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Aharon Bar-Hillel
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2020 – today
- 2024
- [j15]Faina Khoroshevsky, Kaining Zhou, Aharon Bar-Hillel, Ofer Hadar, Shimon Rachmilevitch, Jhonathan E. Ephrath, Naftali Lazarovitch, Yael Edan:
A CNN-based framework for estimation of root length, diameter, and color from in situ minirhizotron images. Comput. Electron. Agric. 227: 109457 (2024) - [j14]Shay Dekel, Yosi Keller
, Aharon Bar-Hillel
Deep Convolutional Tables: Deep Learning Without Convolutions. IEEE Trans. Neural Networks Learn. Syst. 35(10): 13658-13670 (2024) - 2023
- [j13]Hanan Mann, Aharon Bar-Hillel, Raffi Lev-Tzion, Shira Greenfeld, Revital Kariv, Natan Lederman, Eran Matz, Iris Dotan, Dan Turner, Boaz Lerner:
Medical concept embedding of real-valued electronic health records with application to inflammatory bowel disease. Artif. Intell. Medicine 145: 102684 (2023) - [j12]Yael Konforti
SIGN: Statistical Inference Graphs Based on Probabilistic Network Activity Interpretation. IEEE Trans. Pattern Anal. Mach. Intell. 45(3): 3783-3797 (2023) - [i6]Shay Dekel, Yosi Keller, Aharon Bar-Hillel:
Deep Convolutional Tables: Deep Learning without Convolutions. CoRR abs/2304.11706 (2023) - 2022
- [j11]Guy Farjon
Sparse Hierarchical Table Ensemble-A Deep Learning Alternative for Tabular Data. IEEE Access 10: 75376-75384 (2022) - 2021
- [j10]Omer Wosner, Guy Farjon, Aharon Bar-Hillel:
Object detection in agricultural contexts: A multiple resolution benchmark and comparison to human. Comput. Electron. Agric. 189: 106404 (2021) - [j9]Faina Khoroshevsky
Parts-per-Object Count in Agricultural Images: Solving Phenotyping Problems via a Single Deep Neural Network. Remote. Sens. 13(13): 2496 (2021) - [i5]Yael Konforti, Alon Shpigler, Boaz Lerner, Aharon Bar-Hillel:
Inference Graphs for CNN Interpretation. CoRR abs/2110.10568 (2021) - 2020
- [j8]Adar Vit, Guy Shani, Aharon Bar-Hillel:
Length phenotyping with interest point detection. Comput. Electron. Agric. 176: 105629 (2020) - [c33]Ron M. Hecht, Ariel Telpaz, Gila Kamhi, Omer Tsimhoni, Aharon Bar-Hillel, Naftali Tishby:
Modeling the Effect of Driver's Eye Gaze Pattern Under Workload: Gaussian Mixture Approach. CogSci 2020 - [c32]Yael Konforti, Alon Shpigler, Boaz Lerner, Aharon Bar-Hillel:
Inference Graphs for CNN Interpretation. ECCV (25) 2020: 69-84 - [c31]Faina Khoroshevsky
Phenotyping Problems of Parts-per-Object Count. ECCV Workshops (6) 2020: 261-278 - [c30]Omer Wosner, Guy Farjon, Faina Khoroshevsky
Detection in Agricultural Contexts: Are We Close to Human Level? ECCV Workshops (6) 2020: 375-390 - [i4]Dan Halbersberg, Aharon Bar-Hillel, Shon Mendelson, Daniel A. Koster, Lena Karol, Boaz Lerner:
Transfer Learning of Photometric Phenotypes in Agriculture Using Metadata. CoRR abs/2004.00303 (2020)
2010 – 2019
- 2019
- [j7]Ron M. Hecht
Information Constrained Control Analysis of Eye Gaze Distribution Under Workload. IEEE Trans. Hum. Mach. Syst. 49(6): 474-484 (2019) - [c29]Adar Vit, Guy Shani, Aharon Bar-Hillel
Length Phenotyping With Interest Point Detection. CVPR Workshops 2019: 2609-2618 - [c28]Ron M. Hecht, Ariel Telpaz, Gila Kamhi, Aharon Bar-Hillel, Naftali Tishby:
Information Constrained Control for Visual Detection of Important Areas. ICASSP 2019: 4080-4084 - [c27]Yuval Litvak, Armin Biess
Learning Pose Estimation for High-Precision Robotic Assembly Using Simulated Depth Images. ICRA 2019: 3521-3527 - 2018
- [c26]Yotam Itzhaky, Guy Farjon, Faina Khoroshevsky, Alon Shpigler, Aharon Bar-Hillel:
Leaf counting: Multiple scale regression and detection using deep CNNs. BMVC 2018: 328 - [c25]Atalya Waissman, Aharon Bar-Hillel
Input-Dependably Feature-Map Pruning. ICANN (1) 2018: 706-713 - [i3]Yuval Litvak, Armin Biess, Aharon Bar-Hillel:
Learning a High-Precision Robotic Assembly Task Using Pose Estimation from Simulated Depth Images. CoRR abs/1809.10699 (2018) - 2017
- [c24]Eyal Krupka, Kfir Karmon, Noam Bloom, Daniel Freedman, Ilya Gurvich, Aviv Hurvitz, Ido Leichter, Yoni Smolin, Yuval Tzairi, Alon Vinnikov, Aharon Bar-Hillel
Toward Realistic Hands Gesture Interface: Keeping it Simple for Developers and Machines. CHI 2017: 1887-1898 - 2016
- [i2]Aharon Bar-Hillel, Eyal Krupka, Noam Bloom:
Convolutional Tables Ensemble: classification in microseconds. CoRR abs/1602.04489 (2016) - 2015
- [j6]Shaul Oron, Aharon Bar-Hillel
Locally Orderless Tracking. Int. J. Comput. Vis. 111(2): 213-228 (2015) - [j5]Shaul Oron
Real-time tracking-with-detection for coping with viewpoint change. Mach. Vis. Appl. 26(4): 507-518 (2015) - [c23]Ron M. Hecht, Aharon Bar-Hillel, Stas Tiomkin, Hadar Levi, Omer Tsimhoni
Cognitive workload and vocabulary sparseness: theory and practice. INTERSPEECH 2015: 3394-3398 - 2014
- [j4]Aharon Bar-Hillel
Recent progress in road and lane detection: a survey. Mach. Vis. Appl. 25(3): 727-745 (2014) - [c22]Eyal Krupka, Alon Vinnikov, Ben Klein, Aharon Bar-Hillel, Daniel Freedman, Simon Stachniak:
Discriminative Ferns Ensemble for Hand Pose Recognition. CVPR 2014: 3670-3677 - [c21]Shaul Oron, Aharon Bar-Hillel, Shai Avidan:
Extended Lucas-Kanade Tracking. ECCV (5) 2014: 142-156 - 2013
- [j3]Ron M. Hecht, Elad Noor, Gil Dobry, Yaniv Zigel
Effective Model Representation by Information Bottleneck Principle. IEEE Trans. Speech Audio Process. 21(8): 1755-1759 (2013) - [c20]Dan Levi, Shai Silberstein, Aharon Bar-Hillel
Fast Multiple-Part Based Object Detection Using KD-Ferns. CVPR 2013: 947-954 - 2012
- [c19]Shaul Oron, Aharon Bar-Hillel
Locally Orderless Tracking. CVPR 2012: 1940-1947 - [c18]Yaniv Alon, Aharon Bar-Hillel
Off-vehicle evaluation of camera-based pedestrian detection. Intelligent Vehicles Symposium 2012: 352-358 - [c17]Hyunggi Cho, Paul E. Rybski, Aharon Bar-Hillel
Real-time pedestrian detection with deformable part models. Intelligent Vehicles Symposium 2012: 1035-1042 - 2011
- [c16]Aharon Bar-Hillel
Fusing visual and range imaging for object class recognition. ICCV 2011: 65-72 - 2010
- [c15]Aharon Bar-Hillel
Part-Based Feature Synthesis for Human Detection. ECCV (4) 2010: 127-142
2000 – 2009
- 2009
- [c14]Ran Gilad-Bachrach
Efficient human computation: the distributed labeling problem. KDD Workshop on Human Computation 2009: 70-76 - [i1]Ran Gilad-Bachrach, Aharon Bar-Hillel, Liat Ein-Dor:
Efficient Human Computation. CoRR abs/0903.1125 (2009) - 2008
- [j2]Aharon Bar-Hillel
Efficient Learning of Relational Object Class Models. Int. J. Comput. Vis. 77(1-3): 175-198 (2008) - 2007
- [c13]Aharon Bar-Hillel, Daphna Weinshall:
Learning distance function by coding similarity. ICML 2007: 65-72 - [c12]Aharon Bar-Hillel
Workstation capacity tuning using reinforcement learning. SC 2007: 32 - 2006
- [b1]Aharon Bar-Hillel:
Learning from weak representations using distance functions and generative models (למידה מיצוגים חלשים באמצעות פונקציות מרחק ומודלים גנרטיביים.). Hebrew University of Jerusalem, Israel, 2006 - [c11]Tomer Hertz
Learning a kernel function for classification with small training samples. ICML 2006: 401-408 - [c10]Aharon Bar-Hillel, Daphna Weinshall:
Subordinate class recognition using relational object models. NIPS 2006: 73-80 - 2005
- [j1]Aharon Bar-Hillel, Tomer Hertz, Noam Shental, Daphna Weinshall:
Learning a Mahalanobis Metric from Equivalence Constraints. J. Mach. Learn. Res. 6: 937-965 (2005) - [c9]Aharon Bar-Hillel
Object Class Recognition by Boosting a Part-Based Model. CVPR (1) 2005: 702-709 - [c8]Aharon Bar-Hillel, Tomer Hertz
Efficient Learning of Relational Object Class Models. ICCV 2005: 1762-1769 - 2004
- [c7]Tomer Hertz, Aharon Bar-Hillel, Daphna Weinshall:
Learning Distance Functions for Image Retrieval. CVPR (2) 2004: 570-577 - [c6]Tomer Hertz, Aharon Bar-Hillel, Daphna Weinshall:
Boosting margin based distance functions for clustering. ICML 2004 - [c5]Aharon Bar-Hillel, Adam Spiro, Eran Stark:
Spike Sorting: Bayesian Clustering of Non-Stationary Data. NIPS 2004: 105-112 - 2003
- [c4]Aharon Bar-Hillel, Daphna Weinshall:
Learning with Equivalence Constraints and the Relation to Multiclass Learning. COLT 2003: 640-654 - [c3]Tomer Hertz, Noam Shental, Aharon Bar-Hillel, Daphna Weinshall:
Enhancing Image and Video Retrieval: Learning via Equivalence Constraint. CVPR (2) 2003: 668-674 - [c2]Aharon Bar-Hillel, Tomer Hertz, Noam Shental, Daphna Weinshall:
Learning Distance Functions using Equivalence Relations. ICML 2003: 11-18 - [c1]Noam Shental, Aharon Bar-Hillel, Tomer Hertz, Daphna Weinshall:
Computing Gaussian Mixture Models with EM Using Equivalence Constraints. NIPS 2003: 465-472
Coauthor Index
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last updated on 2024-11-04 21:43 CET by the dblp team
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