چکیده مقاله
This paper investigates sea ice discrimination using SAR images through the utilizationof GLCM Gray Level Co occurrence Matrix feature extraction coupled with L scorefeature selection By focusing on the specific challenge of distinguishing between sea and ice,we aim to streamline the process while maintaining accuracy Our approach efficiently extractstexture features from Sentinel 1 images and employs L score feature selection to mitigate computationalburden without compromising discrimination efficacy This methodology offers apromising avenue for expediting sea ice discrimination tasks, essential for various remote sensingand environmental monitoring applications At the end, this offers significant time savings byapplying the feature selection method, which can happen with almost the same accuracy
کلیدواژهها
نویسندگان
Parsa Shamsaddini
Faculty of Intelligent Systems Engineering and Data Sciences, Persian Gulf University, Busher, Iran
Ahmad Keshavarz
Faculty of Intelligent Systems Engineering and Data Sciences, Persian Gulf University, Busher, Iran
Hojat Ghimatgar
Faculty of Intelligent Systems Engineering and Data Sciences, Persian Gulf University, Busher, Iran
Stefano Zecchetto
Istituto di Scienze Polari, Consiglio Nazionale delle Ricerche ,Padova, Italy
شیوه ارجاع
Shamsaddini, Parsa and Keshavarz, Ahmad and Ghimatgar, Hojat and Zecchetto, Stefano,1403,Sea-ice discrimination using texture analysis with feature selection over Sentinel-1 images,1st International Biennial Conference of Artificial Intelligence and Data Science 2024,Bushehr
ارائهشده در
مجموعه مقالات اولین کنفرانس بین المللی دوسالانه هوش مصنوعی و علوم داده3 اردیبهشت 1403 · بوشهر