轉載自：https://kiennguyenstuff.wordpress.com/2017/10/05/iris-recognition-papers-in-the-top-journals-in-2017/

Top journals:

– IEEE Transaction on Pattern Analysis and Machine Intelligence (PAMI)

– Pattern Recognition (PR)

– IEEE Transaction on Image Processing

– IEEE Transaction on Forensics and Security

– Pattern Recognition Letters (PRL)

– Computer Vision and Image Understanding (CVIU)

———————————————————————————————————–

2017 – Journals

1. Cancellable iris template generation based on Indexing-First-One hashing

Lai, Yen-Lung ; Jin, Zhe; Jin Teoh, Andrew Beng; Goi, Bok-Min; Yap, Wun-She; Chai, Tong-Yuen; Rathgeb, Christian?Source:?Pattern Recognition, v 64, p 105-117, April 1, 2017

2. Multi-patch deep sparse histograms for iris recognition in visible spectrum using collaborative subspace for robust verification

Raja, Kiran B. ; Raghavendra, R.; Venkatesh, Sushma; Busch, Christoph?Source:Pattern Recognition Letters, v 91, p 27-36, May 1, 2017

3. Results from MICHE II – Mobile Iris CHallenge Evaluation II

De Marsico, Maria ; Nappi, Michele; Proen?a, Hugo?Source:?Pattern Recognition Letters, v 91, p 3-10, May 1, 2017

4. Iris matching by means of Machine Learning paradigms: A new approach to dissimilarity computation

Aginako, Naiara; Echegaray, Goretti; Martínez-Otzeta, J.M.; Rodríguez, Igor; Lazkano, Elena; Sierra, Basilio?Source:?Pattern Recognition Letters, v 91, p 60-64, May 1, 2017

5. Optimal Generation of Iris Codes for Iris Recognition

Hu, Yang ; Sirlantzis, Konstantinos; Howells, Gareth?Source:?IEEE Transactions on Information Forensics and Security, v 12, n 1, p 157-171, January 2017

6. FIRE: Fast Iris REcognition on mobile phones by combining colour and texture features

Galdi, Chiara; Dugelay, Jean-Luc?Source:?Pattern Recognition Letters, v 91, p 44-51, May 1, 2017

7. Periocular and iris local descriptors for identity verification in mobile applications

Aginako, Naiara; Castrillón-Santana, Modesto; Lorenzo-Navarro, Javier; Martínez-Otzeta, José María; Sierra, Basilio?Source:?Pattern Recognition Letters, v 91, p 52-59, May 1, 2017

8. Kurtosis and skewness at pixel level as input for SOM networks to iris recognition on mobile devices

Abate, Andrea F.; Barra, Silvio; Gallo, Luigi; Narducci, Fabio?Source:?Pattern Recognition Letters, v 91, p 37-43, May 1, 2017

9. Toward more accurate iris recognition using cross-spectral matching

Nalla, Pattabhi Ramaiah; Kumar, Ajay?Source:?IEEE Transactions on Image Processing, v 26, n 1, p 208-221, January 2017

10. Combining iris and periocular biometric for matching visible spectrum eye images

Ahmed, Nasir Udin; Cvetkovic, Slobodan; Siddiqi, Erfanul Hoque; Nikiforov, Andrey; Nikiforov, Ilia?Source:?Pattern Recognition Letters, v 91, p 11-16, May 1, 2017

11. “Mobile Iris CHallenge Evaluation part II (MICHE II)”

De Marsico, Maria; Nappi, Michele; Proen?a, Hugo?Source:?Pattern Recognition Letters, v 91, p 1-2, May 1, 2017

12. Certain investigation on iris image recognition using hybrid approach of Fourier transform and Bernstein polynomials

Ramya, M.; Krishnaveni, V.; Sridharan, K.S.?Source:?Pattern Recognition Letters, v 94, p 154-162, July 15, 2017

13. A deep learning approach for iris sensor model identification

Marra, Francesco; Poggi, Giovanni; Sansone, Carlo; Verdoliva, Luisa?Source:?Pattern Recognition Letters, December 23, 2016 Article in Press

14. Long range iris recognition: A survey

Nguyen, Kien; Fookes, Clinton; Jillela, Raghavender; Sridharan, Sridha; Ross, Arun?Source:?Pattern Recognition, v 72, p 123-143, December 2017

15. Recognition of Image-Orientation-Based Iris Spoofing

Czajka, Adam; Bowyer, Kevin W.; Krumdick, Michael; Vidalmata, Rosaura G.?Source:IEEE Transactions on Information Forensics and Security, v 12, n 9, p 2184-2196, September 2017

16. A code-level approach to heterogeneous iris recognition

Liu, Nianfeng; Liu, Jing; Sun, Zhenan; Tan, Tieniu?Source:?IEEE Transactions on Information Forensics and Security, v 12, n 10, p 2373-2386, October 2017

?

總結

以上是生活随笔為你收集整理的Iris recognition papers in the top journals in 2017的全部內容，希望文章能夠幫你解決所遇到的問題。

如果覺得生活随笔網站內容還不錯，歡迎將生活随笔推薦給好友。