{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/vehicle-color-recognition-using-convolutional","title":"Vehicle Color Recognition using Convolutional Neural Network","arxiv_id":"1510.07391","date":"2015-10-26","proceeding":null,"authors":["Reza Fuad Rachmadi","I Ketut Eddy Purnama"],"abstract":"Vehicle color information is one of the important elements in ITS\n(Intelligent Traffic System). In this paper, we present a vehicle color\nrecognition method using convolutional neural network (CNN). Naturally, CNN is\ndesigned to learn classification method based on shape information, but we\nproved that CNN can also learn classification based on color distribution. In\nour method, we convert the input image to two different color spaces, HSV and\nCIE Lab, and run it to some CNN architecture. The training process follow\nprocedure introduce by Krizhevsky, that learning rate is decreasing by factor\nof 10 after some iterations. To test our method, we use publicly vehicle color\nrecognition dataset provided by Chen. The results, our model outperform the\noriginal system provide by Chen with 2% higher overall accuracy.","url_abs":"http://arxiv.org/abs/1510.07391v3","url_pdf":"http://arxiv.org/pdf/1510.07391v3.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"vehicle-color-recognition-using-convolutional","repo_url":"https://github.com/HoangTrinh/Vehicle_ReID_using_fusion_of_multi_features","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":null},{"paper_slug":"vehicle-color-recognition-using-convolutional","repo_url":"https://github.com/Recolip/pytorch_model","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"vehicle-color-recognition-using-convolutional","repo_url":"https://github.com/Spectra456/Color-Recognition-CNN","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":null},{"paper_slug":"vehicle-color-recognition-using-convolutional","repo_url":"https://github.com/i-am-g2/VehicleColorRecognition","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"vehicle-color-recognition-using-convolutional","repo_url":"https://github.com/jasonqhuang/Color_CNN","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":null},{"paper_slug":"vehicle-color-recognition-using-convolutional","repo_url":"https://github.com/jwhabi/Vehicle-Color-Identification","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"vehicle-color-recognition-using-convolutional","repo_url":"https://github.com/srihari-humbarwadi/Vehicle-Color-Recognition-using-Convolutional-Neural-Network","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":null},{"paper_slug":"vehicle-color-recognition-using-convolutional","repo_url":"https://github.com/tomjerrygithub/Pytorch_VehicleColorRecognition","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"classification","task_name":"General Classification"},{"task_slug":"vehicle-color-recognition","task_name":"Vehicle Color Recognition"}],"methods":[{"method_slug":"1d-cnn","method_name":"1D CNN"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}