به نام خدا
Title: Handwritten Text Segmentation using Average Longest Path Algorithm
Authors: Dhaval Salvi, Jun Zhou, Jarrell Waggoner, and Song Wang
Abstract: Offline handwritten text recognition is a very challenging problem. Aside from the large variation of different hand-writing styles, neighboring characters within a word are usually connected, and we may need to segment a word into individual characters for accurate character recognition. Many existing methods achieve text segmentation by evaluating the local stroke geometry and imposing constraint on the size of each resulting character, such as the character width, height and aspect ratio. These constraints are well suited for printed texts, but may not hold for handwritten texts. Other methods apply holistic approach by using setof lexicons to guide and correct the segmentation and recognition. This approach may fail when the lexicon domain is insufficient. In this paper, we present a new global non-holistic method for handwritten text segmentation, which does not make any limiting assumptions on the characterize and the number of characters in a word. Specifically, the proposed method finds the text segmentation with the maximum average likeliness for the resulting characters. For this purpose, we use a graph model that describes the possible locations for segmenting neighboring characters, and we then develop an average longest path algorithm to identify the globally optimal segmentation. We conduct experiments on real images of handwritten texts taken from the IAM handwriting database and compare the performance of the proposed method against an existing text segmentation algorithm that uses dynamic programming.
Publish Year: 2013
Published in: WACV – IEEE
موضوع: تشخصی دست خط (Handwritten Text Recognition)
ایران سای – مرحع علمی فنی مهندسی
حامی دانش بومی ایرانیان
به نام خدا
Title: Influence of Sci-Fi Films on Artificial Intelligence and Vice-Versa
Authors: D Lorenk, M Tarhaniov and P Sincak
Abstract: Sci-fi technological movie domain is an important part of human culture. The paper focus on comparison study of selected robotics sci-fi movie domain from a technological point of view. It is necessary to accomplish technological analysis of studied sci-fi movies and able to distinguish about possible current technology and future direction of the artificial intelligence in the domain of Robot intelligence. The review of existing movies which are in fact influencing thinking of humans is essential since it can influence a future research direction in AI. This information is interesting for inspiration of students and research associates in theory and applications. In conclusion, we envision potential problems of social networks and impact of Internet of things facts which is becoming a reality with IPv6 protocol. The goal of the paper is also to underline the importance of such cultural phenomena as sci-fi movies for the future of humanity.
Publish Year: 2013
Published in: SAMI – IEEE
موضوع: هوش مصنوعی (Artificial Intelligence)
ایران سای – مرجع علمی فنی مهندسی
حامی دانش بومی ایرانیان
به نام خدا
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ایران سای – مرجع علمی فنی مهندسی
حامی دانش بومی ایرانیان
به نام خدا
Title: Increasing the efficiency of quicksort using a neural network based algorithm selection model
Author: Ugur Erkin Kocamaz
Abstract: Quicksort is one of the most popular sorting algorithms it is based on a divide-and-conquer technique and has a wide acceptance as the fastest general-purpose sorting technique. Though it is successful in separating large partitions into small ones, quicksort runs slowly when it processes its small partitions, for which completing the sorting through using a different sorting algorithm is much plausible solution. This variant minimizes the overall execution time but it switches to a constant sorting algorithm at a constant cut-off point. To cope with this constancy problem, it has been suggested that a dynamic model which can choose the fastest sorting algorithm for the small partitions. The model includes continuation with quicksort so that the cut-off point is also more flexible. To implement this with an intelligent algorithm selection model, artificial neural net- works are preferred due to their non-comparison, constant-time and low-cost architecture features. In spite of the fact that finding the best sorting algorithm by using a neural net- work causes some extra computational time, the gain in overall execution time is greater. As a result, a faster variant of quicksort has been implemented by using artificial neural network based algorithm selection approach. Experimental results of the proposed algorithm and the several other fast sorting algorithms have been presented, compared and discussed.
Publish Year: 2013
Published in: Information Sciences - Science Direct
موضوع: شبکه های عصبی مصنوعی (Artificial Neural Networks)
ایران سای – مرجع علمی فنی مهندسی
حامی دانش بومی ایرانیان
به نام خدا
Title: Comparative Study of Traditional Requirement Engineering and Agile Requirement Engineering
Authors: Asma Batool , Yasir Hafeez Motla , Bushra Hamid , Sohail Asghar, Muhammad Riaz , Mehwish Mukhtar, Mehmood Ahmed
Abstract: Traditional RE and Agile RE are two different approaches on the basis of their planning and control mechanism. This Paper distinguishes the Traditional RE and Agile RE. Furthermore it investigates the reasons for which software industries shifted from Traditional RE to Agile RE. Research is carried out by conducting a literature study and finally a case study of software development to evaluate which approach has better success rate than other. With the help of our finding and results we have evaluated that Agile RE performs better than Traditional RE in large organizations where changes evolve throughout the development phase of software life cycle. Keywords- Requirement Engineering , Traditional Requirement Engineering, Agile Requirement Engineering, Scrum, Extreme Programming, Obj ect Oriented Development, Requirement Elicitation, Requirement Analysis, Requirement Management, Software Requirement Specification.
Publish Year: 2013
Published in: ICACT – IEEE
موضوع: مهندسی نرم افزار
ایران سای – مرجع علمی فنی مهندسی
حامی دانش بومی ایرانیان
