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ORCIDErik G. Learned-Miller
Erik Gundersen Miller – Erik G. Miller
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- affiliation: University of Massachusetts Amherst, USA
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2020 – today
- 2022
[i36]Pia Bideau, Erik G. Learned-Miller, Cordelia Schmid, Karteek Alahari:
The Right Spin: Learning Object Motion from Rotation-Compensated Flow Fields. CoRR abs/2203.00115 (2022)- [i35]Tejas Panambur, Deep Chakraborty, Melissa Meyer, Ralph Milliken, Erik G. Learned-Miller, Mario Parente:
Self-Supervised Learning to Guide Scientifically Relevant Categorization of Martian Terrain Images. CoRR abs/2204.09854 (2022) - 2021
- [j15]Alireza Sedghi, Lauren J. O'Donnell
, Tina Kapur, Erik G. Learned-Miller, Parvin Mousavi, William M. Wells III:
Image registration: Maximum likelihood, minimum entropy and deep learning. Medical Image Anal. 69: 101939 (2021) - [c90]Zitian Chen, Subhransu Maji, Erik G. Learned-Miller:
Shot in the Dark: Few-Shot Learning With No Base-Class Labels. CVPR Workshops 2021: 2668-2677 - [c89]Cheng Gu, Erik G. Learned-Miller, Daniel Sheldon, Guillermo Gallego, Pia Bideau:
The Spatio-Temporal Poisson Point Process: A Simple Model for the Alignment of Event Camera Data. ICCV 2021: 13475-13484 - [c88]My Phan, Philip Thomas, Erik G. Learned-Miller:
Towards Practical Mean Bounds for Small Samples. ICML 2021: 8567-8576 - [c87]Yash Chandak, Scott Niekum, Bruno C. da Silva, Erik G. Learned-Miller, Emma Brunskill, Philip S. Thomas:
Universal Off-Policy Evaluation. NeurIPS 2021: 27475-27490 - [c86]Chen Qu, Hamed Zamani, Liu Yang, W. Bruce Croft, Erik G. Learned-Miller:
Passage Retrieval for Outside-Knowledge Visual Question Answering. SIGIR 2021: 1753-1757 - [i34]Huaizu Jiang, Erik G. Learned-Miller:
DCVNet: Dilated Cost Volume Networks for Fast Optical Flow. CoRR abs/2103.17271 (2021) - [i33]Yash Chandak, Scott Niekum, Bruno Castro da Silva, Erik G. Learned-Miller, Emma Brunskill, Philip S. Thomas:
Universal Off-Policy Evaluation. CoRR abs/2104.12820 (2021) - [i32]Chen Qu, Hamed Zamani, Liu Yang, W. Bruce Croft, Erik G. Learned-Miller:
Passage Retrieval for Outside-Knowledge Visual Question Answering. CoRR abs/2105.03938 (2021) - [i31]Cheng Gu, Erik G. Learned-Miller, Daniel Sheldon, Guillermo Gallego, Pia Bideau:
The Spatio-Temporal Poisson Point Process: A Simple Model for the Alignment of Event Camera Data. CoRR abs/2106.06887 (2021) - [i30]Gopal Sharma, Bidya Dash, Matheus Gadelha, Aruni RoyChowdhury, Marios Loizou, Evangelos Kalogerakis, Liangliang Cao, Erik G. Learned-Miller, Rui Wang, Subhransu Maji:
SurFit: Learning to Fit Surfaces Improves Few Shot Learning on Point Clouds. CoRR abs/2112.13942 (2021) - 2020
- [c85]Colin Samplawski, Erik G. Learned-Miller, Heesung Kwon, Benjamin M. Marlin:
Zero-Shot Learning in the Presence of Hierarchically Coarsened Labels. CVPR Workshops 2020: 4015-4019 - [c84]Huaizu Jiang, Ishan Misra, Marcus Rohrbach, Erik G. Learned-Miller, Xinlei Chen:
In Defense of Grid Features for Visual Question Answering. CVPR 2020: 10264-10273 - [c83]Aruni RoyChowdhury, Xiang Yu, Kihyuk Sohn, Erik G. Learned-Miller, Manmohan Chandraker:
Improving Face Recognition by Clustering Unlabeled Faces in the Wild. ECCV (24) 2020: 119-136 - [c82]Matheus Gadelha, Aruni RoyChowdhury, Gopal Sharma, Evangelos Kalogerakis, Liangliang Cao, Erik G. Learned-Miller, Rui Wang, Subhransu Maji:
Label-Efficient Learning on Point Clouds Using Approximate Convex Decompositions. ECCV (10) 2020: 473-491 - [c81]Zhipeng Tang, Fabien Delattre, Pia Bideau, Mark D. Corner, Erik G. Learned-Miller:
C-14: assured timestamps for drone videos. MobiCom 2020: 39:1-39:13 - [i29]Huaizu Jiang, Ishan Misra, Marcus Rohrbach, Erik G. Learned-Miller, Xinlei Chen:
In Defense of Grid Features for Visual Question Answering. CoRR abs/2001.03615 (2020) - [i28]Matheus Gadelha, Aruni RoyChowdhury, Gopal Sharma, Evangelos Kalogerakis, Liangliang Cao, Erik G. Learned-Miller, Rui Wang, Subhransu Maji:
Label-Efficient Learning on Point Clouds using Approximate Convex Decompositions. CoRR abs/2003.13834 (2020) - [i27]Zitian Chen, Zhiqiang Shen, Jiahui Yu, Erik G. Learned-Miller:
Cross-Supervised Object Detection. CoRR abs/2006.15056 (2020) - [i26]Aruni RoyChowdhury, Xiang Yu, Kihyuk Sohn, Erik G. Learned-Miller, Manmohan Chandraker:
Improving Face Recognition by Clustering Unlabeled Faces in the Wild. CoRR abs/2007.06995 (2020) - [i25]Zitian Chen, Subhransu Maji, Erik G. Learned-Miller:
Shot in the Dark: Few-Shot Learning with No Base-Class Labels. CoRR abs/2010.02430 (2020) - [i24]Lijun Zhang, Xiao Liu, Erik G. Learned-Miller, Hui Guan:
SID-NISM: A Self-supervised Low-light Image Enhancement Framework. CoRR abs/2012.08707 (2020)
2010 – 2019
- 2019
- [j14]Keen Sung, Joydeep Biswas, Erik G. Learned-Miller, Brian Neil Levine, Marc Liberatore:
Server-Side Traffic Analysis Reveals Mobile Location Information over the Internet. IEEE Trans. Mob. Comput. 18(6): 1407-1418 (2019) - [c80]Ashish Singh, Hang Su, SouYoung Jin, Huaizu Jiang, Chetan Manjesh, Geng Luo, Ziwei He, Li Hong, Erik G. Learned-Miller, Rosie Cowell:
Half&Half: New Tasks and Benchmarks for Studying Visual Common Sense. CVPR Workshops 2019: 1-4 - [c79]Aruni RoyChowdhury, Prithvijit Chakrabarty, Ashish Singh, SouYoung Jin, Huaizu Jiang, Liangliang Cao, Erik G. Learned-Miller:
Automatic adaptation of object detectors to new domains using self-training. CVPR Workshops 2019: 22-32 - [c78]Aruni RoyChowdhury, Prithvijit Chakrabarty, Ashish Singh, SouYoung Jin, Huaizu Jiang, Liangliang Cao, Erik G. Learned-Miller:
Automatic Adaptation of Object Detectors to New Domains Using Self-Training. CVPR 2019: 780-790 - [c77]Hang Su, Varun Jampani, Deqing Sun, Orazio Gallo, Erik G. Learned-Miller, Jan Kautz:
Pixel-Adaptive Convolutional Neural Networks. CVPR 2019: 11166-11175 - [c76]Huaizu Jiang, Deqing Sun, Varun Jampani, Zhaoyang Lv, Erik G. Learned-Miller, Jan Kautz:
SENSE: A Shared Encoder Network for Scene-Flow Estimation. ICCV 2019: 3194-3203 - [c75]Philip S. Thomas, Erik G. Learned-Miller:
Concentration Inequalities for Conditional Value at Risk. ICML 2019: 6225-6233 - [i23]Marwan A. Mattar, Michael G. Ross, Erik G. Learned-Miller:
Nonparametric Curve Alignment. CoRR abs/1902.00626 (2019) - [i22]Colin Samplawski, Heesung Kwon, Erik G. Learned-Miller, Benjamin M. Marlin:
Integrating Propositional and Relational Label Side Information for Hierarchical Zero-Shot Image Classification. CoRR abs/1902.05492 (2019) - [i21]Hang Su, Varun Jampani, Deqing Sun, Orazio Gallo, Erik G. Learned-Miller, Jan Kautz:
Pixel-Adaptive Convolutional Neural Networks. CoRR abs/1904.05373 (2019) - [i20]Aruni RoyChowdhury, Prithvijit Chakrabarty, Ashish Singh, SouYoung Jin, Huaizu Jiang, Liangliang Cao, Erik G. Learned-Miller:
Automatic adaptation of object detectors to new domains using self-training. CoRR abs/1904.07305 (2019) - [i19]Erik G. Learned-Miller, Philip S. Thomas:
A New Confidence Interval for the Mean of a Bounded Random Variable. CoRR abs/1905.06208 (2019) - [i18]Huaizu Jiang, Deqing Sun, Varun Jampani, Zhaoyang Lv, Erik G. Learned-Miller, Jan Kautz:
SENSE: a Shared Encoder Network for Scene-flow Estimation. CoRR abs/1910.12361 (2019) - 2018
- [c74]Hamed Zamani, Mostafa Dehghani, W. Bruce Croft, Erik G. Learned-Miller, Jaap Kamps:
From Neural Re-Ranking to Neural Ranking: Learning a Sparse Representation for Inverted Indexing. CIKM 2018: 497-506 - [c73]Pia Bideau, Aruni RoyChowdhury, Rakesh R. Menon, Erik G. Learned-Miller:
The Best of Both Worlds: Combining CNNs and Geometric Constraints for Hierarchical Motion Segmentation. CVPR 2018: 508-517 - [c72]Huaizu Jiang, Deqing Sun, Varun Jampani, Ming-Hsuan Yang, Erik G. Learned-Miller, Jan Kautz:
Super SloMo: High Quality Estimation of Multiple Intermediate Frames for Video Interpolation. CVPR 2018: 9000-9008 - [c71]Huaizu Jiang, Gustav Larsson, Michael Maire, Greg Shakhnarovich, Erik G. Learned-Miller:
Self-Supervised Relative Depth Learning for Urban Scene Understanding. ECCV (11) 2018: 20-37 - [c70]SouYoung Jin, Aruni RoyChowdhury, Huaizu Jiang, Ashish Singh, Aditya Prasad, Deep Chakraborty, Erik G. Learned-Miller:
Unsupervised Hard Example Mining from Videos for Improved Object Detection. ECCV (13) 2018: 316-333 - [c69]Pia Bideau, Rakesh R. Menon, Erik G. Learned-Miller:
MoA-Net: Self-supervised Motion Segmentation. ECCV Workshops (6) 2018: 715-730 - [c68]Li Yang Ku, Jonathan Rogers, Philip Strawser, Julia Badger, Erik G. Learned-Miller, Rod Grupen:
A Framework for Dexterous Manipulation. IROS 2018: 4131-4138 - [c67]Li Yang Ku, Scott Jordan, Julia Badger, Erik G. Learned-Miller, Rod Grupen:
Learning to Use a Ratchet by Modeling Spatial Relations in Demonstrations. ISER 2018: 398-410 - [c66]Hamed R. Bonab, Hamed Zamani, Erik G. Learned-Miller, James Allan:
Citation Worthiness of Sentences in Scientific Reports. SIGIR 2018: 1061-1064 - [i17]SouYoung Jin, Aruni RoyChowdhury, Huaizu Jiang, Ashish Singh, Aditya Prasad, Deep Chakraborty, Erik G. Learned-Miller:
Unsupervised Hard Example Mining from Videos for Improved Object Detection. CoRR abs/1808.04285 (2018) - 2017
- [j13]Kristen Grauman, Erik G. Learned-Miller, Antonio Torralba, Andrew Zisserman:
Guest Editorial: Best of CVPR 2015. IEEE Trans. Pattern Anal. Mach. Intell. 39(4): 625-626 (2017) - [c65]Huaizu Jiang, Erik G. Learned-Miller:
Face Detection with the Faster R-CNN. FG 2017: 650-657 - [c64]Sou-Young Jin, Hang Su, Chris Stauffer, Erik G. Learned-Miller:
End-to-End Face Detection and Cast Grouping in Movies Using Erdös-Rényi Clustering. ICCV 2017: 5286-5295 - [c63]Li Yang Ku, Erik G. Learned-Miller, Roderic A. Grupen:
An aspect representation for object manipulation based on convolutional neural networks. ICRA 2017: 794-800 - [c62]Li Yang Ku, Erik G. Learned-Miller, Roderic A. Grupen:
Associating grasp configurations with hierarchical features in convolutional neural networks. IROS 2017: 2434-2441 - [c61]Haw-Shiuan Chang, Erik G. Learned-Miller, Andrew McCallum:
Active Bias: Training More Accurate Neural Networks by Emphasizing High Variance Samples. NIPS 2017: 1002-1012 - [i16]Haw-Shiuan Chang, Erik G. Learned-Miller, Andrew McCallum:
Active Bias: Training a More Accurate Neural Network by Emphasizing High Variance Samples. CoRR abs/1704.07433 (2017) - [i15]Sou-Young Jin, Hang Su, Chris Stauffer, Erik G. Learned-Miller:
End-to-end Face Detection and Cast Grouping in Movies Using Erdős-Rényi Clustering. CoRR abs/1709.02458 (2017) - [i14]Huaizu Jiang, Deqing Sun, Varun Jampani, Ming-Hsuan Yang, Erik G. Learned-Miller, Jan Kautz:
Super SloMo: High Quality Estimation of Multiple Intermediate Frames for Video Interpolation. CoRR abs/1712.00080 (2017) - [i13]Huaizu Jiang, Erik G. Learned-Miller, Gustav Larsson, Michael Maire, Greg Shakhnarovich:
Self-Supervised Depth Learning for Urban Scene Understanding. CoRR abs/1712.04850 (2017) - 2016
- [c60]Manolis Savva, Fisher Yu, Hao Su, Masaki Aono, Baoquan Chen, Daniel Cohen-Or, Weihong Deng, Hang Su, Song Bai, Xiang Bai, Noa Fish, Jiajie Han, Evangelos Kalogerakis, Erik G. Learned-Miller, Yangyan Li, Minghui Liao, Subhransu Maji, Atsushi Tatsuma, Yida Wang, Nanhai Zhang, Zhichao Zhou:
Large-Scale 3D Shape Retrieval from ShapeNet Core55. 3DOR@Eurographics 2016 - [c59]Aruni Roy Chowdhury, Daniel Sheldon, Subhransu Maji, Erik G. Learned-Miller:
Distinguishing Weather Phenomena from Bird Migration Patterns in Radar Imagery. CVPR Workshops 2016: 276-283 - [c58]Pia Bideau, Erik G. Learned-Miller:
It's Moving! A Probabilistic Model for Causal Motion Segmentation in Moving Camera Videos. ECCV (8) 2016: 433-449 - [c57]Aruni Roy Chowdhury, Tsung-Yu Lin, Subhransu Maji, Erik G. Learned-Miller:
One-to-many face recognition with bilinear CNNs. WACV 2016: 1-9 - [i12]Pia Bideau, Erik G. Learned-Miller:
It's Moving! A Probabilistic Model for Causal Motion Segmentation in Moving Camera Videos. CoRR abs/1604.00136 (2016) - [i11]Huaizu Jiang, Erik G. Learned-Miller:
Face Detection with the Faster R-CNN. CoRR abs/1606.03473 (2016) - [i10]Li Yang Ku, Erik G. Learned-Miller, Roderic A. Grupen:
Associating Grasping with Convolutional Neural Network Features. CoRR abs/1609.03947 (2016) - [i9]Pia Bideau, Erik G. Learned-Miller:
A Detailed Rubric for Motion Segmentation. CoRR abs/1610.10033 (2016) - 2015
- [c56]Li Yang Ku, Dirk Ruiken, Erik G. Learned-Miller, Roderic A. Grupen:
Error detection and surprise in stochastic robot actions. Humanoids 2015: 1096-1101 - [c55]Hang Su, Subhransu Maji, Evangelos Kalogerakis, Erik G. Learned-Miller:
Multi-view Convolutional Neural Networks for 3D Shape Recognition. ICCV 2015: 945-953 - [c54]Li Yang Ku, Erik G. Learned-Miller, Roderic A. Grupen:
Modeling Objects as Aspect Transition Graphs to Support Manipulation. ISRR (2) 2015: 127-143 - [i8]Hang Su, Subhransu Maji, Evangelos Kalogerakis, Erik G. Learned-Miller:
Multi-view Convolutional Neural Networks for 3D Shape Recognition. CoRR abs/1505.00880 (2015) - [i7]Aruni RoyChowdhury, Tsung-Yu Lin, Subhransu Maji, Erik G. Learned-Miller:
Face Identification with Bilinear CNNs. CoRR abs/1506.01342 (2015) - [i6]Manjunath Narayana, Allen R. Hanson, Erik G. Learned-Miller:
Coherent Motion Segmentation in Moving Camera Videos using Optical Flow Orientations. CoRR abs/1511.01619 (2015) - [i5]Manjunath Narayana, Allen R. Hanson, Erik G. Learned-Miller:
Background subtraction - separating the modeling and the inference. CoRR abs/1511.01627 (2015) - [i4]Manjunath Narayana, Allen R. Hanson, Erik G. Learned-Miller:
Background Modeling Using Adaptive Pixelwise Kernel Variances in a Hybrid Feature Space. CoRR abs/1511.01631 (2015) - 2014
- [j12]Manjunath Narayana, Allen R. Hanson, Erik G. Learned-Miller:
Background subtraction: separating the modeling and the inference. Mach. Vis. Appl. 25(5): 1163-1174 (2014) - [c53]Andrew Kae, Benjamin M. Marlin, Erik G. Learned-Miller:
The Shape-Time Random Field for Semantic Video Labeling. CVPR 2014: 272-279 - [c52]Laura Sevilla-Lara, Deqing Sun, Erik G. Learned-Miller, Michael J. Black:
Optical Flow Estimation with Channel Constancy. ECCV (1) 2014: 423-438 - [c51]Li Yang Ku, Shiraj Sen, Erik G. Learned-Miller, Roderic A. Grupen:
The Aspect Transition Graph: An Affordance-Based Model. ECCV Workshops (2) 2014: 459-465 - 2013
- [j11]Mastooreh Salajegheh, Yue Wang, Anxiao Jiang, Erik G. Learned-Miller, Kevin Fu:
Half-Wits: Software Techniques for Low-Voltage Probabilistic Storage on Microcontrollers with NOR Flash Memory. ACM Trans. Embed. Comput. Syst. 12(2s): 91:1-91:25 (2013) - [c50]Benjamin Mears, Laura Sevilla-Lara, Erik G. Learned-Miller:
Distribution Fields with Adaptive Kernels for Large Displacement Image Alignment. BMVC 2013 - [c49]Andrew Kae, Kihyuk Sohn, Honglak Lee, Erik G. Learned-Miller:
Augmenting CRFs with Boltzmann Machine Shape Priors for Image Labeling. CVPR 2013: 2019-2026 - [c48]Manjunath Narayana, Allen R. Hanson, Erik G. Learned-Miller:
Coherent Motion Segmentation in Moving Camera Videos Using Optical Flow Orientations. ICCV 2013: 1577-1584 - [c47]Yahan Zhou, Jacqueline L. Feild, Erik G. Learned-Miller, Rui Wang:
Scene Text Segmentation via Inverse Rendering. ICDAR 2013: 457-461 - [c46]Jacqueline L. Feild, Erik G. Learned-Miller:
Improving Open-Vocabulary Scene Text Recognition. ICDAR 2013: 604-608 - [c45]Jacqueline L. Feild, Erik G. Learned-Miller, David A. Smith:
Using a Probabilistic Syllable Model to Improve Scene Text Recognition. ICDAR 2013: 897-901 - [c44]Hamed Soroush, Keen Sung, Erik G. Learned-Miller, Brian Neil Levine, Marc Liberatore:
Turning Off GPS Is Not Enough: Cellular Location Leaks over the Internet. Privacy Enhancing Technologies 2013: 103-122 - 2012
- [j10]Gary B. Huang, Andrew Kae, Carl Doersch, Erik G. Learned-Miller:
Bounding the Probability of Error for High Precision Optical Character Recognition. J. Mach. Learn. Res. 13: 363-387 (2012) - [c43]Manjunath Narayana, Allen R. Hanson, Erik G. Learned-Miller:
Improvements in Joint Domain-Range Modeling for Background Subtraction. BMVC 2012: 1-11 - [c42]Laura Sevilla-Lara, Erik G. Learned-Miller:
Distribution fields for tracking. CVPR 2012: 1910-1917 - [c41]Manjunath Narayana, Allen R. Hanson, Erik G. Learned-Miller:
Background modeling using adaptive pixelwise kernel variances in a hybrid feature space. CVPR 2012: 2104-2111 - [c40]Gary B. Huang, Honglak Lee, Erik G. Learned-Miller:
Learning hierarchical representations for face verification with convolutional deep belief networks. CVPR 2012: 2518-2525 - [c39]Gary B. Huang, Marwan A. Mattar, Honglak Lee, Erik G. Learned-Miller:
Learning to Align from Scratch. NIPS 2012: 773-781 - [c38]Marwan A. Mattar, Allen R. Hanson, Erik G. Learned-Miller:
Unsupervised Joint Alignment and Clustering using Bayesian Nonparametrics. UAI 2012: 584-593 - [i3]Marwan A. Mattar, Allen R. Hanson, Erik G. Learned-Miller:
Unsupervised Joint Alignment and Clustering using Bayesian Nonparametrics. CoRR abs/1210.4892 (2012) - 2011
- [j9]Andrew Kae, David A. Smith, Erik G. Learned-Miller:
Learning on the fly: a font-free approach toward multilingual OCR. Int. J. Document Anal. Recognit. 14(3): 289-301 (2011) - [j8]Gang Hua, Ming-Hsuan Yang, Erik G. Learned-Miller, Yi Ma, Matthew A. Turk, David J. Kriegman, Thomas S. Huang:
Introduction to the Special Section on Real-World Face Recognition. IEEE Trans. Pattern Anal. Mach. Intell. 33(10): 1921-1924 (2011) - [c37]David L. Smith, Jacqueline L. Feild, Erik G. Learned-Miller:
Enforcing similarity constraints with integer programming for better scene text recognition. CVPR 2011: 73-80 - [c36]Vidit Jain, Erik G. Learned-Miller:
Online domain adaptation of a pre-trained cascade of classifiers. CVPR 2011: 577-584 - [c35]Mastooreh Salajegheh, Yue Wang, Kevin Fu, Anxiao Jiang, Erik G. Learned-Miller:
Exploiting Half-Wits: Smarter Storage for Low-Power Devices. FAST 2011: 47-60 - [c34]Robert J. Walls, Erik G. Learned-Miller, Brian Neil Levine:
Forensic Triage for Mobile Phones with DEC0DE. USENIX Security Symposium 2011 - 2010
- [c33]John Tuttle, Robert J. Walls, Erik G. Learned-Miller, Brian Neil Levine:
Reverse engineering for mobile systems forensics with Ares. Insider Threats@CCS 2010: 21-28 - [c32]Gary B. Huang, Erik G. Learned-Miller:
Learning class-specific image transformations with higher-order Boltzmann machines. CVPR Workshops 2010: 25-32 - [c31]Andrew Kae, Gary B. Huang, Carl Doersch, Erik G. Learned-Miller:
Improving state-of-the-art OCR through high-precision document-specific modeling. CVPR 2010: 1935-1942
2000 – 2009
- 2009
- [j7]Jerod J. Weinman, Erik G. Learned-Miller, Allen R. Hanson:
Scene Text Recognition Using Similarity and a Lexicon with Sparse Belief Propagation. IEEE Trans. Pattern Anal. Mach. Intell. 31(10): 1733-1746 (2009) - [c30]Marwan A. Mattar, Michael G. Ross, Erik G. Learned-Miller:
Nonparametric curve alignment. ICASSP 2009: 3457-3460 - [c29]Andrew Kae, Erik G. Learned-Miller:
Learning on the Fly: Font-Free Approaches to Difficult OCR Problems. ICDAR 2009: 571-575 - [i2]Andrew Kae, Gary B. Huang, Erik G. Learned-Miller:
Bounding the Probability of Error for High Precision Recognition. CoRR abs/0907.0418 (2009) - 2008
- [j6]Andras Ferencz, Erik G. Learned-Miller, Jitendra Malik:
Learning to Locate Informative Features for Visual Identification. Int. J. Comput. Vis. 77(1-3): 3-24 (2008) - [j5]Erik G. Learned-Miller, Joseph DeStefano:
A Probabilistic Upper Bound on Differential Entropy. IEEE Trans. Inf. Theory 54(11): 5223-5230 (2008) - [c28]Gary B. Huang, Manjunath Narayana, Erik G. Learned-Miller:
Towards unconstrained face recognition. CVPR Workshops 2008: 1-8 - [c27]Jerod J. Weinman, Erik G. Learned-Miller, Allen R. Hanson:
A discriminative semi-Markov model for robust scene text recognition. ICPR 2008: 1-5 - 2007
- [j4]Manjunatha Jagalur, Chris Pal, Erik G. Learned-Miller, R. Thomas Zoeller, David Kulp:
Analyzing in situ gene expression in the mouse brain with image registration, feature extraction and block clustering. BMC Bioinform. 8(S-10) (2007) - [c26]Gary B. Huang, Vidit Jain, Erik G. Learned-Miller:
Unsupervised Joint Alignment of Complex Images. ICCV 2007: 1-8 - [c25]Vidit Jain, Erik G. Learned-Miller, Andrew McCallum:
People-LDA: Anchoring Topics to People using Face Recognition. ICCV 2007: 1-8 - [c24]Gary B. Huang, Erik G. Learned-Miller, Andrew McCallum:
Cryptogram Decoding for OCR Using Numerization Strings. ICDAR 2007: 208-212 - [c23]Jerod J. Weinman, Erik G. Learned-Miller, Allen R. Hanson:
Fast Lexicon-Based Scene Text Recognition with Sparse Belief Propagation. ICDAR 2007: 979-983 - [c22]Michael L. Wick, Michael G. Ross, Erik G. Learned-Miller:
Context-Sensitive Error Correction: Using Topic Models to Improve OCR. ICDAR 2007: 1168-1172 - [c21]David Walker Duhon, Jerod J. Weinman, Erik G. Learned-Miller:
Techniques and Applications for Persistent Backgrounding in a Humanoid Torso Robot. ICRA 2007: 3034-3040 - 2006
- [j3]Erik G. Learned-Miller:
Data Driven Image Models through Continuous Joint Alignment. IEEE Trans. Pattern Anal. Mach. Intell. 28(2): 236-250 (2006) - [c20]Vidit Jain, Andras Ferencz, Erik G. Learned-Miller:
Discriminative Training of Hyper-feature Models for Object Identification. BMVC 2006: 357-366 - [c19]