Gastrointestinal Tract Anomaly Detection from Endoscopic Videos Using Object Detection Approach

Author:

Chheda Tejas,Iyer Rithvika,Koppaka Soumya,Kalbande Dhananjay

Publisher

Springer International Publishing

Reference17 articles.

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2. Girshick, R.: Fast R-CNN. In: 2015 IEEE International Conference on Computer Vision (ICCV), pp. 1440–1448 (2015). https://doi.org/10.1109/ICCV.2015.169

3. Girshick, R.B., Donahue, J., Darrell, T., Malik, J.: Rich feature hierarchies for accurate object detection and semantic segmentation. CoRR abs/1311.2524 (2013). http://arxiv.org/abs/1311.2524

4. Iakovidis, D.K., Georgakopoulos, S.V., Vasilakakis, M., Koulaouzidis, A., Plagianakos, V.P.: Detecting and locating gastrointestinal anomalies using deep learning and iterative cluster unification. IEEE Trans. Med. Imaging 37(10), 2196–2210 (2018). https://doi.org/10.1109/TMI.2018.2837002

5. Jeong, J., Park, H., Kwak, N.: Enhancement of SSD by concatenating feature maps for object detection (2017)

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