WE4.M1.5
Patch-Based Tiny Object Classification for High Resolution Aerial Images
Mohammad Iqbal Nouyed, Gianfranco Doretto, Donald A. Adjeroh, West Virginia University, United States
Session:
WE4.M1: Deep Learning for Image Classification Oral
Track:
Data Analysis
Location:
Mezzanine: Room M1
Presentation Time:
Wednesday, 6 August, 16:45 - 17:00
Session Chair:
Martina Pastorino, University of Genoa
Session WE4.M1
WE4.M1.1: CLASSIFICATION OF HYPERSPECTRAL IMAGES USING GRAPH KOLMOGOROV-ARNOLD CONVOLUTIONAL NETWORK WITH LIMITED SAMPLES
Hengyi Zheng, Hui Shen, Weimeng Xu, Yufan Yang, Zhihao Shen, Hongjun Su, Hohai University, China; Qian Du, Mississippi State University, United States
WE4.M1.2: CSMAMBA: A MULTI-SCALE FRAMEWORK INTEGRATING CNN WITH SUPERPIXEL-LEVEL MAMBA FOR HYPERSPECTRAL IMAGE CLASSIFICATION
Yilin Duan, China University of Geosciences, China; Hesong Hu, Mengxiong Tang, Guangzhou Municipal Construction Group Co., Ltd, China; Jia Chen, Wuhan University of Science and Technology, China; Zhaozhao Zeng, Jun Li, China University of Geosciences, China
WE4.M1.3: FUNCTION-LEVEL BUILDING FOOTPRINT SEGMENTATION BASED ON VISUAL-LANGUAGE FOUNDATION MODEL
Da He, Xiaoping Liu, Qian Shi, Yan Zhou, Sun Yat-Sen University, China; Qiqi Zhu, China University of Geosciences (Wuhan), China
WE4.M1.4: MULTI-LABEL REMOTE SENSING IMAGE CLASSIFICATION VIA SCENE-TO-LABEL LEARNING
Ruiqi Du, Xu Tang, Jingjing Ma, Xiangrong Zhang, Xidian University, China
WE4.M1.5: Patch-Based Tiny Object Classification for High Resolution Aerial Images
Mohammad Iqbal Nouyed, Gianfranco Doretto, Donald A. Adjeroh, West Virginia University, United States
Resources