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Adaptive convolutional neural network using N-gram for spatial object recognition

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Abstract

Remote sensing applications are playing a vital role to improve the commercial satellite imagery with high resolution. In the spatial information system, object detection is the basic needs for computing the mathematical model. Geographical object related analysis for the image is used to gather data from remote sensing images. In this paper, we propose an Adaptive Convolutional Neural Network model using N-gram for Spatial Object Recognition on Satellite Images. Our methodology needs a learning model for the structures in the images to gather the data using prior knowledge. N-gram uses the functionalities of learning models. Spatial object recognition is performed using the learning method to segment the images with the human subjects that can increase their understanding of including the perception, cognition and decision. The result obtained for two stage of image processing is collected, and a relationship to psychological and mathematical basis is made. The results show that convinced association relevant level to the human perception is serving additional to identify the spatial objects. The experimentation is performed in MATLAB software where the results proved that our methodology is superior suitable for precise object detection and recognition on dissimilar levels of satellite images.

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Acknowledgements

This research is funded by Vietnam National Foundation for Science and Technology Development (NAFOSTED) under grant number 102.05-2018.02.

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Authors and Affiliations

  1. Department of Electronics and Communication Engineering, Dr. Sivanthi Aditanar College of Engineering, Tiruchendur, India

    J. Joshua Bapu

  2. Department of Computer Science and Engineering, Dr. Sivanthi Aditanar College of Engineering, Tiruchendur, India

    D. Jemi Florinabel

  3. Department of Computer Science and Engineering, SCAD College of Engineering and Technology, Tirunelveli, India

    Y. Harold Robinson

  4. Department of Computer Science and Engineering, Anna University Regional Campus, Tirunelveli, India

    E. Golden Julie

  5. Department of Computer Science and Engineering, LNCT College, Bhopal, India

    Raghvendra Kumar

  6. School of Odonto – Stomatology, Hanoi Medical University, Hanoi, Vietnam

    Vo Truong Nhu Ngoc

  7. VNU Information Technology Institute, Vietnam National University, Hanoi, Vietnam

    Le Hoang Son

  8. Faculty of Computer Science and Engineering, Thuyloi University, Hanoi, Vietnam

    Tran Manh Tuan

  9. Thuong Mai University, Hanoi, Vietnam

    Cu Nguyen Giap

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  1. J. Joshua Bapu
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  2. D. Jemi Florinabel
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  8. Tran Manh Tuan
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  9. Cu Nguyen Giap
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Correspondence to Tran Manh Tuan.

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Bapu, J.J., Florinabel, D.J., Robinson, Y.H. et al. Adaptive convolutional neural network using N-gram for spatial object recognition. Earth Sci Inform 12, 525–540 (2019). https://doi.org/10.1007/s12145-019-00396-x

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