Search results for "vision."
showing 10 items of 4900 documents
Distinguishing Onion Leaves from Weed Leaves Based on Segmentation of Color Images and a BP Neural Network
2006
A new algorithm to distinguish onion leaves from weed leaves in images is suggested. This algorithm is based on segmentation of color images and on BP neural network. It includes: discarding soil for conserving only plants in the image, color image segmentation, merging small regions by analyzing the frontier rates and the averages of color indices of the regions, at last a BP neural network is used to determine if the small regions belongs to onion leaf or not. The algorithm has been applied to many images and the correct identifiable percents for onion leaves are between 80%~ 90%.
Connectionist models of face processing: A survey
1994
Abstract Connectionist models of face recognition, identification, and categorization have appeared recently in several disciplines, including psychology, computer science, and engineering. We present a review of these models with the goal of complementing a recent survey by Samal and Iyengar [Pattern Recognition25, 65–77 (1992)] of nonconnectionist approaches to the problem of the automatic face recognition. We concentrate on models that use linear autoassociative networks, nonlinear autoassociative (or compression) and/or heteroassociative backpropagation networks. One advantage of these models over some nonconnectionist approaches is that analyzable features emerge naturally from image-b…
Logo detection in images using HOG and SIFT
2017
In this paper we present a study of logo detection in images from a media agency. We compare two most widely used methods — HOG and SIFT on a challenging dataset of images arising from a printed press and news portals. Despite common opinion that SIFT method is superior, our results show that HOG method performs significantly better on our dataset. We augment the HOG method with image resizing and rotation to improve its performance even more. We found out that by using such approach it is possible to obtain good results with increased recall and reasonably decreased precision.
Regularized RBF Networks for Hyperspectral Data Classification
2004
In this paper, we analyze several regularized types of Radial Basis Function (RBF) Networks for crop classification using hyperspectral images. We compare the regularized RBF neural network with Support Vector Machines (SVM) using the RBF kernel, and AdaBoost Regularized (ABR) algorithm using RBF bases, in terms of accuracy and robustness. Several scenarios of increasing input space dimensionality are tested for six images containing six crop classes. Also, regularization, sparseness, and knowledge extraction are paid attention.
Challenges of automatic processing of large amount of skin lesion multispectral data
2020
This work will describe the challenges involved in setting up automatic processing for a large differentiated data set. In this study, a multispectral (skin diffuse reflection images using 526nm (green), 663nm (red), and 964nm (infrared) illumination and autofluorescence (AF) image using 405 nm excitation) data set with 756 lesions (3024 images) was processed. Previously, using MATLAB software, finding markers, correctly segmenting images with dark edges and image alignment were the main causes of the problems in automatic data processing. To improve automatic processing and eliminate the use of licensed software, the latter was substituted with the open source Python environment. For more …
A Feed-Forward Neural Network for Robust Segmentation of Color Images
1999
A novel approach for segmentation of color images is proposed. The approach is based on a feed-forward neural network that learns to recognize the hue range of meaningful objects. Experimental results showed that the proposed method is effective and robust even in presence of changing environmental conditions. The described technique has been tested in the framework of the Robot Soccer World Cup Initiative (RoboCup). The approach is fully general and it may be successfully employed in any intermediate level image-processing task, where the color is a meaningful descriptor.
A Neural Architecture for 3D Segmentation
2003
An original neural scheme for segmentation of range data is presented, which is part of a more general 3D vision system for robotic applications. The entire process relies on a neural architecture aimed to perform first order image irradiance analysis, that is local estimation of magnitude and orientation of the image irradiance gradient.
Aspects of cell production in mantle tissue of Ciona intestinalis L. (Tunicata, Ascidiacea)
2005
Renewal of cell population is needed in the tunic of ascidians, as the tunic cells are involved in many biological functions. Tunic cells are thought to arrive by migrating across the mantle epithelium into the tunic from the blood lacunae or the mesenchymal space. Electron microscope observations show that the mantle epithelium of Ciona intestinalis shares some proliferative characteristics, releasing cells into the tunic and thus providing an increase renewal of tunical cells in restricted zones of adult animals.
Le copropriétaire de parts sociales a le droit de participer aux décisions collectives, malgré la présence d'un mandataire unique de l'indivision
2014
International audience; Note sous Cour de cassation (com.), 21 janvier 2014, n° 13-10.151 (F-P+B), M. et Mme Truptil c/ Société Earl de Fauque
Management options for reducing vision-related asthenopic complaints
2022
Diplomdarbs uzrakstīts angļu valodā uz 23 lappusēm. Tajā ir 8 attēli, 4 tabulas un 17 atsauces. Īpaši ar Covid-19 tiek uzlabota elektronisko ierīču lietošana īpaši skolas vecuma bērniem, kuri ar e-mācībām daudzas stundas dienā pavadīja, izmantojot datorus, lai pētītu, palielinot jau tuvredzības laikā esošo astenopisko simptomu nopietnību. Izmantojot +0,50D atkarību skolas vecuma bērniem (8-16 g.v.) ar ezoforiju tuvredzības stāvoklī 45 dienas, mēs varam ievērojami samazināt šo simptomu skaitu, kā arī varam pamanīt foorijas samazināšanos. Izmantojot šo metodi, pacientam var būt ērta redze tuvumā un uzlabota veiktspēja datora lietošanas un studiju laikā.