A novel weakly-supervised approach for RGB-D-based nuclear waste object detection

Li Sun; Cheng Zhao; Zhi Yan; Pengcheng Liu; Tom Duckett; Rustam Stolkin

doi:10.1109/JSEN.2018.2888815

A novel weakly-supervised approach for RGB-D-based nuclear waste object detection

Li Sun, Cheng Zhao, Zhi Yan, Pengcheng Liu, Tom Duckett, Rustam Stolkin

Computer Science

Research output: Contribution to journal › Article › peer-review

Original language	English
Pages (from-to)	3487-3500
Number of pages	14
Journal	IEEE Sensors Journal
Volume	19
Issue number	9
Early online date	19 Dec 2018
DOIs	https://doi.org/10.1109/JSEN.2018.2888815
Publication status	Published - 1 May 2019

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10.1109/JSEN.2018.2888815

http://eprints.lincoln.ac.uk/35699/

Pengcheng Liu
- pengcheng.liuyork.acuk
- Computer Science - Senior Lecturer
Person: Academic

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title = "A novel weakly-supervised approach for RGB-D-based nuclear waste object detection",

author = "Li Sun and Cheng Zhao and Zhi Yan and Pengcheng Liu and Tom Duckett and Rustam Stolkin",

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AU - Sun, Li

AU - Zhao, Cheng

AU - Yan, Zhi

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AU - Duckett, Tom

AU - Stolkin, Rustam

PY - 2019/5/1

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JO - IEEE Sensors Journal

JF - IEEE Sensors Journal

IS - 9

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A novel weakly-supervised approach for RGB-D-based nuclear waste object detection

Bibliographical note

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Profiles

Pengcheng Liu

Cite this