{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T12:02:29Z","timestamp":1775044949534,"version":"3.50.1"},"reference-count":32,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2019,3,20]],"date-time":"2019-03-20T00:00:00Z","timestamp":1553040000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["ASI"],"abstract":"<jats:p>This work is a part of an ongoing study to substitute the identification of waste containers via radio-frequency identification. The purpose of this paper is to propose a method of identification based on computer vision that performs detection using images, video, or real-time video capture to identify different types of waste containers. Compared to the current method of identification, this approach is more agile and does not require as many resources. Two approaches are employed, one using feature detectors\/descriptors and other using convolutional neural networks. The former used a vector of locally aggregated descriptors (VLAD); however, it failed to accomplish what was desired. The latter used you only look once (YOLO), a convolutional neural network, and reached an accuracy in the range of 90%, meaning that it correctly identified and classified 90% of the pictures used on the test set.<\/jats:p>","DOI":"10.3390\/asi2010011","type":"journal-article","created":{"date-parts":[[2019,3,21]],"date-time":"2019-03-21T04:11:56Z","timestamp":1553141516000},"page":"11","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["Detection of Waste Containers Using Computer Vision"],"prefix":"10.3390","volume":"2","author":[{"given":"Miguel","family":"Valente","sequence":"first","affiliation":[{"name":"Escola Superior de Tecnologia, Instituto Polit\u00e9cnico de Castelo Branco, 6000-767 Castelo Branco, Portugal"}]},{"given":"H\u00e9lio","family":"Silva","sequence":"additional","affiliation":[{"name":"EVOX Technologies, 6000-767 Castelo Branco, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5830-3790","authenticated-orcid":false,"given":"Jo\u00e3o","family":"Caldeira","sequence":"additional","affiliation":[{"name":"Escola Superior de Tecnologia, Instituto Polit\u00e9cnico de Castelo Branco, 6000-767 Castelo Branco, Portugal"},{"name":"Instituto de Telecomunica\u00e7\u00f5es, Universidade da Beira Interior, 6201-001 Covilh\u00e3, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8057-5474","authenticated-orcid":false,"given":"Vasco","family":"Soares","sequence":"additional","affiliation":[{"name":"Escola Superior de Tecnologia, Instituto Polit\u00e9cnico de Castelo Branco, 6000-767 Castelo Branco, Portugal"},{"name":"Instituto de Telecomunica\u00e7\u00f5es, Universidade da Beira Interior, 6201-001 Covilh\u00e3, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1691-1709","authenticated-orcid":false,"given":"Pedro","family":"Gaspar","sequence":"additional","affiliation":[{"name":"Departamento de Engenharia Eletromec\u00e2nica, Universidade da Beira Interior, 6201-001 Covilh\u00e3, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2019,3,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1109\/JIOT.2014.2306328","article-title":"Internet of things for smart cities","volume":"1","author":"Zanella","year":"2014","journal-title":"IEEE Internet Things J."},{"key":"ref_2","first-page":"447","article-title":"RFID application in municipal solid waste management system","volume":"3","author":"Abdoli","year":"2009","journal-title":"IJER"},{"key":"ref_3","first-page":"27","article-title":"A feasibility study of a RFID traceability system in municipal solid waste management","volume":"12","author":"Gnoni","year":"2013","journal-title":"Int. J. Inf. Technol. Manag."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Szeliski, R. (2010). Computer Vision: Algorithms and Applications, Springer Science & Business Media.","DOI":"10.1007\/978-1-84882-935-0"},{"key":"ref_5","unstructured":"Achatz, S. (2016). State of the Art of Object Recognition Techniques. Sci. Semin. Neurocientific Syst. Theory."},{"key":"ref_6","unstructured":"Zhao, Z.-Q., Zheng, P., Xu, S., and Wu, X. (arXiv, 2018). Object detection with deep learning: A review, arXiv."},{"key":"ref_7","unstructured":"Hu, F., Zhu, Z., and Zhang, J. (2014). Mobile panoramic vision for assisting the blind via indexing and localization. European Conference on Computer Vision, Springer."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"225","DOI":"10.1016\/j.patcog.2015.12.010","article-title":"Robust lane detection using two-stage feature extraction with curve fitting","volume":"59","author":"Niu","year":"2016","journal-title":"Pattern Recognit."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1224","DOI":"10.1109\/TPAMI.2017.2709749","article-title":"SIFT meets CNN: A decade survey of instance retrieval","volume":"40","author":"Zheng","year":"2018","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_10","unstructured":"Zhou, W., Li, H., and Tian, Q. (arXiv, 2017). Recent Advance in Content-based Image Retrieval: A Literature Survey, arXiv."},{"key":"ref_11","unstructured":"Kumar, K.K. (2010, January 12\u201313). CBIR: Content Based Image Retrieval. Proceedings of the National Conference on Recent Trends in Information\/Network Security, Chennai, India."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"J\u00e9gou, H., Douze, M., Schmid, C., and P\u00e9rez, P. (2010, January 13\u201318). Aggregating local descriptors into a compact image representation. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), San Francisco, CA, USA.","DOI":"10.1109\/CVPR.2010.5540039"},{"key":"ref_13","unstructured":"Diaz, J.G. (2019, February 14). VLAD. GitHub Repository. Available online: https:\/\/github.com\/jorjasso\/VLAD."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Rublee, E., Rabaud, V., Konolige, K., and Bradski, G. (2011, January 6\u201313). ORB: An efficient alternative to SIFT or SURF. Proceedings of the 2011 IEEE International Conference on Computer Vision (ICCV), Barcelona, Spain.","DOI":"10.1109\/ICCV.2011.6126544"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Bay, H., Tuytelaars, T., and van Gool, L. (2006, January 7\u201313). Surf: Speeded up robust features. Proceedings of the European Conference on Computer Vision, Graz, Austria.","DOI":"10.1007\/11744023_32"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1023\/B:VISI.0000029664.99615.94","article-title":"Distinctive image features from scale-invariant keypoints","volume":"60","author":"Lowe","year":"2004","journal-title":"Int. J. Comput. Vis."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"177","DOI":"10.1561\/0600000017","article-title":"Local invariant feature detectors: A survey","volume":"3","author":"Tuytelaars","year":"2008","journal-title":"Found. Trends\u00ae Comput. Graph. Vis."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Salahat, E., and Qasaimeh, M. (2017, January 22\u201325). Recent advances in features extraction and description algorithms: A comprehensive survey. Proceedings of the 2017 IEEE International Conference on Industrial Technology (ICIT), Toronto, ON, Canada.","DOI":"10.1109\/ICIT.2017.7915508"},{"key":"ref_19","unstructured":"Miksik, O., and Mikolajczyk, K. (2012, January 11\u201315). Evaluation of local detectors and descriptors for fast feature matching. Proceedings of the 21st International Conference on Pattern Recognition (ICPR), Tsukuba, Japan."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Redmon, J., Divvala, S., Girshick, R., and Farhadi, A. (2016, January 27\u201330). You only look once: Unified, real-time object detection. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Las Vegas, NV, USA.","DOI":"10.1109\/CVPR.2016.91"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Redmon, J., and Farhadi, A. (2016, December 25). YOLO9000: Better, faster, stronger. arXiv preprint. ArXiv161208242. Available online: https:\/\/arxiv.org\/abs\/1612.08242.","DOI":"10.1109\/CVPR.2017.690"},{"key":"ref_22","unstructured":"Redmon, J., and Farhadi, A. (arXiv, 2018). Yolov3: An incremental improvement, arXiv."},{"key":"ref_23","first-page":"120","article-title":"The OpenCV Library","volume":"25","author":"Bradski","year":"2000","journal-title":"Dr. Dobb\u2019s J. Softw. Tools"},{"key":"ref_24","unstructured":"Bober-Irizar, M. (2019, February 14). PyVLAD. GitHub Repository. Available online: https:\/\/github.com\/mxbi\/PyVLAD."},{"key":"ref_25","unstructured":"Lin, T. (2019, February 14). labelImg. GitHub Repository. Available online: https:\/\/github.com\/tzutalin\/labelImg."},{"key":"ref_26","unstructured":"Trieu, T.H. (2019, February 14). Darkflow. GitHub Repository. Available online: https:\/\/github.com\/thtrieu\/darkflow."},{"key":"ref_27","unstructured":"Bezlepkin, A. (2019, February 14). Darknet. GitHub Repository. Available online: https:\/\/github.com\/AlexeyAB\/darknet."},{"key":"ref_28","unstructured":"NVIDIA Corporation (2007). NVIDIA CUDA Compute Unified Device Architecture Programming Guide, NVIDIA Corporation."},{"key":"ref_29","unstructured":"Chetlur, S., Woolley, C., Vandermersch, P., Cohen, J., Tran, J., Catanzaro, B., and Shelhamer, E. (arXiv, 2014). Cudnn: Efficient primitives for deep learning, arXiv."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"303","DOI":"10.1007\/s11263-009-0275-4","article-title":"The pascal visual object classes (voc) challenge","volume":"88","author":"Everingham","year":"2010","journal-title":"Int. J. Comput. Vis."},{"key":"ref_31","unstructured":"Cartucho, J. (2019, February 14). map. GitHub Repository. Available online: https:\/\/github.com\/Cartucho\/mAP."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Arandjelovic, R., and Zisserman, A. (2013, January 23\u201328). All about VLAD. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Portland, OR, USA.","DOI":"10.1109\/CVPR.2013.207"}],"container-title":["Applied System Innovation"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2571-5577\/2\/1\/11\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T12:39:19Z","timestamp":1760186359000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2571-5577\/2\/1\/11"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,3,20]]},"references-count":32,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2019,3]]}},"alternative-id":["asi2010011"],"URL":"https:\/\/doi.org\/10.3390\/asi2010011","relation":{},"ISSN":["2571-5577"],"issn-type":[{"value":"2571-5577","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,3,20]]}}}