А Nоvel Data-Driven Орtimаl Methоdоlоgy fоr Deteсting Shiр from Sаr Images Bаsed on Аrtifiсiаl Intelligenсe
M.S. Аntony Vigil1, Rishаbh Jаin2, Аbhinаv Сhаndrа3, Tаnmаy Аgаrwаl4
1M.S.Antony Vigil, Assistant Professor, Department of Computer Science and Engineering, SRM Institute of Science and Technology, Ramapuram, Chennai(Tamil Nadu), India.
2Rishabh Jain, Pursuing Bachelors, Computer Science and Engineering, SRM Institute of Science and Technology, Ramapuram, Chennai(Tamil Nadu), India.
3Abhinav Chandra, Student, Computer Science and Engineering, SRM Institute of Science and Technology, Chennai(Tamil Nadu), India.
4Tanmay Agarwal, Pursuing Bachelors, Computer Science and Engineering, SRM Institute of Science and Technology, Ramapuram, Chennai(Tamil Nadu), India.
Manuscript received on 29 May 2021 | Revised Manuscript received on 01 June 2021 | Manuscript Accepted on 15 June 2021 | Manuscript published on 30 June 2021 | PP: 17-22 | Volume-1 Issue-3, June 2021 | Retrieval Number: 100.1/ijainn.C1035061321 | DOI: 10.54105/ijainn.C1035.061321
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Published by Lattice Science Publication (LSP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: There are a variety of deep learning algorithms available in the supervision of ships, but they are dealing with multiple issues of inaccurate identification on rate and in adequate target detection on speed. At this stage, an algorithm is given оn Соnvоlutiоnаl Neural Network for target identification and detection using the ship image. The study involves the investigation of the reactions of hyper spectral atmospheric rectification on the accurate and precise results of ship detection. The ship features which were detected from two atmospheric rectified algorithms on airborne hyperspectral data were corrected by the application of these algorithms with the help of an unsupervised target detection procedure. High accuracy and fast ship identification was a result of this algorithm and using unique modules, improving the loss function and enlargement of data for the smaller targets. The results of the experiments show that our algorithm has given much better detection rate as compared to target detection algorithm using traditional machine learning.
Keywords: The Study Involves The Investigation of The Reactions of Hyper Spectral Atmospheric Rectification on The Accurate and Precise Results of Ship Detection.
Scope of the Article: Artificial Intelligence