{"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/a-framework-of-transfer-learning-in-object","title":"A Framework of Transfer Learning in Object Detection for Embedded Systems","arxiv_id":"1811.04863","date":"2018-11-12","proceeding":null,"authors":["Ioannis Athanasiadis","Panagiotis Mousouliotis","Loukas Petrou"],"abstract":"Transfer learning is one of the subjects undergoing intense study in the area\nof machine learning. In object recognition and object detection there are known\nexperiments for the transferability of parameters, but not for neural networks\nwhich are suitable for object detection in real time embedded applications,\nsuch as the SqueezeDet neural network. We use transfer learning to accelerate\nthe training of SqueezeDet to a new group of classes. Also, experiments are\nconducted to study the transferability and co-adaptation phenomena introduced\nby the transfer learning process. To accelerate training, we propose a new\nimplementation of the SqueezeDet training which provides a faster pipeline for\ndata processing and achieves 1.8 times speedup compared to the initial\nimplementation. Finally, we created a mechanism for automatic hyperparameter\noptimization using an empirical method.","url_abs":"http://arxiv.org/abs/1811.04863v2","url_pdf":"http://arxiv.org/pdf/1811.04863v2.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":"a-framework-of-transfer-learning-in-object","repo_url":"https://github.com/supernlogn/squeezeDetTL","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[{"task_slug":"hyperparameter-optimization","task_name":"Hyperparameter Optimization"},{"task_slug":"object","task_name":"Object"},{"task_slug":"object-detection","task_name":"Object Detection"},{"task_slug":"object-recognition","task_name":"Object Recognition"},{"task_slug":"transfer-learning","task_name":"Transfer Learning"},{"task_slug":"object-detection-1","task_name":"object-detection"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}