mlsanityData to 7 Oct 2026

Waste detection in Pomerania: non-profit project for detecting waste in environment

arXiv 2105.06808 ↗First posted 12 May 2021cs.CV eess.IVcited by 8

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Abstract (arXiv)

Waste pollution is one of the most significant environmental issues in the modern world. The importance of recycling is well known, either for economic or ecological reasons, and the industry demands high efficiency. Our team conducted comprehensive research on Artificial Intelligence usage in waste detection and classification to fight the world's waste pollution problem. As a result an open-source framework that enables the detection and classification of litter was developed. The final pipeline consists of two neural networks: one that detects litter and a second responsible for litter classification. Waste is classified into seven categories: bio, glass, metal and plastic, non-recyclable, other, paper and unknown. Our approach achieves up to 70% of average precision in waste detection and around 75% of classification accuracy on the test dataset. The code used in the studies is publicly available online.

Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Builds on 41 of its 90 references that are in the map. First posted on arXiv 12 May 2021.

Builds on

41 of 90 references.

References · 41

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Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 1; 2023: 1; 2024: 3; 2025: 2; 2026: 1.

8 papers.

  1. 2023Optimized Custom Dataset for Efficient Detection of Underwater Trashcited by 3
  2. 2024Deep Learning Innovations for Underwater Waste Detection: An In-Depth Analysiscited by 3
  3. 2024Riverbed litter monitoring using consumer-grade aerial-aquatic speedy scanner (AASS) and deep learning based super-resolution reconstruction and detection networkcited by 2
  4. 2024Analyzing mixed construction and demolition waste in material recovery facilities: evolution, challenges, and applications of computer vision and deep learningcited by 1
  5. 2022Automated Medical Device Display Reading Using Deep Learning Object Detectioncited by 0
  6. 2025From Street Views to Urban Science: Discovering Road Safety Factors with Multimodal Large Language Modelscited by 0
  7. 2025YOLO-SAT: A Data-based and Model-based Enhanced YOLOv12 Model for Desert Waste Detection and Classificationcited by 0
  8. 2026Open-access model for detecting openly dumped dispersed municipal solid waste from crowdsourced UAV imagery in Sub-Saharan Africacited by 0