{
  "id": "1702.00723",
  "version": "v1",
  "published": "2017-02-01T18:32:12.000Z",
  "updated": "2017-02-01T18:32:12.000Z",
  "title": "Handwritten Recognition Using SVM, KNN and Neural Network",
  "authors": [
    "Norhidayu Abdul Hamid",
    "Nilam Nur Amir Sjarif"
  ],
  "comment": "11 pages ; 22 Figures",
  "categories": [
    "cs.CV"
  ],
  "abstract": "Handwritten recognition (HWR) is the ability of a computer to receive and interpret intelligible handwritten input from source such as paper documents, photographs, touch-screens and other devices. In this paper we will using three (3) classification t o re cognize the handwritten which is SVM, KNN and Neural Network.",
  "revisions": [
    {
      "version": "v1",
      "updated": "2017-02-01T18:32:12.000Z"
    }
  ],
  "analyses": {
    "subjects": [
      "68Txx"
    ],
    "keywords": [
      "neural network",
      "handwritten recognition",
      "interpret intelligible handwritten input",
      "paper documents",
      "photographs"
    ],
    "note": {
      "typesetting": "TeX",
      "pages": 11,
      "language": "en",
      "license": "arXiv",
      "status": "editable"
    }
  }
}