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Performance Evaluation of Deep Learning Models for Ship Detection

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Computer Vision and Image Processing (CVIP 2021)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1568))

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Abstract

Although enormous success is achieved in the field of object detection, yet ship detection in high-resolution images is still an crucial task. Ship detection from optical remote sensing images plays a significant role in military and civil applications. For maritime surveillance, monitoring and traffic supervision ship detection deserves optimal solutions to identify objects accurately with faster speed. In this work, various object detection methods such as You Only Look Once (YOLO) v3, YOLO v4, RetinaNet152, EfficientDet-D2 and Faster-RCNN have been implemented to improve efficiency, speed and accuracy. Numerous experiments were conducted to evaluate the efficiency of object detection methods. The YOLO v4 with custom selection of anchor boxes using K-means++ clustering algorithm outperformed as compared to other detection methods in terms of accuracy, which is evaluated using COCO metrics, training and detection time. All the experiments are performed on the Airbus detection dataset from https://www.kaggle.com/c/airbus-ship-detection.

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Authors and Affiliations

  1. Punjab Engineering College, Chandigarh, 160012, India

    Rahul Sharma, Harshit Sharma, Tamanna Meena, Padmavati Khandnor, Palak Bansal & Paras Sharma

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  1. Rahul Sharma
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  2. Harshit Sharma
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  3. Tamanna Meena
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  4. Padmavati Khandnor
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  5. Palak Bansal
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  6. Paras Sharma
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Corresponding author

Correspondence to Tamanna Meena .

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Editors and Affiliations

  1. Indian Institute of Technology Roorkee, Roorkee, India

    Balasubramanian Raman

  2. Indian Institute of Technology Ropar, Ropar, India

    Subrahmanyam Murala

  3. Jadavpur University, Kolkata, India

    Ananda Chowdhury

  4. Indian Institute of Technology Ropar, Ropar, India

    Abhinav Dhall

  5. Indian Institute of Technology Ropar, Ropar, India

    Puneet Goyal

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Sharma, R., Sharma, H., Meena, T., Khandnor, P., Bansal, P., Sharma, P. (2022). Performance Evaluation of Deep Learning Models for Ship Detection. In: Raman, B., Murala, S., Chowdhury, A., Dhall, A., Goyal, P. (eds) Computer Vision and Image Processing. CVIP 2021. Communications in Computer and Information Science, vol 1568. Springer, Cham. https://doi.org/10.1007/978-3-031-11349-9_24

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  • DOI: https://doi.org/10.1007/978-3-031-11349-9_24

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