NDLI: Real time object recognition for teaching neural networks

Content Provider	IEEE Xplore Digital Library
Author	Khan, F. Cervantes, A.
Copyright Year	1999
Description	Author affiliation: Dept. of Comput. Sci., Texas Univ., Brownsville, TX, USA (Khan, F.)
Abstract	Undergraduate students in computer science learn best when they are given the opportunity to apply hardware and software concepts to real world systems, and neural-network applications present attractive possibilities for giving them such opportunity. An example of how to take advantage of these possibilities is given in this paper, which describes a specific neural network technique that has been developed and applied to the problem of identifying real world objects in real time. Those objects can be as simple as paper cut-outs or they can be mechanical objects such as a nut or a bolt. These objects are placed on a plane, and are "examined" by an "identifying system" consisting of a camera attached to a PC through a video capture card. The pixels collected from the image of the object are fed to a set of neural network nodes for pattern recognition. Patterns are recognized by a multi-layer neural network where the output of a neuron, which can be characterized by sigmoid "activation function", is a function of weighted inputs. Lisp is used as the programming language due to its simple syntax and powerful recursive features for processing lists. The binary equivalent of the computed output is evaluated as a recognition signature which is compared to the signature of objects in a list. Of course, the artificial neural network is "trainable". To master the technique, the students start by learning about neurons and forward and backpropagation methods, but they soon find themselves "training" a multilayered neural network that they themselves have built. The learning experience encompasses video capturing, image handling, filtering, and image compression, and it demystifies neural network programming.
File Size	513995
File Format	PDF
ISBN	0780356438
ISSN	01905848
DOI	10.1109/FIE.1999.839219
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1999-11-10
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Object recognition Education Neural networks Pattern recognition Multi-layer neural network Neurons Artificial neural networks Computer science Hardware Application software
Content Type	Text
Resource Type	Article
Subject	Education Computer Science Applications Software

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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