Offline Handwritten Character Recognition using MLPNN and PSO Algorithm


Authors : Aarthna Maheshwari, Khushboo Shah

Volume/Issue : Volume 3 - 2018, Issue 2 - February

Google Scholar : https://goo.gl/DF9R4u

Scribd : https://goo.gl/agkVjr

Thomson Reuters ResearcherID : https://goo.gl/3bkzwv

Abstract : Classical techniques are not flexible and adaptive for new handwriting constraints. Offline handwritten character recognition for English alphabets has been proposed in this paper. The proposed system uses three layer feed forward neural network and optimized the weight using PSO algorithm. The proposed system works well with benchmark dataset from C.E.D.A.R.

Classical techniques are not flexible and adaptive for new handwriting constraints. Offline handwritten character recognition for English alphabets has been proposed in this paper. The proposed system uses three layer feed forward neural network and optimized the weight using PSO algorithm. The proposed system works well with benchmark dataset from C.E.D.A.R.

Video Explanation for Published paper

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