SECURE AND EFFICIENT IMAGE SCENE CLASSIFICATION USING CNN

SECURE AND EFFICIENT IMAGE SCENE CLASSIFICATION USING CNN

T.GEETHA1,    R.KAVIYA2,   T.KAVIYA2,   A.KIRUTHIKA,   C.KIRUTHIKA2

1.  Research Scholar, Dept of  CSE, B.S.Abdur Rahman Crescent Institute of    Science    & Technology, Vandalur,Chennai-600 048 Email : geethat_cse_jan21@crescent.education

2. Final year CSE, Dhanalakshmi Srinivasan engineering college ,Perambalur

Abstract: The utilization of remote detecting picture scene order, which endeavors to group remote detecting pictures into various semantic classes relying upon their substance. Profound learning-based remote detecting picture scene classification has created a ton of consideration and accomplished critical steps because of these organizations' solid element mastering abilities. As far as we could possibly know, there hasn't been an extensive examination of late profound learning progresses for scene order in remote detecting pictures. This cycle gives a careful assessment of profound learning calculations for remote detecting picture scene grouping, which is vital given the field's fast advancement. The remote detecting scene is dissected utilizing the profound gaining calculation from the info remote detecting photos, and afterward the profound learning strategy is used. After the pictures have been all prepared, the profound learning strategy predicts the result utilizing exactness, accuracy, review, and F1-score.

Keywords: Scene classification, Convolutional Neural Network (CNN), Remote Sensing (RS).