Global Postal Automation

2021 ◽  
pp. 135-154
Author(s):  
Aimee Vachon ◽  
Leslie Ordonez ◽  
Jorge Ramón Fonseca Cacho
Keyword(s):  
Postal Automation

Computer Vision and robotics in postal automation

1999 ◽  
Vol 18 (3-4) ◽  
pp. 265-273
Author(s):  
Giovanni B. Garibotto
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Pattern Recognition ◽  
Material Handling ◽  
State Of The Art ◽  
Short Description ◽  
The Other ◽  
Functional Requirements ◽  
Postal Automation ◽  
And Robotics

The paper is intended to provide an overview of advanced robotic technologies within the context of Postal Automation services. The main functional requirements of the application are briefly referred, as well as the state of the art and new emerging solutions. Image Processing and Pattern Recognition have always played a fundamental role in Address Interpretation and Mail sorting and the new challenging objective is now off-line handwritten cursive recognition, in order to be able to handle all kind of addresses in a uniform way. On the other hand, advanced electromechanical and robotic solutions are extremely important to solve the problems of mail storage, transportation and distribution, as well as for material handling and logistics. Finally a short description of new services of Postal Automation is referred, by considering new emerging services of hybrid mail and paper to electronic conversion.

Postal Automation System in Gurmukhi Script using Deep Learning

2021 ◽  
Author(s):  
Sandhya Sharma ◽  
Sheifali Gupta ◽  
Neeraj Kumar ◽  
Tanvi Arora
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Holistic Approach ◽  
North India ◽  
Automation System ◽  
Official Language ◽  
Major Research ◽  
Research Areas ◽  
Postal Automation ◽  
Gurmukhi Script

Nowadays in the era of automation, the postal automation system is one of the major research areas. Developing a postal automation system for a nation like India is much troublesome than other nations because of India’s multi-script and multi-lingual behavior. This proposed work will be helpful in the postal automation of district names of Punjab (state) written in Gurmukhi script, which is the official language of the state in North India. For this, a holistic approach i.e. a segmentation-free technique has been used with the help of Convolutional Neural Network (CNN) and Deep learning (DL). For the purpose of recognition, a database of 22[Formula: see text]000 images (samples) which are handwritten in Gurmukhi script for all the 22 districts of Punjab is prepared. Each sample is written two times by 500 different writers generating 1000 samples for each district name. Two CNN models are proposed which are named as ConvNetGuru and ConvNetGuruMod for the purpose of recognition. Maximum validation accuracy achieved by ConvNetGuru is 90% and ConvNetGuruMod is 98%.

The New Field Theory: An Application to Postal Automation

1964 ◽  
Vol 6 (5) ◽  
pp. 517-522 ◽  
Author(s):  
James J. Asher ◽  
Richard I. Post
Keyword(s):  
Field Theory ◽  
Decision Making ◽  
Experimental Research ◽  
Theoretical Models ◽  
Complex Problem ◽  
Computer Processing ◽  
The Future ◽  
Engineering Psychology ◽  
Postal Automation

To solve complex human problems such as those usually found in engineering psychology, theoretical models should function as heuristic stimulant for the invention of solution possibilities. These solutions were called stimulus fields which when invented then suggest many hypotheses testable with experiments. The exploration of the invented system with experimental research is necessary because most of the process or variance within the system is unknown, but discoverable. This schema of neo-field theory was illustrated with a complex problem of mail encoding by postal operators. The problem was concerned with informational decision-making by postal operators who in the future may encode mail for computer processing.

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