Development of Intelligent Automatic Recognition System of Breadboard Function Circuit Based on Image Processing

2019 ◽  
Vol 08 (03) ◽  
pp. 35-40
Author(s):  
赛潮 鲁
Keyword(s):  
Image Processing ◽  
Recognition System ◽  
Automatic Recognition

scholarly journals Smart Care Using a DNN-Based Approach for Activities of Daily Living (ADL) Recognition

2020 ◽  
Vol 11 (1) ◽  
pp. 10
Author(s):  
Muchun Su ◽  
Diana Wahyu Hayati ◽  
Shaowu Tseng ◽  
Jiehhaur Chen ◽  
Hsihsien Wei
Keyword(s):  
Neural Network ◽  
Health Care ◽  
Activities Of Daily Living ◽  
Video Processing ◽  
Daily Living ◽  
Deep Neural Network ◽  
Recognition System ◽  
Automatic Recognition ◽  
Data Filtering ◽  
Accuracy Rate

Health care for independently living elders is more important than ever. Automatic recognition of their Activities of Daily Living (ADL) is the first step to solving the health care issues faced by seniors in an efficient way. The paper describes a Deep Neural Network (DNN)-based recognition system aimed at facilitating smart care, which combines ADL recognition, image/video processing, movement calculation, and DNN. An algorithm is developed for processing skeletal data, filtering noise, and pattern recognition for identification of the 10 most common ADL including standing, bending, squatting, sitting, eating, hand holding, hand raising, sitting plus drinking, standing plus drinking, and falling. The evaluation results show that this DNN-based system is suitable method for dealing with ADL recognition with an accuracy rate of over 95%. The findings support the feasibility of this system that is efficient enough for both practical and academic applications.

A compliant control method for disassembly of non-elastic parts using realised motion

Robotica ◽  
1995 ◽  
Vol 13 (6) ◽  
pp. 591-598 ◽  
Author(s):  
Yagmur Denizhan
Keyword(s):  
Control Method ◽  
Recognition System ◽  
Automatic Recognition ◽  
Human Operator ◽  
Control Methods ◽  
Compliant Control ◽  
On Line

SummaryIn disassembly tasks, due to the large variety of objects and the different positions and orientations in which they appear, the disassembly trajectories supplied on-line by a human operator or an automatic recognition system can contain large errors. The classical compliant control methods turn out to be insufficient to eliminate sticking which is due to these errors. This paper presents a compliant control method for disassembly of non-elastic parts in non-elastic environments which adopts the trajectories according to realised motion. In case of sticking a new direction of motion is searched for until the manipulated part is set into motion.

An Extensive Study on Currency Recognition System Using Image Processing

2018 ◽  
Author(s):  
Georgie V. Rajan ◽  
Dincy M. Panicker ◽  
Nisha Elizabeth Chacko ◽  
Jayalekshmi Mohan ◽  
V.K. Kavitha
Keyword(s):  
Image Processing ◽  
Recognition System ◽  
Extensive Study

scholarly journals Automatic Damaged Number Plate Recognition System In Image Processing

2019 ◽  
Vol 8 (6S2) ◽  
pp. 287-291
Keyword(s):  
Image Processing ◽  
Recognition System ◽  
Planning System ◽  
License Plate ◽  
Restricted Area ◽  
Proof Scheme ◽  
Optical Character ◽  
The Supreme Court ◽  
Security Control ◽  
Real Goal

The use of the NPR (Number Plate Recognition) is a structure expected to assist confirm the number tags of cars. This structure is anticipated to have the real goal of the security system. This structure is based on an image planning system. This scheme helps to distinguish between the number plates of the cars, to prepare them and to use the information taken care of for further methodology such as securing, empowering the car to pass or to expel the car. NPR is an image scheduling development that utilizes the number (license) plate to acknowledge the car. The goal is to structure a gainful altered attested vehicle unmistakable proof scheme by the use of car number plateThe system is carried out along the route of security control of a particularly restricted area, such as military areas or area around the finest public working settings, such as the Parliament, the Supreme Court, etc. First, the produced system receives a image of the car. The region of the vehicle number plate is evacuated using the picture division in the picture. The optical character affirmation method is used to confirm the character. The resulting information is then used to distinguish and record the information in the database. The structure is performed and impersonated in Python, and the execution is tried on a licensed image. It is seen from the outset that the produced structure acknowledges and sees the car amount vividly.

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