Active Learning-DETR: Cost-Effective Object Detection for Kitchen Waste-Reference-Cited by-同舟云学术

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Active Learning-DETR: Cost-Effective Object Detection for Kitchen Waste

Published:2024 Issue: Volume:73 Page:1-15
ISSN:0018-9456
Container-title:IEEE Transactions on Instrumentation and Measurement
language:
Short-container-title:IEEE Trans. Instrum. Meas.

Author:

Qin Hai¹^ORCID,Shu Liye¹^ORCID,Zhou Li¹^ORCID,Deng Songyun¹^ORCID,Xiao Haihua¹^ORCID,Sun Wei¹^ORCID,Liang Qiaokang¹^ORCID,Zhang Dan²^ORCID,Wang Yaonan¹^ORCID

Affiliation:

1. National Engineering Research Center for Robot Vision Perception and Control, College of Electrical and Information Engineering, Hunan University, Changsha, China

2. Department of Mechanical Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong

Funder

Project of the National Key Research and Development Program of China

National Natural Science Foundation of China

Hunan Provincial Natural Science Foundation of China

Scientific Research Project of Hunan Education Department

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/19/10367905/10443710.pdf?arnumber=10443710

Reference35 articles.

1. Co-composting of kitchen waste with agriculture and forestry residues and characteristics of compost with different particle size: An industrial scale case study

2. State-of-the-art of the pyrolysis and co-pyrolysis of food waste: Progress and challenges

3. Anaerobic digestion and recycling of kitchen waste: a review

4. Revealing influencing factors on global waste distribution via deep-learning based dumpsite detection from satellite imagery

5. Deep Learning Based Robot for Automatically Picking Up Garbage on the Grass

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