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The technologies developed by the IDENTITY consortium throughout the project life is for civil and research purposes only.

1. Fabio Bacchini & Ludovica Lorusso, Race, Again. How Face Recognition Technology Reinforces Racial Discrimination, Journal of Information, Communication and Ethics in Society
2. Fabio Bacchini & Ludovica Lorusso, A Tattoo Is Not a Face. Ethical Aspects of Tattoo-based Biometrics, Journal of Information, Communication and Ethics in Society, 16, 2, 2018, pp. 110-122.
3. Fabio Bacchini & Ludovica Lorusso, Biometrica, Discriminazioni e Stile di Pensiero Razzista (Biometrics, Discrimination, and the Racist Style of Thought), Bioetica. Rivista Interdisciplinare, 2-3, 2017, pp. 247-270.
4. Nelson M茅ndez, Luis A. Bouza, Leonardo Chang, Heydi M茅ndez-V谩zquez:
   Efficient and Effective Face Frontalization for Face Recognition in the Wild. In Iberoamerican Conference on Pattern Recognition (CIARP 2017): 391-398
5. Fabiola Becerra-Riera, Annette Morales-Gonz谩lez, Heydi M茅ndez-V谩zquez:
   Exploring Local Deep Representations for Facial Gender Classification in Videos. In International Workshop on Artificial Intelligence and Pattern Recognition (IWAIPR 2018): 104-112
6. Mairelys Hern谩ndez-Dur谩n, Yenisel Plasencia Cala帽a, Heydi M茅ndez-V谩zquez:
   Low-Resolution Face Recognition with Deep Convolutional Features in the Dissimilarity Space. In International Workshop on Artificial Intelligence and Pattern Recognition (IWAIPR 2018): 95-103
7. Yoanna Mart铆nez-D铆az, Heydi M茅ndez-V谩zquez, Leyanis L贸pez-脕vila, Leonardo Chang, Enrique Sucar, Massimo Tistarelli: Toward More Realistic Face Recognition Evaluation in the YouTube Faces Database. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, pp. 413-421, Junio 2018, USA
8. Fabiola Becerra-Riera, Nelson M茅ndez Llanes, Annette Morales-Gonz谩lez, Heydi M茅ndez-V谩zquez and Massimo Tistarelli: On combining face local appearance and geometrical features for race classification. In Iberoamerican Conference on Pattern Recognition (CIARP 2018), Madrid, Espa帽a.
9. C.-C. Chang, C.-T. Li and Y. Shi, 鈥淩eversible Watermarking Based on Privacy Homomorphism,鈥� IEEE Access, 2018 (Accepted)
10. N. Jia, V. Sanchez, and C.-T. Li, "View-invariant Gait Recognition: A Feature Selection Solution," IET Biometrics, vol. 7, no. 4, pp. 287 – 295, July 2018
11. R. Li, C.-T. Li and Y. Guan "Inference of a Compact Representation of Sensor Fingerprint for Source Camera Identification," Pattern Recognition, vol. 74, no. 2, pp. 556 -567, 2018
12. F. Calderon, S. Bravo-Solorio, C.-T. Li, an A. K. Nandi, "Fast Fragile Watermark Embedding and Iterative Mechanism with High Self-Restoration Performance,鈥� Digital Signal Processing, vol. 73, pp. 83-92, Feb 2018
13. X. Yu, H. Tan, H. Liang, C.-T. Li, G. Liao, "A Multi-Task Learning CNN for Image Steganalysis," IEEE International Workshop on Information Forensics and Security (WIFS), Hong Kong, 11 -13 Dec 2018
14. Y. Guo, S. Lin, and C.-T. Li, 鈥淗omogeneous Feature Transfer and Heterogeneous Location Fine-tuning for Cross-City Property Appraisal Framework,鈥� in Proc. 16th Australian Data Mining Conference, Bathurst, Australia, 28-30 November, 2018
15. Y. Quan, X. Lin, and C.-T.Li, 鈥淧rovenance Analysis for Instagram Photos,鈥� in Proc. 16th Australian Data Mining Conference, Bathurst, Australia, 28-30 November, 2018
16. X. Lin and C.-T. Li, 鈥淩otation-invariant Binary Representation of Sensor Pattern Noise for Source-Oriented Image and Video Clustering,鈥� in Proc. 15th IEEE International Conference on Advanced Video and Signal-based Surveillance (AVSS), Auckland, New Zealand, 27-30 November 2018
17. C.-C. Chang and C.-T. Li, "Privacy-Preserving Reversible Watermarking for Data Exfiltration Prevention through Lexicographic Permutations,鈥� in Proc. 14th International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP), Sendai, Japan, 26 – 28 November 2018
18. R. Leyva, V. Sanchez, and C.-T. Li, " 'Detecting Small Objects in High resolution Images with Integral Fisher Score,"" in Proc. IEEE International Conference on Image Processing (ICIP), Athens, Greece, 7 - 10 October 2018
19. H. Wang, X. Wei, V. Sanchez, C.-T. Li, "Fusion Network for Face-based Age Estimation," in Proc. IEEE International Conference on Image Processing (ICIP), Athens, Greece, 7 - 10 October 2018
20. S. Ren, L. He, J. Li, Z. Chen, P. Jiang, and C.-T. Li, "Contention-aware Prediction for Performance Impact of Task Co-running in Multicore Computers," in Proc. 9th EAI International Conference on Big Data Technologies and Applications, Exeter, UK, 4-5 September 2018
21. S. Lin, C.-T. Li and A. Kot, 鈥淢ulti-task Mid-level Feature Alignment Network for Unsupervised Cross-Dataset Person Re-Identification鈥�, 29th British Machine Vision Conference, Newcastle, UK, 3 - 6 September, 2018
22. R. Caldelli, I. Amerini, C.-T. Li, "PRNU-based image classification of the origin social network with CNN," in Proc. The 26th European Signal Processing Conference (EUSIPCO 2018), Rome, Italy, 3 – 7 September 2018
23. R. Leyva, V. Sanchez, and C.-T. Li, "Fast Detection of Abnormal Events in Video with Binary Features," in Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Calgary, Canada, 15–20 April 2018
24. X. Guan and C.-T. Li, "Active Learning in Multi-Domain Collaborative Filtering Recommender Systems," in Proc. The 33rd ACM Symposium on Applied Computing, Pau, France, 9 – 13 April 2018
25. K. Nguyen, C. Fookes, S. Sridharan, M. Tistarelli, M. Nixon 鈥淪uper-resolution for biometrics: A comprehensive survey,鈥� Pattern Recognition 78:23-42, June 2018.
26. M. Nappi, S. Ricciardi, M. Tistarelli, 鈥淐ontext awareness in biometric systems and methods: State of the art and future scenarios,鈥� Image and Vision Computing 76 pp. 27-37, August 2018.
27. Yoanna Martinez-Diaz, Heydi Mendez-Vazquez, Leyanis Lopez-Avila, Leonardo Chang, L. Enrique Sucar, Massimo Tistarelli 鈥淭oward More Realistic Face Recognition Evaluation Protocols for the YouTube Faces Database,鈥� in Proc. of CVPR 2018 pp. 526-534, June 2018.
28. Souad Khellat-Khiel, Andrea Lagorio, Massimo Tistarelli, 鈥淔ace recognition 鈥渙n the move鈥� combining incomplete information,鈥� in Proc. of 2018 International Workshop on Biometrics and Forensics (IWBF), June 2018.

29. H. Zhu , Z. Gu, H. Zhao, K. Chen, C. Li, L. He, "Developing a Pattern Discovery Method in Time Series Data and its GPU Acceleration", BIG DATA MINING AND ANALYTICS, 2018

30. H. Zhu, L. He, S. Fu, R. Li, X. Han, Z. Fu, Y. Hu, C. Li, "WolfPath: Accelerating iterative traversing-based graph processing algorithms on GPU", International Journal of Parallel Programming, 2017

31. R. Leyva, V. Sanchez and C.-T. Li, "Video Anomaly Detection with Compact Feature Sets for Online Performance," IEEE Transactions on Image Processing, vol. 26, no. 7, pp. 3463 – 3478, July 2017
32. Wang, C. Chen, L. He, B. Gao, J Ren, Z. Fu, S. Fu, Y. Hu, C.-T. Li, "Modelling and developing conflict-aware scheduling on large-scale data centres," Future Generation Computer Systems
33. C.-C. Chang and C.-T. Li, "Secure Secret Sharing in the Cloud", in Proc. 19th IEEE International Symposium on Multimedia (ISM), 11 - 13 Dec 2017
34. N. Jia, C.-T. Li and V. Sanchez, "Learning Optimised Representation for View-invariant Gait Recognition," in Proc. IAPR/IEEE International Joint Conference on Biometrics (IJCB), Denver, USA, October 2017
35. S. Lin and C.-T. Li, 鈥淓nd-to-End Correspondence and Relationship Learning of Mid-Level Deep Features for Person Re-Identification," in Proc. The International Conference on Digital Image Computing: Techniques and Applications (DICTA'17), Sydney, Australia, 39 November - 1 December, 2017
36. R. Leyva, V. Sanchez, and C.-T. Li, "Abnormal Event detection in Videos using Binary Features," in Proc. 40th International Conference on Telecommunications and Signal Processing (TSP), July 2017, Barcelona, Spain
37. C.-C. Chang and C,-T. Li, "Reversible Data Hiding in JPEG Images Based on Adjustable Padding," in Proc. 5th International Workshop on Biometrics and Forensics, Coventry, UK, April 2017
38. N. Jia, V. Sanchez, C.-T. Li, A. Liew , "Fast and Robust Framework on View-invariant Gait Recognition," in Proc. 5th International Workshop on Biometrics and Forensics, Coventry, UK, April 2017
39. X. Yu, H. Liang, M. Li, and C.-T. Li, 鈥淎n adaptive tri-pixel unit steganographic algorithm using the least two significant bits,鈥� in Proc. 5th International Workshop on Biometrics and Forensics, Coventry, UK, April 2017
40. R. Leyva, V. Sanchez, and C.-T. Li, "The LV Dataset: a Realistic Surveillance Video Dataset for Abnormal Event Detection," in Proc. 5th International Workshop on Biometrics and Forensics, Coventry, UK, April 2017
41. Ruchaud, N., & Dugelay, J. L. (2017, July). ASePPI : prot茅ger la vie priv茅e tout en pr茅servant l鈥檜tilit茅 de la vid茅osurveillanc. GRETSI, September 2017.
42. Ruchaud, N., & Dugelay, J. L. (2017, July). AsePPI, an Adaptive Scrambling enabling Privacy Protection and Intelligibility in H.264/AVC. Eusipco, August 2017.
43. Ruchaud, N., & Dugelay, J. L. (2017, July). ASePPI: Robust Privacy Protection Against De-Anonymization Attacks. In Computer Vision and Pattern Recognition Workshops (CVPRW), 2017 IEEE Conference on (pp. 1352-1359). IEEE.
44. Ruchaud, N., & Dugelay, J. L. (2017, February). De-genderization by body contours reshaping. In Identity, Security and Behavior Analysis (ISBA), 2017 IEEE International Conference on (pp. 1-6). IEEE.
45. Ruchaud, N., & Dugelay, J. L. (2016, July). Privacy protecting, intelligibility preserving video surveillance. In Multimedia & Expo Workshops (ICMEW), 2016 IEEE International Conference on (pp. 1-6). IEEE.
46. Ruchaud, N., & Dugelay, J. L. (2016). Automatic Face Anonymization in Visual Data: Are we really well protected?. Electronic Imaging, 2016(15), 1-7.
47. Galdi, C., Nappi, M., & Dugelay, J. L. (2017, May). Secure User Authentication on Smartphones via Sensor and Face Recognition on Short Video Clips. In International Conference on Green, Pervasive, and Cloud Computing (pp. 15-22). Springer, Cham.
48. Galdi, C., & Dugelay, J. L. (2017). FIRE: Fast Iris REcognition on mobile phones by combining colour and texture features. Pattern Recognition Letters, 91, 44-51.
49. Galdi, C., Hartung, F., & Dugelay, J. L. (2017). Videos versus still images: Asymmetric sensor pattern noise comparison on mobile phones. Electronic Imaging, 2017(7), 100-103.
50. Galdi, C., & Dugelay, J. L. (2016, December). Fusing iris colour and texture information for fast iris recognition on mobile devices. In Pattern Recognition (ICPR), 2016 23rd International Conference on (pp. 160-164). IEEE.
51. Galdi, C., Nappi, M., & Dugelay, J. L. (2016). Multimodal authentication on smartphones: Combining iris and sensor recognition for a double check of user identity. Pattern Recognition Letters, 82, 144-153.
52. Sepas-Moghaddam, A., Chiesa, V., Correia, P. L., Pereira, F., & Dugelay, J. L. (2017, April). The IST-EURECOM Light Field Face Database. In Biometrics and Forensics (IWBF), 2017 5th International Workshop on (pp. 1-6). IEEE.
53. Chiesa, V., & Dugelay, J. L. (2016, September). Impact of multi-focused images on recognition of soft biometric traits. In Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series (Vol. 9971).
54. Akhtar, Z., Hadid, A., Nixon, M., Tistarelli, M., Dugelay, J. L., & Marcel, S. (2017). Biometrics: In Search of Identity and Security (Q & A). IEEE MultiMedia.
55. Gonzalez-Sosa, E., Dantcheva, A., Vera-Rodriguez, R., Dugelay, J. L., Br茅mond, F., & Fierrez, J. (2016, December). Image-based gender estimation from body and face across distances. In Pattern Recognition (ICPR), 2016 23rd International Conference on (pp. 3061-3066). IEEE.
56. Luca Debiasi, Andreas Uhl, 鈥淧RNU Enhancement Effects on Biometric Source Sensor Attribution鈥�, IET Biometrics 4:6, pp. 256-265, 2017
57. Thomas Bergm眉ller, Eleftherios Christopoulos, Kevin Fehrenbach, Martin Schn枚ll, Andreas Uhl, 鈥淩ecompression effects in iris recognition鈥�, Image and Vision Computing (Special Section on the Best of Biometrics 2015) 58, pp. 142-157, 2017
58. Peter Wild, Heinz Hofbauer, James Ferryman, Andreas Uhl, 鈥淨uality-based Iris Segmentation-level Fusion鈥�, EURASIP Journal on Information Security 2016:25, 2016
59. Heinz Hofbauer, Fernando Alonso-Fernandez, Josef Bigun, Andreas Uhl, 鈥淓xperimental Analysis Regarding the Influence of Iris Segmentation on the Recognition Rate鈥�, IET Biometrics 5:3, pp. 200-211, 2016
60. Aslan, A. Uhl, A. Meschtscherjakov, M. Tscheligi, 鈥淒esign and Exploration of Mid-air Authentication Gestures鈥�, ACM Transactions on Interactive Intelligent Systems 6:23, pp. 1-22, 2016
61. Christof Kauba, Andreas Uhl, 鈥淔ingerprint Recognition under the Influence of Sensor Ageing鈥�, IET Biometrics 4:6, pp. 254-255, 2016
62. Ehsaneddin Jalilian, Andreas Uhl, 鈥淚ris Segmentation Using Fully Convolutional Encoder--Decoder Networks鈥�, In Bir Bhanu, Ajay Kumar, editors, Deep Learning for Biometrics, pp. 133-155, (ZG) Switzerland, Springer, 2017
63. Luca Debiasi, Christof Kauba, Andreas Uhl, 鈥淚dentifying Iris Sensors from Iris Images鈥�, In Christian Rathgeb, Christoph Busch, editors, Iris and Periocular Biometric Recognition, pp. 359-382, London, UK, IET, 2017
64. Peter Wild, Heinz Hofbauer, James Ferryman, Andreas Uhl, 鈥淩obust Iris Image Segmentation鈥�, In Christian Rathgeb, Christoph Busch, editors, Iris and Periocular Biometrics, pp. 57-83, London, UK, IET, 2017
65. Veronika Haaf, Martin Neukamp, Jutta H盲mmerle-Uhl, Andreas Uhl, 鈥淩eal-World Non-NIR Illumination and Wavelength-Specific Acquisition Variants in Iris Recognition鈥�, In Proceedings of the International Conference on Vision, Image and Signal Processing (ICVISP 2017)Osaka, Japan, September 22 – 24
66. Eduardo Ribeiro, Andreas Uhl, Fernando Alonso-Fernandez, Reuben A. Farrugia, 鈥淓xploring Deep Learning Image Super-Resolution for Iris Recognition鈥�, In Proc. of the 25th European Signal Processing Conference (EUSIPCO 2017), Kos Island, Greece, August 28 - September 2, 2017
67. Simon Kirchgasser, Andreas Uhl, 鈥淭emplate Ageing in non-minutiae Fingerprint Recognition鈥�, In Proceedings of the International Workshop on Biometrics and Forensics (IWBF '17), pp. 1-6, Coventry, United Kingdom, April 4 – 5
68. Simon Kirchgasser, Andreas Uhl, 鈥淔ingerprint Template Ageing vs. Template Changes Revisited鈥�, In Proceedings of the International Conference of the Biometrics Special Interest Group (BIOSIG'17), pp. 1-12, Darmstadt, Germany, September 20 – 22
69. Ehsaneddin Jalilian, Andreas Uhl, Roland Kwitt, 鈥淒omain Adaptation for CNN Based Iris Segmentation鈥�, In Proceedings of the 16th International Conference of the Biometrics Special Interest Group (BIOSIG'17), pp. 51-60, Darmstadt, Germany, September 20 – 22
70. Martin Draschl, Jutta H盲mmerle-Uhl, Andreas Uhl, 鈥淪ensor Dependency in Efficient Fingerprint Image Protection using Selective JPEG2000 Encryption鈥�, In Proceedings of the 5th International Workshop on Biometrics and Forensics (IWBF'17), pp. 1-6, Coventry, United Kindom, April 4 - 5
71. P. Drozdowski, C. Rathgeb, H. Hofbauer, J. Wagner, A. Uhl, C. Busch, 鈥淭owards Pre-alignment of Near-infrared Iris Images鈥�, In Proceedings of the IAPR/IEEE International Joint Conference on Biometrics (IJCB'17), pp. 8, 2017
72. C. Kauba, L. Debiasi, A. Uhl, 鈥淚dentifying the Origin of Iris Images Based on Fusion of Local Image Descriptors and PRNU Based Techniques鈥�, In Proceedings of the IAPR/IEEE International Joint Conference on Biometrics (IJCB'17), pp. 294-301, Denver, Colorado, USA, October 1 - October 4
73. Simon Kirchgasser, Andreas Uhl, 鈥淭emplate Ageing and Quality Analysis in Time-Span separated Fingerprint Data鈥�, In Proceedings of the IEEE International Conference on Identity, Security and Behavior Analysis (ISBA '17), pp. 1-8, New Delhi, Indien, February 22 – 24
74. Amrit Pal Singh Bhogal, Dominik S枚llinger, Pauline Trung, Andreas Uhl, 鈥淣on-reference image quality assessment for biometric presentation attack detection鈥�, In Proceedings of the 5th International Workshop on Biometrics and Forensics (IWBF'17), pp. 1-6, Coventry, United Kindom, April 4 – 5
75. Amrit Pal Singh Bhogal, Dominik S枚llinger, Pauline Trung, Jutta H盲mmerle-Uhl, Andreas Uhl, 鈥淣on-reference image quality assessment for fingervein presentation attack detection鈥�, In Proceedings of 20th Scandinavian Conference on Image Analysis (SCIA'17), pp. 184-196, Springer Lecture Notes on Computer Science, 10269, 2017
76. C. Champod and M. Tistarelli (2017) 鈥淏iometric Technologies for Forensic Science and Policing: State of the
    Art鈥�, in: M. Tistarelli, C. Champod Ed.s Handbook of Biometrics for Forensic Science, Springer Verlag, pp. 1-15, Springer Verlag, February 2017.
77. M. Nappi, S Ricciardi, M Tistarelli (2017) 鈥淩eal Time 3D Face-Ear Recognition on
    Mobile Devices: New Scenarios for 3D Biometrics 鈥渋n-the-Wild鈥濃��, in: M. De
    Marsico, M. Nappi, H. Pedro Proen莽a (Ed.s) Human Recognition in Unconstrained
    Environments: Using Computer Vision, Pattern Recognition and Machine Learning
    Methods for Biometrics, pp. 55-76, Academic Press, 2017.
78. M.Tistarelli, R. Beveridge, P Flynn, M Nappi (2017) Special Issue on Best of
    Biometrics 2015, Guest editors' introduction, Image and Vision Computing, Vol. 58, pp 108-109, 2017.
79. H.Mendez Vazquez; F Becerra Riera; A Morales-Gonzalez, M. Tistarelli (2017) 鈥淎ge
    and Gender Classification using Local Appearance Descriptors from Facial
    Components鈥�, in Proc. IAPR/IEEE 3rd Int.l Joint Conference on
    Biometrics - IJCB 2017, pp. 1-7, Denver
    (CO) USA, IEEE Computer Society Press, October 2017.
80. C.-L. Li and X. Lin, "A Fast Source-Oriented Image Clustering Method for Digital Forensics," EURASIP Journal on Image and Video Processing (Accepted)
81. R.Li, C.-T. Li and Y. Guan "Inference of a Compact Representation of Sensor
    Fingerprint for Source Camera Identification," Pattern Recognition, 2017 (Accepted)
82. Lin and C.-T. Li, 鈥淟arge-Scale Image Clustering based on Camera Fingerprint,鈥� IEEE Transactions on Information Forensics and Security, vol. 12, no. 4, pp. 793-1808, April 2017
83. Antipov, S.-A. Berrani, and J.-L. Dugelay, 鈥淢inimalistic CNN-based ensemble model for gender prediction from face images,鈥� Pattern Recognition Letters, Vol.70, 15 January 2016
84. Gonzalez-Sosa, A. Dantcheva, R. Vera-Rodriguez, J.-L. Dugelay, F. Bremond, and J. Fierrez, 鈥淚mage-based gender estimation from body and face across distances,鈥� in Proc. 23rd International Conference on Pattern Recognition, Cancun, Mexico, December 4-8, 2016
85. Chiesa and J.-L. Dugelay, 鈥淚mpact of multi-focused images on recognition of soft biometric traits,鈥� SPIE Optical Engineering and Applications, San Diego, USA, 28 August-1 September 2016
86. Ruchaud and J.-L. Dugelay, 鈥淧rivacy protecting, intelligibility preserving video surveillance,鈥� IEEE International Conference on Multimedia and Expo, Seattle, USA, July 11-15, 2016
87. Ruchaud and J.-L. Dugelay, 鈥淎utomatic face anonymization in visual data: Are we really well protected?鈥� SPIE International Symposium on Electronic Imaging, San Francisco, USA, February14-18, 2016
88. Lin and C.-T. Li, 鈥淚mage Provenance Inference through Content-Based Device Fingerprint Analysis鈥�, in Computational Methods in Information Security: Algorithms, Technologies and Applications, ed. by A. I. Awad, N. Yen, and M. Fairhurst, Institution of Engineering and Technology (IET), 2017
89. Leyva, V. Sanchez, and C.-T. Li, 鈥淔ast Binary-Based Video Descriptors for Action Recognition,鈥� in Proc. The International Conference on Digital Image Computing: Techniques and Applications (DICTA鈥�16), Gold Coast, Australia, 30 November – 2 December, 2016
90. T. Nguyen, T. T. Nguyen, X. C. Pham, A. W.-C. Liew, Y. Hu, T. Liang, and C.-T. Li, 鈥淎 Novel Online Bayes Classifier,鈥� in Proc. The International Conference on Digital Image Computing: Techniques and Applications (DICTA鈥�16), Gold Coast, Australia, 30 November – 2 December, 2016
91. Sayyed-Ali HOSSAYNI, Mohammad-R RAJATI, Esteve DEL ACEBO, Diego REFORGIATO RECUPERO, Aldo GANGEMI, Mohammad-R AKBARZADEH-T and Josep Lluis DE LA ROSA I ESTEVA, Towards Interval Version of Fuzzy Synsets, International Conference of Artificial Intelligence of ACIA, 18, November 2016
92. Leyva, V. Sanchez, and C.-T. Li, 鈥淎 Fast Binary Pair-based Video Descriptor for Action Recognition,鈥� in Proc. IEEE International Conference on Image Processing (ICIP鈥�16), Phoenix, Arizona, USA, 25 – 28 September, 2016
93. Michele Nappi, Ricciardi and Massimo Tistarelli, 鈥�Deceiving faces: When plastic surgery challenges face recognition,鈥�: Image and Vision Computing, vol. 54, pp. 71 – 82, October 2016
94. Rauf, N. Jia, C. Song, Y. Huang, and L. Wang, 鈥淜nowledge Transfer Between Networks and Its Application on Gait Recognition鈥�, Digital Signal Processing (2016), International Conference on, October 2016.
95. Liang, C.-T. Li, Y. Guan and Y. Hu, 鈥淕ait Recognition based on the Golden Ratio,鈥� EURASIP Journal on Image and Video Processing, (2016) 2016: 22. doi:10.1186/s13640-016-0126-5, Dec 2016
96. Lin and C.-T. Li, 鈥淩efining PRNU-Based Detection of Image Forgeries,鈥� in Proc. The 1st IEEE Digital Media & Academic Forum, Santorini, Greece, 4 -6 July, 2016
97. Christian Rathgeb, Andreas Uhl, Peter Wild, Heinz Hofbauer, 鈥淒esign Decisions for an Iris Recognition SDK. In Kevin Bowyer, Mark J. Burge, editors, Handbook of Iris Recognition, Advances in Computer Vision and Pattern Recognition, Springer, 2016
98. Heinz Hofbauer, Andreas Uhl, 鈥淐alculating a boundary for the Significance from the Equal-Error Rate,鈥� In Proceedings of the 9th IAPR/IEEE International Conference on Biometrics (ICB'16), pp. 1-4, 2016
99. Victoria Ablinger, Cornelia Zenz, Jutta H盲mmerle-Uhl, Andreas Uhl, 鈥淐ompression Standards in Fingervein Recognition. In Proceedings of the 9th IAPR/IEEE International Conference on Biometrics (ICB'16), pp. 1-7, 2016
100. Heinz Hofbauer, Inmaculada Tomeo-Reyes, Andreas Uhl, 鈥淚solating Iris Template Ageing in a Semi-controlled Environment,鈥� In Proceedings of the International Conference of the Biometrics Special Interest Group (BIOSIG'16), pp. 8, Darmstadt, Germany, September 21 - 23, 2016
101. Martin Draschl, Jutta H盲mmerle-Uhl, Andreas Uhl, 鈥淎ssessment of Efficient Fingerprint Image Protection Principles using different Types of AFIS,鈥� In Proceedings of the 18th International Conference on Information and Communications Security (ICICS'16), pp. 241-253, Singapore, Springer LNCS, 9977, November 29th - December 2nd, 2016
102. Martin Draschl, Jutta H盲mmerle-Uhl, Andreas Uhl, 鈥� Efficient Fingerprint Image Protection Principles using Selective JPEG2000 Encryption,鈥� In Proceedings of the 1st Workshop on Sensing, Processing and Learning for Intelligent Machines (SPLINE 2016), pp. 1-6, Aalborg, Denmark, July 6 - July 8, 2016
103. Daniel Kocher, Stefan Schwarz, Andreas Uhl, 鈥淓mpirical Evaluation of LBP-Extension Features for Finger Vein Spoofing Detection,鈥� In Proceedings of
     the International Conference of the Biometrics Special Interest Group (BIOSIG'16), pp. 8, Darmstadt, Germany, September 21 - 23, 2016
104. Simon Kirchgasser, Andreas Uhl, 鈥淏iometric Menagerie in Time-Span separated Fingerprint Data,鈥� In Proceedings of the International Conference of the Biometrics Special Interest Group (BIOSIG'16), pp. 1-12, Darmstadt, Germany, September 21 - 23, 2016
105. Christof Kauba, Emanuela Piciucco, Emanuele Maiorana, Patrizio Campisi, Andreas Uhl, 鈥淎dvanced Variants of Feature Level Fusion for Finger Vein Recognition,鈥� In Proceedings of the International Conference of the Biometrics Special Interest Group (BIOSIG'16), pp. 1-12, Darmstadt, Germany, September 21 - 23, 2016
106. Christof Kauba, Andreas Uhl, 鈥淔ingerprint Recognition under the Influence of Sensor Ageing,鈥� In Proceedings of the 4th International Workshop on Biometrics and Forensics (IWBF'16), pp. 1-6, Limassol, Cyprus, March 3 - March 4, 2016
107. Christof Kauba, Andreas Uhl, 鈥淧RNU-Based Image Alignment for Defective Pixel Detection,鈥� In Proceedings of the IEEE Eighth International Conference on Biometrics: Theory, Applications, and Systems (BTAS2016), pp. 1-6, Niagara Falls, Buffalo, New York, USA, September 6 - September 9, 2016
108. Emanuela Piciucco, Emanuele Maiorana, Christof Kauba, Andreas Uhl, Patrizio Campisi, 鈥淐ancelable Biometrics for Finger Vein Recognition,鈥� In Proceedings of the 1st Workshop on Sensing, Processing and Learning for Intelligent Machines (SPLINE 2016), pp. 1-6, Aalborg, Denmark, July 6 - July 8, 2016
109. Christian Rathgeb, Heinz Hofbauer, Andreas Uhl, Christoph Busch, 鈥淭ripleA: Accelerated Accuracy-preserving Alignment for Iris-Codes,鈥� In Proceedings of the 9th IAPR/IEEE International Conference on Biometrics (ICB'16), pp. 1-8, 2016
110. Wei and C.-T. Li, 鈥淔ace Recognition Technologies for Evidential Evaluation of Video Traces,鈥� in Biometrics in Forensic Science, ed. by M. Tistarelli and C. Champod, Springer, 2016