Research on the PDC rock cuttings image instance segmentation method based on improved U-Net++ network and multi-feature fusion-Reference-Cited by-同舟云学术

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Research on the PDC rock cuttings image instance segmentation method based on improved U-Net++ network and multi-feature fusion

Published:2024-05-28 Issue: Volume: Page:1-22
ISSN:1091-6466
Container-title:Petroleum Science and Technology
language:en
Short-container-title:Petroleum Science and Technology

Author:

Huo Fengcai¹²³^ORCID,Dong Shuai¹²³,Ren Weijian¹²,Dong Hongli¹²,Li Ang¹²³

Affiliation:

1. Artificial Intelligence Energy Research Institute, Northeast Petroleum University, Daqing, China

2. Heilongjiang Provincial Key Laboratory of Networking and Intelligent Control, Daqing, China

3. Bohai-rim Energy Research Institute of NEPU, Qinghuagndao, China

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/10916466.2024.2357699

Reference21 articles.

1. Segmentation of Oil Spills on Side-Looking Airborne Radar Imagery with Autoencoders

2. Cheng, B., R. Girshick, P. Dollár, A. C. Berg, and A. Kirillov. 2021. Boundary IoU: Improving object-centric image segmentation evaluation. Proceedings of the IEEE/CVF. Conference on Computer Vision and Pattern Recognition (CVPR), 15334–42. https://arxiv.org/pdf/2103.16562.pdf.

3. Bottom-up image detection of water channel slope damages based on superpixel segmentation and support vector machine

4. An End-to-End Oil-Spill Monitoring Method for Multisensory Satellite Images Based on Deep Semantic Segmentation

5. Fault estimation for complex networks with randomly varying topologies and stochastic inner couplings

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