Thermo vision are used in military, police custom traffic control, industrial and other specific applications for collecting and processing thermo visual information from infrared images. There is a problem in the steps of implementation of the developed methods and algorithms for infrared image processing in real time practical applications of thermo vision systems. Here is proposed to exploit...

abstract-manual harvesting of saffron as a laborious and exhausting job; it not only raises production costs, but also reduces the quality due to contaminations. saffron quality could be enhanced if automated harvesting is substituted. as the main step towards designing a saffron harvester robot, an appropriate algorithm was developed in this study based on image processing techniques to recogn...

Today, increasing attention is being paid to research into spike-based neural computation both to gain a better understanding of the brain and to explore biologically-inspired computation. Within this field, the primate visual pathway and its hierarchical organization have been extensively studied. Spiking Neural Networks (SNNs), inspired by the understanding of observed biological structure an...

In this study, a method based on using image processing and artificial neural network is introduced to determine pelt color and curl size of newborn lambs in Zandi sheep. The data was collected from 300 newborn lambs reared in the Zandi sheep breeding centre of Khojir, Tehran. Primarily, curl size and pelt color of new born lambs was recorded by experienced appraisers, and at the same time, sev...

The estimation of metallurgical parameters of flotation process from froth visual features is the ultimate goal of a machine vision based control system. In this study, a batch flotation system was operated under different process conditions and metallurgical parameters and froth image data were determined simultaneously. Algorithms have been developed for measuring textural and physical froth ...

The following is a proposal for separating cursive characters into separate and distinctive characters for recognition. The proposed method begins with thresholding of gray level image into binarised image using iterative thresholding selection method. The binary image is then slant corrected. Using Neuroheuristic technique, the slant corrected word is over segmented and artificial neural netwo...

The last decade has witnessed an exponential growth of visual information and an unprecedentedly broad range of applications of image and video. To efficiently access, utilize, and transmit visual information, visual representation and analysis have attracted intensive attention and become one of the most active research topics in the fields of signal processing, computer vision, and artificial...

In this paper, we propose to train binarized convolutional neural networks (CNNs) that are of significant importance for deploying deep learning mobile devices with limited power capacity and computing resources. Previous works on quantizing CNNs often seek approximate the floating-point information weights and/or activations using a set discrete values. Such methods, termed value approximation...

We investigate supervised learning in neural networks. We consider a multi-layered feed-forward network with back propagation. We find that the network of small-world connectivity reduces the learning error and learning time when compared to the networks of regular or random connectivity. Our study has potential applications in the domain of data-mining, image processing, speech recognition, an...