Super resolution convolutional neural network based pre-processing for automatic polyp detection in colonoscopy images-Reference-Cited by-同舟云学术

Super resolution convolutional neural network based pre-processing for automatic polyp detection in colonoscopy images

Published:2021-03 Issue: Volume:90 Page:106959
ISSN:0045-7906
Container-title:Computers & Electrical Engineering
language:en
Short-container-title:Computers & Electrical Engineering

Author:

Taş Merve,Yılmaz Bülent

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,General Computer Science,Control and Systems Engineering

Reference28 articles.

1. Ren, S., K. He, R.B. Girshick, and J. Sun, Faster R-CNN: towards real-time object detection with region proposal networks. CoRR abs/1506.01497. arXiv preprint arXiv:1506.01497, 2015.

2. Ssd: single shot multibox detector;Liu,2016

3. You only look once: Unified, real-time object detection;Redmon,2016

4. Single-shot refinement neural network for object detection;Zhang,2018

5. M2det: A single-shot object detector based on multi-level feature pyramid network;Zhao,2019

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