59 papers:
- POPL-2015-JungSSSTBD #concurrent #invariant #monad #named #orthogonal #reasoning
- Iris: Monoids and Invariants as an Orthogonal Basis for Concurrent Reasoning (RJ, DS, FS, KS, AT, LB, DD), pp. 637–650.
- ICEIS-v2-2014-ZhengJL #hybrid #learning #taxonomy #using
- Cross-Sensor Iris Matching using Patch-based Hybrid Dictionary Learning (BRZ, DYJ, YHL), pp. 169–174.
- ICPR-2014-FrucciGNRB #detection #mobile #named
- IDEM: Iris DEtection on Mobile Devices (MF, CG, MN, DR, GSdB), pp. 1752–1757.
- ICPR-2014-GuptaBVS #on the #using
- On Iris Spoofing Using Print Attack (PG, SB, MV, RS), pp. 1681–1686.
- ICPR-2014-HofbauerAWBU #segmentation
- A Ground Truth for Iris Segmentation (HH, FAF, PW, JB, AU), pp. 527–532.
- ICPR-2014-LeoMD #segmentation
- Highly Usable and Accurate Iris Segmentation (ML, TDM, CD), pp. 2489–2494.
- ICPR-2014-MatveevG #approximate #detection #segmentation
- Iris Segmentation System Based on Approximate Feature Detection with Subsequent Refinements (IM, KG), pp. 1704–1709.
- ICPR-2014-ZhaoTHTY #comparison #performance #segmentation
- A Performance Comparison between Circular and Spline-Based Methods for Iris Segmentation (YZ, CT, XH, AOT, RY), pp. 351–356.
- ICPR-2012-LiST #locality #using
- Accurate iris localization using contour segments (HL, ZS, TT), pp. 3398–3401.
- ICPR-2012-LiW #encoding #matrix #recognition #using
- Iris recognition using ordinal encoding of Log-Euclidean covariance matrices (PL, GW), pp. 2420–2423.
- ICPR-2012-TanK #identification #image
- Human identification from at-a-distance images by simultaneously exploiting iris and periocular features (CWT, AK), pp. 553–556.
- ICPR-2012-WangST #feature model #linear #programming #recognition #robust
- Robust regularized feature selection for iris recognition via linear programming (LW, ZS, TT), pp. 3358–3361.
- ICPR-2012-YanoZL #authentication #multimodal
- Multimodal biometric authentication based on iris pattern and pupil light reflex (VY, AZ, LLL), pp. 2857–2860.
- ICPR-2012-ZhangSTW #classification #image
- Iris image classification based on color information (HZ, ZS, TT, JW), pp. 3427–3430.
- SAC-2011-RathgebUW #recognition
- Shifting score fusion: on exploiting shifting variation in iris recognition (CR, AU, PW), pp. 3–7.
- ICPR-2010-KohGC #locality #robust #using
- A Robust Iris Localization Method Using an Active Contour Model and Hough Transform (JK, VG, VC), pp. 2852–2856.
- ICPR-2010-MarsicoNR #identification #named #segmentation
- IS_IS: Iris Segmentation for Identification Systems (MDM, MN, DR), pp. 2857–2860.
- ICPR-2010-OudaTN
- Tokenless Cancelable Biometrics Scheme for Protecting Iris Codes (OO, NT, TN), pp. 882–885.
- ICPR-2010-RathgebU #performance #recognition
- Attacking Iris Recognition: An Efficient Hill-Climbing Technique (CR, AU), pp. 1217–1220.
- ICPR-2010-RathgebU10a #database #generative
- Iris-Biometric Hash Generation for Biometric Database Indexing (CR, AU), pp. 2848–2851.
- ICPR-2010-RoySB #game studies #image #segmentation #using
- Segmentation of Unideal Iris Images Using Game Theory (KR, CYS, PB), pp. 2844–2847.
- ICPR-2010-SunderR #image #retrieval
- Iris Image Retrieval Based on Macro-features (MSS, AR), pp. 1318–1321.
- ICPR-2010-VatsaSRN #multi #recognition
- Quality-Based Fusion for Multichannel Iris Recognition (MV, RS, AR, AN), pp. 1314–1317.
- ICPR-2010-WoodardPMJR #on the
- On the Fusion of Periocular and Iris Biometrics in Non-ideal Imagery (DLW, SJP, PEM, RRJ, AR), pp. 201–204.
- ICPR-2010-ZhangST #identification
- Hierarchical Fusion of Face and Iris for Personal Identification (XZ, ZS, TT), pp. 217–220.
- ICPR-2010-ZhouK #identification #image #locality #using
- Personal Identification from Iris Images Using Localized Radon Transform (YZ, AK), pp. 2840–2843.
- KDD-2010-AdaB #composition #generative
- The new iris data: modular data generators (IA, MRB), pp. 413–422.
- SAC-2010-Hammerle-UhlRU #case study #recognition #robust
- Experimental study on the impact of robust watermarking on iris recognition accuracy (JHU, KR, AU), pp. 1479–1484.
- RE-2009-FailyF #requirements #risk management
- Context-Sensitive Requirements and Risk Management with IRIS (SF, IF), pp. 379–380.
- ICPR-2008-LiL #incremental #segmentation
- An incremental method for accurate iris segmentation (PL, XL), pp. 1–4.
- ICPR-v4-2006-ChouSCC #multi #recognition
- Iris Recognition with Multi-Scale Edge-Type Matching (CTC, SWS, WSC, VWC), pp. 545–548.
- ICPR-v4-2006-FengFDW #locality
- Iris Localization with Dual Coarse-to-fine Strategy (XF, CF, XD, YW), pp. 553–556.
- ICPR-v4-2006-HeCTW
- Key Techniques and Methods for Imaging Iris in Focus (YH, JC, TT, YW), pp. 557–561.
- ICPR-v4-2006-HeTS #locality
- Iris Localization via Pulling and Pushing (ZH, TT, ZS), pp. 366–369.
- ICPR-v4-2006-KongZK #precise #representation
- An Anatomy of IrisCode for Precise Phase Representation (AWKK, DZ, MK), pp. 429–432.
- ICPR-v4-2006-LiuX #recognition
- Iris Recognition Based on DLDA (CL, MX), pp. 489–492.
- ICPR-v4-2006-ProencaA #identification #image #normalisation
- A Method for the Identification of Noisy Regions in Normalized Iris Images (HP, LAA), pp. 405–408.
- ICPR-v4-2006-XuZM #automation #segmentation
- Automatic Iris Segmentation Based on Local Areas (GX, ZZ, YM), pp. 505–508.
- ICPR-v4-2006-YaoLYZL #algorithm #analysis #identification
- Analysis and Improvement of An Iris Identification Algorithm (PY, JL, XY, ZZ, BL), pp. 362–365.
- ICPR-v4-2006-YaoLYZL06a #algorithm #recognition #using
- Iris Recognition Algorithm Using Modified Log-Gabor Filters (PY, JL, XY, ZZ, BL), pp. 461–464.
- ICPR-v4-2006-ZaimQSIT #clustering #image #robust #segmentation #using
- A Robust and Accurate Segmentation of Iris Images Using Optimal Partitioning (AZ, MKQ, JS, JI, RT), pp. 578–581.
- MLDM-2005-CaoHXW #algorithm #network #recognition
- Iris Recognition Algorithm Based on Point Covering of High-Dimensional Space and Neural Network (WC, JH, GX, SW), pp. 305–313.
- ICPR-v2-2004-BollePCR
- Iris Individuality: A Partial Iris Model (RMB, SP, JHC, NKR), pp. 927–930.
- ICPR-v2-2004-SunWTC #estimation #recognition #robust
- Robust Direction Estimation of Gradient Vector Field for Iris Recognition (ZS, YW, TT, JC), pp. 783–786.
- ICPR-v3-2004-HuangWTC #recognition #segmentation
- A New Iris Segmentation Method for Recognition (JH, YW, TT, JC), pp. 554–557.
- ICPR-v4-2004-CuiWHTS #image #synthesis
- An Iris Image Synthesis Method Based on PCA and Super-Resolution (JC, YW, JH, TT, ZS), pp. 471–474.
- ICPR-v4-2004-KrichenMGD #identification #using
- Iris Identification Using Wavelet Packets (EK, MAM, SGS, BD), pp. 335–338.
- ICPR-v4-2004-SungLPL #bound #locality #recognition #using
- Iris Recognition Using Collarette Boundary Localization (HS, JL, JhP, YL), pp. 857–860.
- SIGMOD-2003-DeshpandeNGS03a #named
- IrisNet: Internet-scale Resource-Intensive Sensor Services (AD, SN, PBG, SS), p. 667.
- VLDB-2003-NathDKGKS #architecture #named
- IrisNet: An Architecture for Internet-scale Sensing Services (SN, AD, YK, PBG, BK, SS), pp. 1137–1140.
- ICPR-v2-2002-MaWT #recognition #symmetry #using
- Iris Recognition Using Circular Symmetric Filters (LM, YW, TT), pp. 414–417.
- ICPR-v2-2002-ToenniesBA #locality #realtime
- Feasibility of Hough-Transform-Based Iris Localisation for Real-Time-Application (KDT, FB, MA), pp. 1053–1056.
- SIGMOD-2000-HsuLG #image #information management #mining
- Image Mining in IRIS: Integrated Retinal Information System (WH, MLL, KGG), p. 593.
- ICPR-v2-2000-ZhuTW00a #identification
- Biometric Personal Identification Based on Iris Patterns (YZ, TT, YW), pp. 2801–2804.
- ICPR-v4-2000-DijkstraS #image #named #recognition
- IRIS — An Image Recognition and Interpretation System for the Dutch Postbank (ILD, NS), pp. 4023–4026.
- ICPR-1996-KobatakeM #adaptation #detection
- Adaptive filter to detect rounded convex regions: iris filter (HK, MM), pp. 340–344.
- OOPSLA-1993-Strauss #3d #tool support
- IRIS Inventor, A 3D Graphics Toolkit (PSS), pp. 192–200.
- SIGMOD-1990-KentLMW #database
- The Iris Database System (WK, PL, SM, WKW), p. 392.
- CAiSE-1990-VassiliouMKCMM #design #generative #named #requirements
- IRIS — A Mapping Assistant for Generating Designs from Requirements (YV, MM, PK, LC, MM, JM), pp. 307–338.