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Keyword: Features extractionA Word Spotting Method for Arabic Manuscripts Based on Speeded Up Robust Features Technique
The diversity of manuscripts according to their contents, forms, organizations and presentations provides a data-rich structures. The aim is to disseminate this cultural heritage in the images format to the general public via digital libraries. However, handwriting is an obstacle to text recognition algorithms in images, especially cursive writing of Arabic calligraphy. Most current search…
Read MoreDomain Independent Feature Extraction using Rule Based Approach
Sentiment analysis is one of the most popular information extraction tasks both from business and research prospective. From the standpoint of research, sentiment analysis relies on the methods developed for natural language processing and information extraction. One of the key aspects of it is the opinion word lexicon. Product’s feature from online reviews is an…
Read MoreTransfer and Ensemble Learning in Real-time Accurate Age and Age-group Estimation
Aging is considered to be a complex process in almost every species’ life, which can be studied at a variety of levels of abstraction as well as in different organs. Not surprisingly, biometric characteristics from facial images play a significant role in predicting human’s age. Specifically, automatic age estimation in real-time situation has begun to…
Read MoreSH-CNN: Shearlet Convolutional Neural Network for Gender Classification
Gender detection and age estimation become an active research area and a very important field today, wish has been widely used in various applications including them: biometrics, social network, Targeted advertising, access control, human-computer interaction, electronic customer, etc. The need to further improve the recognition or classification rate keeps increasing day after day. In this…
Read MoreInvestment of Classic Deep CNNs and SVM for Classifying Remote Sensing Images
Feature extraction is an important process in image classification for achieving an efficient accuracy for the classification learning models. One of these methods is using the convolution neural networks. The use of the trained classic deep convolution neural networks as features extraction gives a considerable results in the remote sensing images classification models. So, this…
Read MoreMachine Learning framework for image classification
Hereby in this paper, we are going to refer image classification. The main issue in image classification is features extraction and image vector representation. We expose the Bag of Features method used to find image representation. Class prediction accuracy of varying classifiers algorithms is measured on Caltech 101 images. For feature extraction functions we evaluate…
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