Name
Abstract | ||
|---|---|---|
Increasing pollution and changing life styles has severely affected human health specially our sense organs. More exposure to screen has increased vision related problems even at very early age of life. The developing technologies should be utilized to help the persons with no or very less vision to lead an independent life in society. Computer vision is one such field that can be utilized to develop some cost effective products that can be very useful for these scenarios. The detection and recognition of text from natural image can be very useful for visually imparted persons as well as in various other applications like developing a smart system to help driver in getting voice signal for every road sign, and even warning if we did not follow the one. The proposed work uses deep convolutional neural network to implement a text detection and recognition system that is much simpler and faster as compare to traditional hand crafted feature based methods. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/TENCON.2019.8929695 | TENCON IEEE Region 10 Conference Proceedings |
Keywords | Field | DocType |
Convolutional neural network,deep neural network | Increased vision,Smart system,Recognition system,Computer science,Convolutional neural network,Control engineering,Feature extraction,Human–computer interaction,Feature based,Text detection,Human health | Conference |
ISSN | Citations | PageRank |
2159-3442 | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rashmi Kapoor | 1 | 0 | 0.34 |
| M. Aruna Bharathi | 2 | 0 | 0.34 |
| M. Sushama | 3 | 0 | 0.34 |