XGBoosted Binary CNNs for Multi-Class Classification of Colorectal Polyp Size-Reference-Cited by-同舟云学术

XGBoosted Binary CNNs for Multi-Class Classification of Colorectal Polyp Size

Published:2023 Issue: Volume:11 Page:128461-128472
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Haldar Promit¹,Sharma Vanshali²^ORCID,Iwahori Yuji³^ORCID,Bhuyan M. K.¹^ORCID,Wang Aili⁴^ORCID,Wu Haibin⁴^ORCID,Kasugai Kunio⁵

Affiliation:

1. Department of Electronics and Electrical Engineering, Indian Institute of Technology Guwahati, Guwahati, India

2. Department of Computer Science and Engineering, Indian Institute of Technology Guwahati, Guwahati, India

3. Department of Computer Science, Chubu University, Kasugai, Japan

4. Higher Educational Key Laboratory for Measuring and Control Technology and Instrumentations of Heilongjiang, Harbin University of Science and Technology, Harbin, China

5. Department of Gastroenterology, Aichi Medical University, Nagakute, Japan

Funder

High End Foreign Experts Introduction Program

Reserved Leaders of Heilongjiang Provincial Leading Talent Echelon 2021

Japan Society for the Promotion of Science (JSPS) Grant-in-Aid for Scientific Research

Chubu University Grant

Department of Science and Technology, Government of India, through the Innovation in Science Pursuit for Inspired Research (INSPIRE) Fellowship

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10319404.pdf?arnumber=10319404

Reference23 articles.

1. Using the Infocus-Breakpoint to estimate the scale of neoplasia in colonoscopy

2. Automated sizing of colorectal polyps using computer vision

3. SSD: Single shot multibox detector;liu;Proc 14th Eur Conf Comput Vis (ECCV),2016

4. Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-Shot Cross-Dataset Transfer