Innovative Region Convolutional Neural Network Algorithm for Object Identification
Abstract
:1. Introduction
2. Materials and Methods
2.1. Scientific Article Data
2.2. Selection of Literature
2.3. Methods and Systematic Data Analysis
- (1)
- Visualization of article data related to the relationship between the article and the appropriate word topic.
- (2)
- Mapping of the number of articles in each year (from 2011–2021) and providing general information. Intervention studies involving animals or humans, and other studies that require ethical approval, must list the authority that provided approval and the corresponding ethical approval code.
3. Results
3.1. Article Data Visualization
3.2. Object Identification with R-CNN, Fast R-CNN, Faster R-CNN, and Mask R-CNN
4. Discussion
4.1. Development of Object Identification Research
4.2. CNN Algorithm Development for Object Identification
4.3. Convolutional Neural Network Algorithm and Open Innovation Engineering
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Type | Keywords |
---|---|
I | Object Identification AND Ancient Manuscript AND R-CNN OR Region Convolutional Neural Network |
II | Keyword I OR Fast R-CNN |
III | Keyword II OR Faster R-CNN |
IV | Keyword III OR Mask R-CNN |
Keyword | I | II | III | IV |
---|---|---|---|---|
Science Direct | 24,739 | 21,163 | 942 | 943 |
Dimensions AI | 185,986 | 170,753 | 1516 | 18 |
Google Scholar | 34,500 | 23,500 | 2570 | 80 |
Filter | 1 | 2 | 3 | 4 |
---|---|---|---|---|
Science Direct | 242 | 143 | 21 | 3 |
Dimensions AI | 18 | 12 | 8 | 9 |
Google Scholar | 75 | 71 | 31 | 20 |
N | 335 | 226 | 60 | 32 |
CNN Model | Author | Approach Used | Objective | Result |
---|---|---|---|---|
R-CNN | [11,12] |
| Region selection | Effectively speeds up the processing time |
Fast R-CNN | [13] |
| Process acceleration | Faster than R-CNN |
Faster R-CNN | [14] | Identifying regional proposals is done with a separate network (RPN) | Process acceleration | Faster than Fast R-CNN |
Mask R-CNN | [10] |
|
| Can perform other tasks in the same framework |
No | Author | Titles | Research Object |
---|---|---|---|
1 | [23] | Image Processing for Historical Newspaper Archives |
|
2 | [24] | Combination of statistic and structural approach to scripts segmentation from line segmentation of Javanese manuscript image |
|
3 | [25] | Appraisal of localized binarization methods on Tamil palm-leaf manuscripts | Localized binary method for storing text information from digital Tamil manuscript images |
4 | [26] | Evaluating Ancient Sundanese Glyph Recognition using Convolutional Neural Network | CNN algorithm for pattern recognition of ancient Sundanese manuscript in lontar media |
5 | [5] | Benchmarking of document image analysis tasks for palm leaf manuscripts from Southeast Asia | Palm-leaf manuscript image analysis |
6 | [27] | Thai Handwritten Recognition on Text Block-Based from Thai Archive Manuscripts | Thai handwriting recognition using CNN |
7 | [28] | Historical Arabic Manuscripts Text Recognition Using Convolutional Neural Network | Arabic text recognition using CNN |
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Share and Cite
Permanasari, Y.; Ruchjana, B.N.; Hadi, S.; Rejito, J. Innovative Region Convolutional Neural Network Algorithm for Object Identification. J. Open Innov. Technol. Mark. Complex. 2022, 8, 182. https://doi.org/10.3390/joitmc8040182
Permanasari Y, Ruchjana BN, Hadi S, Rejito J. Innovative Region Convolutional Neural Network Algorithm for Object Identification. Journal of Open Innovation: Technology, Market, and Complexity. 2022; 8(4):182. https://doi.org/10.3390/joitmc8040182
Chicago/Turabian StylePermanasari, Yurika, Budi Nurani Ruchjana, Setiawan Hadi, and Juli Rejito. 2022. "Innovative Region Convolutional Neural Network Algorithm for Object Identification" Journal of Open Innovation: Technology, Market, and Complexity 8, no. 4: 182. https://doi.org/10.3390/joitmc8040182