{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,2]],"date-time":"2025-08-02T14:54:01Z","timestamp":1754146441710,"version":"3.41.2"},"publisher-location":"New York, NY, USA","reference-count":32,"publisher":"ACM","content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,7,22]]},"DOI":"10.1145\/3715335.3735462","type":"proceedings-article","created":{"date-parts":[[2025,7,18]],"date-time":"2025-07-18T09:31:52Z","timestamp":1752831112000},"page":"143-149","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Recycling Catalytic Converters for Sustainable Resource Management"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-2041-0837","authenticated-orcid":false,"given":"David","family":"Olah","sequence":"first","affiliation":[{"name":"Mount Royal University, Calgary, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-0450-2387","authenticated-orcid":false,"given":"Jesse","family":"Viehweger","sequence":"additional","affiliation":[{"name":"Mount Royal University, Calgary, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5668-6086","authenticated-orcid":false,"given":"Yasaman","family":"Amannejad","sequence":"additional","affiliation":[{"name":"Mount Royal University, Calgary, Alberta, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2025,7,21]]},"reference":[{"key":"e_1_3_3_2_2_2","doi-asserted-by":"crossref","unstructured":"M\u00a0Ali Akcayol and Can Cinar. 2005. Artificial neural network based modeling of heated catalytic converter performance. Applied Thermal Engineering 25 14-15 (2005) 2341\u20132350.","DOI":"10.1016\/j.applthermaleng.2004.12.014"},{"key":"e_1_3_3_2_3_2","doi-asserted-by":"crossref","unstructured":"John Atanbori and Samuel Rose. 2022. MergedNET: A simple approach for one-shot learning in siamese networks based on similarity layers. Neurocomputing 509 (2022) 1\u201310.","DOI":"10.1016\/j.neucom.2022.08.070"},{"key":"e_1_3_3_2_4_2","unstructured":"Jifeng Dai Yi Li Kaiming He and Jian Sun. 2016. R-fcn: Object detection via region-based fully convolutional networks. Advances in neural information processing systems 29 (2016)."},{"key":"e_1_3_3_2_5_2","doi-asserted-by":"crossref","unstructured":"Martin\u00a0A Fischler and Robert\u00a0A Elschlager. 1973. The representation and matching of pictorial structures. IEEE Transactions on computers 100 1 (1973) 67\u201392.","DOI":"10.1109\/T-C.1973.223602"},{"key":"e_1_3_3_2_6_2","volume-title":"Hands-on machine learning with Scikit-Learn, Keras, and TensorFlow","author":"G\u00e9ron Aur\u00e9lien","year":"2022","unstructured":"Aur\u00e9lien G\u00e9ron. 2022. Hands-on machine learning with Scikit-Learn, Keras, and TensorFlow. \" O\u2019Reilly Media, Inc.\"."},{"key":"e_1_3_3_2_7_2","doi-asserted-by":"crossref","unstructured":"Luigi Glielmo Michele Milano and Stefania Santini. 2000. A machine learning approach to modeling and identification of automotive three-way catalytic converters. IEEE\/ASME transactions on mechatronics 5 2 (2000) 132\u2013141.","DOI":"10.1109\/3516.847086"},{"key":"e_1_3_3_2_8_2","doi-asserted-by":"crossref","unstructured":"Jiuxiang Gu Zhenhua Wang Jason Kuen Lianyang Ma Amir Shahroudy Bing Shuai Ting Liu Xingxing Wang Gang Wang Jianfei Cai et\u00a0al. 2018. Recent advances in convolutional neural networks. Pattern recognition 77 (2018) 354\u2013377.","DOI":"10.1016\/j.patcog.2017.10.013"},{"key":"e_1_3_3_2_9_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-11206-0_9"},{"key":"e_1_3_3_2_10_2","doi-asserted-by":"crossref","unstructured":"Chih-Chung Hsu Yi-Xiu Zhuang and Chia-Yen Lee. 2020. Deep fake image detection based on pairwise learning. Applied Sciences 10 1 (2020) 370.","DOI":"10.3390\/app10010370"},{"key":"e_1_3_3_2_11_2","doi-asserted-by":"crossref","unstructured":"David\u00a0H Hubel and Torsten\u00a0N Wiesel. 1962. Receptive fields binocular interaction and functional architecture in the cat\u2019s visual cortex. The Journal of physiology 160 1 (1962) 106.","DOI":"10.1113\/jphysiol.1962.sp006837"},{"key":"e_1_3_3_2_12_2","unstructured":"Liu Jian-Wei Li Hai-En and Luo Xiong-Lin. 2014. Learning technique of probabilistic graphical models: a review. Acta Automatica Sinica 40 6 (2014) 1025\u20131044."},{"key":"e_1_3_3_2_13_2","doi-asserted-by":"crossref","unstructured":"Emmy Kritsanaviparkporn Francisco\u00a0M Baena-Moreno and TR Reina. 2021. Catalytic converters for vehicle exhaust: fundamental aspects and technology overview for newcomers to the field. Chemistry 3 2 (2021) 630\u2013646.","DOI":"10.3390\/chemistry3020044"},{"key":"e_1_3_3_2_14_2","doi-asserted-by":"crossref","unstructured":"Yann LeCun Yoshua Bengio and Geoffrey Hinton. 2015. Deep learning. nature 521 7553 (2015) 436\u2013444.","DOI":"10.1038\/nature14539"},{"key":"e_1_3_3_2_15_2","doi-asserted-by":"publisher","DOI":"10.1109\/CCDC.2019.8832435"},{"key":"e_1_3_3_2_16_2","doi-asserted-by":"crossref","unstructured":"Li Liu Wanli Ouyang Xiaogang Wang Paul Fieguth Jie Chen Xinwang Liu and Matti Pietik\u00e4inen. 2020. Deep learning for generic object detection: A survey. International journal of computer vision 128 (2020) 261\u2013318.","DOI":"10.1007\/s11263-019-01247-4"},{"key":"e_1_3_3_2_17_2","first-page":"1","volume-title":"2016 IEEE Symposium Series on Computational Intelligence (SSCI)","author":"Liu Yanzhu","year":"2016","unstructured":"Yanzhu Liu, Xiaojie Li, Adams Wai\u00a0Kin Kong, and Chi\u00a0Keong Goh. 2016. Learning from small data: A pairwise approach for ordinal regression. In 2016 IEEE Symposium Series on Computational Intelligence (SSCI). IEEE, 1\u20136."},{"key":"e_1_3_3_2_18_2","unstructured":"Tan Mingxing and V\u00a0Le Quoc. 2019. Efficientnet: Rethinking model scaling for convolutional neural networks. arXiv preprint arXiv:1905.11946 1 (2019)."},{"key":"e_1_3_3_2_19_2","doi-asserted-by":"crossref","unstructured":"Ayodele\u00a0T Odularu Peter\u00a0A Ajibade Johannes\u00a0Z Mbese Opeoluwa\u00a0O Oyedeji et\u00a0al. 2019. Developments in platinum-group metals as dual antibacterial and anticancer agents. Journal of Chemistry 2019 (2019).","DOI":"10.1155\/2019\/5459461"},{"key":"e_1_3_3_2_20_2","doi-asserted-by":"crossref","unstructured":"OA Odunlami OK Oderinde FA Akeredolu JA Sonibare OR Obanla and ME Ojewumi. 2022. The effect of air-fuel ratio on tailpipe exhaust emission of motorcycles. Fuel Communications 11 (2022) 100040.","DOI":"10.1016\/j.jfueco.2021.100040"},{"key":"e_1_3_3_2_21_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-72350-1_11"},{"key":"e_1_3_3_2_22_2","volume-title":"AIP conference proceedings","author":"Rajendran Rajasekar","year":"2020","unstructured":"Rajasekar Rajendran, U Logesh, NS Praveen, and Ganesan Subbiah. 2020. Optimum design of catalytic converter to reduce carbon monoxide emissions on diesel engine. In AIP conference proceedings , Vol.\u00a02311. AIP Publishing."},{"key":"e_1_3_3_2_23_2","unstructured":"Shaoqing Ren Kaiming He Ross Girshick and Jian Sun. 2015. Faster r-cnn: Towards real-time object detection with region proposal networks. Advances in neural information processing systems 28 (2015)."},{"key":"e_1_3_3_2_24_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00474"},{"key":"e_1_3_3_2_25_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298682"},{"key":"e_1_3_3_2_26_2","doi-asserted-by":"crossref","unstructured":"Connor Shorten and Taghi\u00a0M Khoshgoftaar. 2019. A survey on image data augmentation for deep learning. Journal of big data 6 1 (2019) 1\u201348.","DOI":"10.1186\/s40537-019-0197-0"},{"key":"e_1_3_3_2_27_2","doi-asserted-by":"publisher","DOI":"10.1109\/BigComp57234.2023.00078"},{"key":"e_1_3_3_2_28_2","doi-asserted-by":"crossref","unstructured":"Farhana Sultana Abu Sufian and Paramartha Dutta. 2020. A review of object detection models based on convolutional neural network. Intelligent computing: image processing based applications (2020) 1\u201316.","DOI":"10.1007\/978-981-15-4288-6_1"},{"key":"e_1_3_3_2_29_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.244"},{"key":"e_1_3_3_2_30_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.220"},{"key":"e_1_3_3_2_31_2","first-page":"6105","volume-title":"International conference on machine learning","author":"Tan Mingxing","year":"2019","unstructured":"Mingxing Tan and Quoc Le. 2019. Efficientnet: Rethinking model scaling for convolutional neural networks. In International conference on machine learning. PMLR, 6105\u20136114."},{"key":"e_1_3_3_2_32_2","doi-asserted-by":"crossref","unstructured":"Michael Tynes Wenhao Gao Daniel\u00a0J Burrill Enrique\u00a0R Batista Danny Perez Ping Yang and Nicholas Lubbers. 2021. Pairwise Difference Regression: A Machine Learning Meta-algorithm for Improved Prediction and Uncertainty Quantification in Chemical Search. Journal of Chemical Information and Modeling 61 8 (2021) 3846\u20133857.","DOI":"10.1021\/acs.jcim.1c00670"},{"key":"e_1_3_3_2_33_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-10590-1_53"}],"event":{"name":"COMPASS '25: ACM SIGCAS\/SIGCHI Conference on Computing and Sustainable Societies","location":"Toronto ON Canada","acronym":"COMPASS '25","sponsor":["SIGCHI ACM Special Interest Group on Computer-Human Interaction","SIGCAS ACM Special Interest Group on Computers and Society"]},"container-title":["Proceedings of the ACM SIGCAS\/SIGCHI Conference on Computing and Sustainable Societies"],"original-title":[],"deposited":{"date-parts":[[2025,7,18]],"date-time":"2025-07-18T09:35:07Z","timestamp":1752831307000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3715335.3735462"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,7,21]]},"references-count":32,"alternative-id":["10.1145\/3715335.3735462","10.1145\/3715335"],"URL":"https:\/\/doi.org\/10.1145\/3715335.3735462","relation":{},"subject":[],"published":{"date-parts":[[2025,7,21]]},"assertion":[{"value":"2025-07-21","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}