Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/74573
Title: Study of machine intelligence for SAR image analysis
Authors: Wang, Siqi
Keywords: DRNTU::Engineering
Issue Date: 2018
Abstract: Image segmentation and object detection are two fundamental but major applications of machine intelligence. With the help of machine learning, image processing work can be done properly in a very short period even if huge amount of images are provided. In this report, the author presents a new approach to detect and classify geographical images which are captured by satellites (SAR) by using Extreme Learning Machine (ELM) methodology. Satellite images and extract representative attributes were collected as row sample data. Followed by training the programme with sample data collected and use the trained machine to predict land-cover types of new geographical images. Compared with conventional segmentation method, which is based on manually work, the performance for machine intelligence auto-classify programme has shown great improvement of time consuming on the test images while maintaining an acceptable accuracy and more consistent performance when dealing with huge amount of images. The introduced machine intelligence based method outperforms the conventional method in both time consuming and labor wasting.
URI: http://hdl.handle.net/10356/74573
Rights: Nanyang Technological University
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)

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