基於深度學習且具有多物件偵測與辨識能力之智慧型自動結帳系統

A Deep Learning Based Intelligent Self-Checkout System with Multiple Objects Detection and Classification

姚世哲(Shih-Jhe Yao)

指導教授 ： 吳炳飛

國立交通大學/電機學院/電機與控制工程系所/碩士(2017年)

摘要

無資料

關鍵字

電腦視覺 ； 機器學習 ； 深度學習 ； 人工智慧 ； 影像處理 ； 零售 ； 結帳

並列摘要

無資料

並列關鍵字

Computer Vision ； Machine Learning ； Deep Learning ； Artificial Intelligence ； Image Process ； Retail ； Checkout

參考文獻

[1] (17 January 2014). With the Introduction of RAPTOR, ECRS Looks to Change How Groceries Are Purchased. [NEWS,Retail & Loyalty,]. Available: http://goo.gl/g8Bq1N

[2] Y. Jia, E. Shelhamer, J. Donahue, S. Karayev, J. Long, R. Girshick, et al., "Caffe: Convolutional architecture for fast feature embedding," in Proceedings of the 22nd ACM international conference on Multimedia, 2014, pp. 675-678.

[3] J. Redmon, S. Divvala, R. Girshick, and A. Farhadi, "You only look once: Unified, real-time object detection," in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2016, pp. 779-788.

[4] A. Krizhevsky, I. Sutskever, and G. E. Hinton, "Imagenet classification with deep convolutional neural networks," in Advances in neural information processing systems, 2012, pp. 1097-1105.

[5] H. Fradi and J.-L. Dugelay, "Robust foreground segmentation using improved gaussian mixture model and optical flow," in Informatics, Electronics & Vision (ICIEV), 2012 International Conference on, 2012, pp. 248-253.