Study of Benchmark Datasets for Performance Evaluation of Content Based Image Retrieval System for Remote Sensing Images - Nisha Gupta (International Journal of Intelligent Systems and Applications in Engineering, 2024)
The development of new feature extraction techniques and the testing of fresh datasets have greatly improved image retrieval systems for remote sensing. When using Remote Sensing Image Retrieval (RSIR) techniques and assessing their effectiveness, benchmark datasets are essential. Notable advancements in creating benchmark datasets for RSIR systems are highlighted in the literature. Unisource retrieval are the two categories into which these datasets fall. While the query and the images that are retrieved come from the same source in Unisource retrieval, they come from distinct sources in cross-source retrieval. In order to determine which datasets are best suited for the use of deep learning Convolutional Neural Networks and contemporary transfer learning techniques, this research offers a thorough examination of the salient features of both types of remote sensing datasets.