Comparative analysis of validating parameters in the deep learning models for remotely sensed images
Author:
Affiliation:
1. School of Mathematics and Computing, Banasthali Vidyapith, Banasthali 304022, India
Publisher
Taru Publications
Subject
Applied Mathematics,Algebra and Number Theory,Analysis
Link
https://www.tandfonline.com/doi/pdf/10.1080/09720529.2022.2068602
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1. Research on Airplane and Ship Detection of Aerial Remote Sensing Images Based on Convolutional Neural Network
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3. Automatic Ship Detection in Remote Sensing Images from Google Earth of Complex Scenes Based on Multiscale Rotation Dense Feature Pyramid Networks
4. Agricultural Greenhouses Detection in High-Resolution Satellite Images Based on Convolutional Neural Networks: Comparison of Faster R-CNN, YOLO v3 and SSD
5. An Alternate Approach to Improve Access Time for Defining Frequent Item Set Through ‘A-Apriori’ in Textual Data Set
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