Open Access
Issue |
MATEC Web Conf.
Volume 392, 2024
International Conference on Multidisciplinary Research and Sustainable Development (ICMED 2024)
|
|
---|---|---|
Article Number | 01069 | |
Number of page(s) | 10 | |
DOI | https://doi.org/10.1051/matecconf/202439201069 | |
Published online | 18 March 2024 |
- Vijaykumar, Patil N., and D. R. Ingle. “A Novel Approach to Predict Blood Group using Fingerprint Map Reading.” 2021 6th International Conference for Convergence in Technology (I2CT). IEEE, 2021. [Google Scholar]
- Patil, Vijaykumar, and D. R. Ingle. “An association between fingerprint patterns with blood group and lifestyle based diseases: a review.” Artificial intelligence review 54 (2021): 1803-1839. [CrossRef] [Google Scholar]
- Ali, Mouad MH, et al. “Fingerprint recognition for person identification and verification based on minutiae matching.” 2016 IEEE 6th international conference on advanced computing (IACC). IEEE, 2016. [Google Scholar]
- Alshehri, Helala, et al. “Cross-sensor fingerprint matching method based on orientation, gradient, and gabor-hog descriptors with score level fusion.” IEEE Access 6 (2018): 28951-28968. [CrossRef] [Google Scholar]
- Fayrouz, I. Noor Eldin, Noor Farida, and A. H. Irshad. “Relation between fingerprints and different blood groups.” Journal of forensic and legal medicine 19.1 (2012): 18-21. [CrossRef] [Google Scholar]
- Sandhu, Harpreet, et al. “Frequency and correlation of lip prints, fingerprints and ABO blood groups in population of Sriganganagar District, Rajasthan.” Acta medica academica 46.2 (2017). [Google Scholar]
- Pimenta, Sara, Graça Minas, and Filomena Soares. “Spectrophotometric approach for automatic human blood typing.” 2012 IEEE 2nd Portuguese Meeting in Bioengineering (ENBENG). IEEE, 2012. [Google Scholar]
- Fernandes, Jose, et al. “A complete blood typing device for automatic agglutination detection based on absorption spectrophotometry.” IEEE Transactions on Instrumentation and Measurement 64.1 (2014): 112-119. [Google Scholar]
- Saponara, Sergio, Abdussalam Elhanashi, and Qinghe Zheng. “Recreating fingerprint images by convolutional neural network autoencoder architecture.” IEEE Access 9 (2021): 147888-147899. [CrossRef] [Google Scholar]
- Ezeobiejesi, Jude, and Bir Bhanu. “Patch based latent fingerprint matching using deep learning.” 2018 25th IEEE International Conference on Image Processing (ICIP). IEEE, 2018. [Google Scholar]
- Shrein, John M. “Fingerprint classification using convolutional neural networks and ridge orientation images.” 2017 IEEE Symposium Series on Computational Intelligence (SSCI). IEEE, 2017. [Google Scholar]
- Li, Zihao, et al. “A novel fingerprint recognition method based on a Siamese neural network.” Journal of Intelligent Systems 31.1 (2022): 690-705. [CrossRef] [Google Scholar]
- Mondal, M., et al. “Blood Group Identification Based on Fingerprint by Using 2D Discrete Wavelet and Binary Transform.” Journal homepage: http://iieta.org/journals/mmc_a 80.2-4 (2019): 57-70. [Google Scholar]
- Ferraz, Ana. “Automatic system for determination of blood types using image processing techniques.” 2013 IEEE 3rd Portuguese meeting in bioengineering (ENBENG). IEEE, 2013. [Google Scholar]
- Pimenta, Sara, Filomena Soares, and Graça Minas. “Development of an automatic electronic system to human blood typing.” 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 2012. [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.