Letter identification and the Neural Image Classifier
نویسندگان
چکیده
منابع مشابه
Letter identification and the neural image classifier.
Letter identification is an important visual task for both practical and theoretical reasons. To extend and test existing models, we have reviewed published data for contrast sensitivity for letter identification as a function of size and have also collected new data. Contrast sensitivity increases rapidly from the acuity limit but slows and asymptotes at a symbol size of about 1 degree. We rec...
متن کاملIdentification of selected monogeneans using image processing, artificial neural network and K-nearest neighbor
Abstract Over the last two decades, improvements in developing computational tools made significant contributions to the classification of biological specimens` images to their correspondence species. These days, identification of biological species is much easier for taxonomist and even non-taxonomists due to the development of automated computer techniques and systems. In this study, we d...
متن کاملAutomated Sewer Inspection Using Image Processing and a Neural Classifier
The focus of the research presented here is on the automated assessment of sewer pipe conditions using a laserbased sensor. The proposed method involves image and data processing algorithms categorising signals acquired from the internal pipe surface. Fault identification is carried out using a neural network. Experimental results are presented.
متن کاملTexture Feature Neural Classifier for Remote Sensing Image Retrieval Systems
Texture information is useful for image data browsing and retrieval. The goal of this paper is to present a texture classification system for remote sensing images addressed to the administration of great collections of those images. The proposed classifier is a hybrid system composed by an unsupervised neural network and a supervised one. Starting from a small portion of the image (pattern) th...
متن کاملClassifier ensembles for image identification using multi-objective Pareto features
In this paper we propose classifier ensembles that use multiple Pareto image features for invariant image identification. Different from traditional ensembles that focus on enhancing diversity by generating diverse base classifiers, the proposed method takes advantage of the diversity inherent in the Pareto features extracted using a multi-objective evolutionary Trace Transform algorithm. Two v...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Vision
سال: 2015
ISSN: 1534-7362
DOI: 10.1167/15.2.15