Object Detection using Transfer Learning for Underwater Robot

In this paper the usage of Transfer Learning method for object detection in underwater environment is experienced and evaluated. Deep learning method of YOLO is utilized for detection of different types of fish underwater. A ROV equipped with camera is employed for video streaming underwater and the data has been analyzed on the main computer Our experimental results confirmed improvement in the mAP by 4% using transfer learning.

[1]  R. A. Salam,et al.  Underwater Image Enhancement Using an Integrated Colour Model , 2007 .

[2]  Ling Shao,et al.  Transfer Learning for Visual Categorization: A Survey , 2015, IEEE Transactions on Neural Networks and Learning Systems.

[3]  Qiang Yang,et al.  A Survey on Transfer Learning , 2010, IEEE Transactions on Knowledge and Data Engineering.

[4]  Ali Farhadi,et al.  You Only Look Once: Unified, Real-Time Object Detection , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[5]  Ying-Ching Chen,et al.  Underwater Image Enhancement by Wavelength Compensation and Dehazing , 2012, IEEE Transactions on Image Processing.

[6]  Alexander Wong,et al.  Fast YOLO: A Fast You Only Look Once System for Real-time Embedded Object Detection in Video , 2017, ArXiv.

[7]  Luc Jaulin,et al.  Automatic underwater image pre-processing , 2006 .

[8]  Xiaogang Wang,et al.  Deep Learning Face Representation from Predicting 10,000 Classes , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.

[9]  Ali Farhadi,et al.  YOLO9000: Better, Faster, Stronger , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[10]  Raimondo Schettini,et al.  Underwater Image Processing: State of the Art of Restoration and Image Enhancement Methods , 2010, EURASIP J. Adv. Signal Process..

[11]  Joseph Redmon,et al.  YOLOv3: An Incremental Improvement , 2018, ArXiv.

[12]  Nicholas G. Polson,et al.  Deep learning for short-term traffic flow prediction , 2016, 1604.04527.

[13]  Naif Alajlan,et al.  Deep Learning Approach for Car Detection in UAV Imagery , 2017, Remote. Sens..

[14]  Vishal K. Mehta,et al.  Irrigation demand and supply, given projections of climate and land-use change, in Yolo County, California , 2013 .