation complexity and thus speedups neural network processing. Usage of convolutional neural networks (CNN) is the standard approach to image recognition despite the fact they can be too computationally demanding, for example for recognition on mobile platforms or in embedded systems. In this paper we propose C...

This work presents a new Algorithm to recognize separate voices of some Arabic words, the digits form zero to ten. Firstly we prepare our signal by pre-processing trial. Next the speech signal is processed as an image by Power Spectrum Estimation. For feature extraction, transformation and hence recognition, the algorithm of minimal eigenvalues of Toeplitz matrices together with other methods o...