Automatic product counting device

1980 ◽  
Vol 37 (3) ◽  
pp. 132-133
Author(s):  
V. S. Zolotkovskii ◽  
V. I. Belyakov ◽  
V. L. Sklyutovskii
Keyword(s):  
Counting Device ◽  
Product Counting ◽  
Automatic Product

scholarly journals Digital Cell Counting Device Integrated with a Single-Cell Array

PLoS ONE ◽  
2014 ◽  
Vol 9 (2) ◽  
pp. e89011 ◽  
Author(s):  
Tatsuya Saeki ◽  
Masahito Hosokawa ◽  
Tae-kyu Lim ◽  
Manabu Harada ◽  
Tadashi Matsunaga ◽  
...  
Keyword(s):  
Single Cell ◽  
Cell Counting ◽  
Cell Array ◽  
Counting Device

An activity layer for an intelligent automatic product design environment

1995 ◽  
Vol 29 (1-4) ◽  
pp. 717-721
Author(s):  
D. An ◽  
H.R. Parsaei ◽  
H.R. Leep ◽  
A.P. Nyaluke
Keyword(s):  
Product Design ◽  
Design Environment ◽  
Automatic Product

Microcontroller Based Retail Pharmaceutical Tablets Counting Device

2007 ◽  
Author(s):  
Amy Chang ◽  
Soon Chin Fhong ◽  
I. Agung Wibowo ◽  
Zaini Bin Tahir ◽  
Mohd Shaiffol B. Ahmad
Keyword(s):  
Pharmaceutical Tablets ◽  
Counting Device

scholarly journals Deep Learning for Retail Product Recognition: Challenges and Techniques

2020 ◽  
Vol 2020 ◽  
pp. 1-23
Author(s):  
Yuchen Wei ◽  
Son Tran ◽  
Shuxiang Xu ◽  
Byeong Kang ◽  
Matthew Springer
Keyword(s):  
Deep Learning ◽  
Visually Impaired ◽  
Retail Store ◽  
Social Progress ◽  
Time Saving ◽  
Daily Lives ◽  
Manual Operation ◽  
Comprehensive Literature Review ◽  
Public Datasets ◽  
Automatic Product

Taking time to identify expected products and waiting for the checkout in a retail store are common scenes we all encounter in our daily lives. The realization of automatic product recognition has great significance for both economic and social progress because it is more reliable than manual operation and time-saving. Product recognition via images is a challenging task in the field of computer vision. It receives increasing consideration due to the great application prospect, such as automatic checkout, stock tracking, planogram compliance, and visually impaired assistance. In recent years, deep learning enjoys a flourishing evolution with tremendous achievements in image classification and object detection. This article aims to present a comprehensive literature review of recent research on deep learning-based retail product recognition. More specifically, this paper reviews the key challenges of deep learning for retail product recognition and discusses potential techniques that can be helpful for the research of the topic. Next, we provide the details of public datasets which could be used for deep learning. Finally, we conclude the current progress and point new perspectives to the research of related fields.

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