Vineeth N. Balasubramanian

Orcid: 0000-0003-2656-0375

Affiliations:
  • Indian Institute of Technology, Hyderabad, Department of Computer Science and Engineering
  • Arizona State University, Tempe, Department of Computer Science and Engineering


According to our database1, Vineeth N. Balasubramanian authored at least 180 papers between 2006 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Explaining Deep Face Algorithms Through Visualization: A Survey.
IEEE Trans. Biom. Behav. Identity Sci., January, 2024

Advancing Ante-Hoc Explainable Models through Generative Adversarial Networks.
CoRR, 2024

Open-Set Object Detection By Aligning Known Class Representations.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

CARE: Counterfactual-based Algorithmic Recourse for Explainable Pose Correction.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

Interpretable Model Drift Detection.
Proceedings of the 7th Joint International Conference on Data Science & Management of Data (11th ACM IKDD CODS and 29th COMAD), 2024

Towards Learning and Explaining Indirect Causal Effects in Neural Networks.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

NESTER: An Adaptive Neurosymbolic Method for Causal Effect Estimation.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

Rethinking Robustness of Model Attributions.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Causal Inference Using LLM-Guided Discovery.
CoRR, 2023

Building a Winning Team: Selecting Source Model Ensembles using a Submodular Transferability Estimation Approach.
CoRR, 2023

Rethinking Counterfactual Data Augmentation Under Confounding.
CoRR, 2023

Δ-Networks for Efficient Model Patching.
CoRR, 2023

Learning Causal Attributions in Neural Networks: Beyond Direct Effects.
CoRR, 2023

Towards Estimating Transferability using Hard Subsets.
CoRR, 2023

ARUBA: An Architecture-Agnostic Balanced Loss for Aerial Object Detection.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

Learning Style Subspaces for Controllable Unpaired Domain Translation.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

MADG: Margin-based Adversarial Learning for Domain Generalization.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Mitigating the Effect of Incidental Correlations on Part-based Learning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Building a Winning Team: Selecting Source Model Ensembles using a Submodular Transferability Estimation Approach.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Data-Free Class-Incremental Hand Gesture Recognition.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

RetroKD : Leveraging Past States for Regularizing Targets in Teacher-Student Learning.
Proceedings of the 6th Joint International Conference on Data Science & Management of Data (10th ACM IKDD CODS and 28th COMAD), 2023

Fiducial Focus Augmentation for Facial Landmark Detection.
Proceedings of the 34th British Machine Vision Conference 2023, 2023

Weakly-supervised Spatially Grounded Concept Learner for Few-Shot Learning.
Proceedings of the 34th British Machine Vision Conference 2023, 2023

2022
Incremental Object Detection via Meta-Learning.
IEEE Trans. Pattern Anal. Mach. Intell., 2022

On the Robustness of Explanations of Deep Neural Network Models: A Survey.
CoRR, 2022

Estimating Treatment Effects using Neurosymbolic Program Synthesis.
CoRR, 2022

Counterfactual Generation Under Confounding.
CoRR, 2022

Learning Modular Structures That Generalize Out-of-Distribution.
CoRR, 2022

INDIGO: Intrinsic Multimodality for Domain Generalization.
CoRR, 2022

On Conditioning the Input Noise for Controlled Image Generation with Diffusion Models.
CoRR, 2022

Toward explainable deep learning.
Commun. ACM, 2022

Leveraging Test-Time Consensus Prediction for Robustness against Unseen Noise.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2022

FLUID: Few-Shot Self-Supervised Image Deraining.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2022

Data InStance Prior (DISP) in Generative Adversarial Networks.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2022

COCOA: Context-Conditional Adaptation for Recognizing Unseen Classes in Unseen Domains.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2022

To miss-attend is to misalign! Residual Self-Attentive Feature Alignment for Adapting Object Detectors.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2022

Multi-Domain Incremental Learning for Semantic Segmentation.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2022

Evaluating and Mitigating Bias in Image Classifiers: A Causal Perspective Using Counterfactuals.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2022

ETL: Efficient Transfer Learning for Face Tasks.
Proceedings of the 17th International Joint Conference on Computer Vision, 2022

New Objects on the Road? No Problem, We'll Learn Them Too.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2022

Matching Learned Causal Effects of Neural Networks with Domain Priors.
Proceedings of the International Conference on Machine Learning, 2022

Novel Class Discovery Without Forgetting.
Proceedings of the Computer Vision, 2022

Distilling the Undistillable: Learning from a Nasty Teacher.
Proceedings of the Computer Vision - ECCV 2022, 2022

Class-Incremental Learning with Cross-Space Clustering and Controlled Transfer.
Proceedings of the Computer Vision - ECCV 2022, 2022

Unseen Classes at a Later Time? No Problem.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Proto2Proto: Can you recognize the car, the way I do?
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Spacing Loss for Discovering Novel Categories.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022

Energy-based Latent Aligner for Incremental Learning.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Pose Tutor: An Explainable System for Pose Correction in the Wild.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022

A Framework for Learning Ante-hoc Explainable Models via Concepts.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Universalization of Any Adversarial Attack using Very Few Test Examples.
Proceedings of the CODS-COMAD 2022: 5th Joint International Conference on Data Science & Management of Data (9th ACM IKDD CODS and 27th COMAD), Bangalore, India, January 8, 2022

Improving Attribution Methods by Learning Submodular Functions.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

On Causally Disentangled Representations.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

Learning Modular Structures That Generalize Out-of-Distribution (Student Abstract).
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
Canonical Saliency Maps: Decoding Deep Face Models.
IEEE Trans. Biom. Behav. Identity Sci., 2021

On the benefits of defining vicinal distributions in latent space.
Pattern Recognit. Lett., 2021

Causal Regularization Using Domain Priors.
CoRR, 2021

Get Fooled for the Right Reason: Improving Adversarial Robustness through a Teacher-guided Curriculum Learning Approach.
CoRR, 2021

Inducing Semantic Grouping of Latent Concepts for Explanations: An Ante-Hoc Approach.
CoRR, 2021

Context-Conditional Adaptation for Recognizing Unseen Classes in Unseen Domains.
CoRR, 2021

Learn from Anywhere: Rethinking Generalized Zero-Shot Learning with Limited Supervision.
CoRR, 2021

Improving Attribution Methods by Learning Submodular Functions.
CoRR, 2021

Two-Level Adversarial Visual-Semantic Coupling for Generalized Zero-shot Learning.
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2021

On Challenges in Unsupervised Domain Generalization.
Proceedings of the NeurIPS 2021 Workshop on Pre-Registration in Machine Learning, 2021

Adversarial Robustness without Adversarial Training: A Teacher-Guided Curriculum Learning Approach.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Can we have it all? On the Trade-off between Spatial and Adversarial Robustness of Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Feature generation for long-tail classification.
Proceedings of the ICVGIP '21: Indian Conference on Computer Vision, Graphics and Image Processing, Jodhpur, India, December 19, 2021

Teaching GANs to sketch in vector format.
Proceedings of the ICVGIP '21: Indian Conference on Computer Vision, Graphics and Image Processing, Jodhpur, India, December 19, 2021

On Adversarial Robustness: A Neural Architecture Search perspective.
Proceedings of the IEEE/CVF International Conference on Computer Vision Workshops, 2021

Instance-Wise Causal Feature Selection for Model Interpretation.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2021

Towards Open World Object Detection.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Beyond VQA: Generating Multi-Word Answers and Rationales to Visual Questions.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2021

Towards Label-Free Few-Shot Learning: How Far Can We Go?
Proceedings of the Computer Vision and Image Processing - 6th International Conference, 2021

Structured Latent Embeddings for Recognizing Unseen Classes in Unseen Domains.
Proceedings of the 32nd British Machine Vision Conference 2021, 2021

Enhanced Regularizers for Attributional Robustness.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

A Deeper Look at the Hessian Eigenspectrum of Deep Neural Networks and its Applications to Regularization.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
DANTE: Deep alternations for training neural networks.
Neural Networks, 2020

Foreword: special issue for the journal track of the 12th Asian conference on machine learning (ACML 2020).
Mach. Learn., 2020

Few Shot Learning With No Labels.
CoRR, 2020

Data Instance Prior for Transfer Learning in GANs.
CoRR, 2020

Beyond VQA: Generating Multi-word Answer and Rationale to Visual Questions.
CoRR, 2020

Assisting Scene Graph Generation with Self-Supervision.
CoRR, 2020

An Empirical Study on the Robustness of NAS based Architectures.
CoRR, 2020

Enhancing Generalized Zero-Shot Learning via Adversarial Visual-Semantic Interaction.
CoRR, 2020

Computer Vision with Deep Learning for Plant Phenotyping in Agriculture: A Survey.
CoRR, 2020

Generative Adversarial Data Programming.
CoRR, 2020

Incremental Object Detection via Meta-Learning.
CoRR, 2020

VarMixup: Exploiting the Latent Space for Robust Training and Inference.
CoRR, 2020

Munich to Dubai: How far is it for Semantic Segmentationƒ.
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2020

Charting the Right Manifold: Manifold Mixup for Few-shot Learning.
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2020

A Little Fog for a Large Turn.
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2020

A Multi-Space Approach to Zero-Shot Object Detection.
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2020

On Initial Pools for Deep Active Learning.
Proceedings of the NeurIPS 2020 Workshop on Pre-registration in Machine Learning, 2020

On Saliency Maps and Adversarial Robustness.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2020

Meta-Consolidation for Continual Learning.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Retrospective Loss: Looking Back to Improve Training of Deep Neural Networks.
Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

STM-GAN: Sequentially Trained Multiple Generators for Mitigating Mode Collapse.
Proceedings of the Neural Information Processing - 27th International Conference, 2020

Attributional Robustness Training Using Input-Gradient Spatial Alignment.
Proceedings of the Computer Vision - ECCV 2020, 2020

Towards Fine-grained Sampling for Active Learning in Object Detection.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Human-Machine Collaboration for Face Recognition.
Proceedings of the CoDS-COMAD 2020: 7th ACM IKDD CoDS and 25th COMAD, 2020

Spatial Feedback Learning to Improve Semantic Segmentation in Hot Weather.
Proceedings of the 31st British Machine Vision Conference 2020, 2020

Zero-Shot Domain Generalization.
Proceedings of the 31st British Machine Vision Conference 2020, 2020

2019
On the Benefits of Attributional Robustness.
CoRR, 2019

Active Learning with Weak Supervision for Cost-Effective Panicle Detection in Cereal Crops.
CoRR, 2019

Automatic estimation of heading date of paddy rice using deep learning.
CoRR, 2019

DANTE: Deep AlterNations for Training nEural networks.
CoRR, 2019

Low-Cost Transfer Learning of Face Tasks.
CoRR, 2019

Region-based active learning for efficient labeling in semantic segmentation.
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2019

C4Synth: Cross-Caption Cycle-Consistent Text-to-Image Synthesis.
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2019

Harnessing the Vulnerability of Latent Layers in Adversarially Trained Models.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Submodular Batch Selection for Training Deep Neural Networks.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Neural Network Attributions: A Causal Perspective.
Proceedings of the 36th International Conference on Machine Learning, 2019

AdvGAN++: Harnessing Latent Layers for Adversary Generation.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision Workshops, 2019

Zero-Shot Task Transfer.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

Borrow From Anywhere: Pseudo Multi-Modal Object Detection in Thermal Imagery.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2019

An Adaptive Supervision Framework for Active Learning in Object Detection.
Proceedings of the 30th British Machine Vision Conference 2019, 2019

2018
Improving multiclass classification by deep networks using DAGSVM and Triplet Loss.
Pattern Recognit. Lett., 2018

MASON: A Model AgnoStic ObjectNess Framework.
CoRR, 2018

On the Analysis of Trajectories of Gradient Descent in the Optimization of Deep Neural Networks.
CoRR, 2018

Fast Dawid-Skene.
CoRR, 2018

Grad-CAM++: Generalized Gradient-Based Visual Explanations for Deep Convolutional Networks.
Proceedings of the 2018 IEEE Winter Conference on Applications of Computer Vision, 2018

VisDrone-DET2018: The Vision Meets Drone Object Detection in Image Challenge Results.
Proceedings of the Computer Vision - ECCV 2018 Workshops, 2018

RefocusGAN: Scene Refocusing Using a Single Image.
Proceedings of the Computer Vision - ECCV 2018, 2018

MASON: A Model AgnoStic ObjectNess Framework.
Proceedings of the Computer Vision - ECCV 2018 Workshops, 2018

Adversarial Data Programming: Using GANs to Relax the Bottleneck of Curated Labeled Data.
Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

<i>ADINE</i>: an adaptive momentum method for stochastic gradient descent.
Proceedings of the ACM India Joint International Conference on Data Science and Management of Data, 2018

Are saddles good enough for neural networks.
Proceedings of the ACM India Joint International Conference on Data Science and Management of Data, 2018

STwalk: learning trajectory representations in temporal graphs.
Proceedings of the ACM India Joint International Conference on Data Science and Management of Data, 2018

Neuro-IoU: Learning a Surrogate Loss for Semantic Segmentation.
Proceedings of the British Machine Vision Conference 2018, 2018

2017
ADINE: An Adaptive Momentum Method for Stochastic Gradient Descent.
CoRR, 2017

Are Saddles Good Enough for Deep Learning?
CoRR, 2017

Sync-DRAW: Automatic Video Generation using Deep Recurrent Attentive Architectures.
Proceedings of the 2017 ACM on Multimedia Conference, 2017

Have i reached the intersection: A deep learning-based approach for intersection detection from monocular cameras.
Proceedings of the 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2017

Attentive Semantic Video Generation Using Captions.
Proceedings of the IEEE International Conference on Computer Vision, 2017

Sequence-to-Sequence Learning for Human Pose Correction in Videos.
Proceedings of the 4th IAPR Asian Conference on Pattern Recognition, 2017

2016
Deep Model Compression: Distilling Knowledge from Noisy Teachers.
CoRR, 2016

Community-based Outlier Detection for Edge-attributed Graphs.
CoRR, 2016

Sync-DRAW: Automatic GIF Generation using Deep Recurrent Attentive Architectures.
CoRR, 2016

DAISEE: Dataset for Affective States in E-Learning Environments.
CoRR, 2016

Fine-tuning human pose estimations in videos.
Proceedings of the 2016 IEEE Winter Conference on Applications of Computer Vision, 2016

A crowdsourced approach to student engagement recognition in e-learning environments.
Proceedings of the 2016 IEEE Winter Conference on Applications of Computer Vision, 2016

2015
Adaptive Batch Mode Active Learning.
IEEE Trans. Neural Networks Learn. Syst., 2015

Active Batch Selection via Convex Relaxations with Guaranteed Solution Bounds.
IEEE Trans. Pattern Anal. Mach. Intell., 2015

Conformal predictions for information fusion - A comparative study of p-value combination methods.
Ann. Math. Artif. Intell., 2015

Model Selection Using Efficiency of Conformal Predictors.
Proceedings of the Statistical Learning and Data Sciences - Third International Symposium, 2015

BatchRank: A Novel Batch Mode Active Learning Framework for Hierarchical Classification.
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

Scaling Up the Training of Deep CNNs for Human Action Recognition.
Proceedings of the 2015 IEEE International Parallel and Distributed Processing Symposium Workshop, 2015

Similarity-based Contrastive Divergence Methods for Energy-based Deep Learning Models.
Proceedings of The 7th Asian Conference on Machine Learning, 2015

2013
Generalized batch mode active learning for face-based biometric recognition.
Pattern Recognit., 2013

PyCP: An Open-Source Conformal Predictions Toolkit.
Proceedings of the Artificial Intelligence Applications and Innovations, 2013

Multiresolution Match Kernels for gesture video classification.
Proceedings of the 2013 IEEE International Conference on Multimedia and Expo Workshops, 2013

Detection of changes in human affect dimensions using an Adaptive Temporal Topic model.
Proceedings of the 2013 IEEE International Conference on Multimedia and Expo, 2013

Latent Facial Topics for affect analysis.
Proceedings of the 2013 IEEE International Conference on Multimedia and Expo Workshops, 2013

Active Matrix Completion.
Proceedings of the 2013 IEEE 13th International Conference on Data Mining, 2013

2012
A novel online Variance Based Instance Selection (VBIS) method for efficient atypicality detection in chest radiographs.
Proceedings of the Medical Imaging 2012: Image Processing, 2012

A novel semi-transductive learning framework for efficient atypicality detection in chest radiographs.
Proceedings of the Medical Imaging 2012: Computer-Aided Diagnosis, 2012

Efficient atypicality detection in chest radiographs.
Proceedings of the 11th International Conference on Information Science, 2012

Batch Mode Active Learning for Multimedia Pattern Recognition.
Proceedings of the 2012 IEEE International Symposium on Multimedia, 2012

2011
Optimal batch selection for active learning in multi-label classification.
Proceedings of the 19th International Conference on Multimedia 2011, Scottsdale, AZ, USA, November 28, 2011

Optimization-Based Domain Adaptation towards Person-Adaptive Classification Models.
Proceedings of the 10th International Conference on Machine Learning and Applications and Workshops, 2011

Active Batch Selection for Fuzzy Classification in Facial Expression Recognition.
Proceedings of the 10th International Conference on Machine Learning and Applications and Workshops, 2011

Dynamic batch mode active learning.
Proceedings of the 24th IEEE Conference on Computer Vision and Pattern Recognition, 2011

Dynamic Batch Mode Active Learning via L1 Regularization.
Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence, 2011

2010
Conformal Predictions in Multimedia Pattern Recognition.
PhD thesis, 2010

Enriching social situational awareness in remote interactions: insights and inspirations from disability focused research.
Proceedings of the 18th International Conference on Multimedia 2010, 2010

What catches a radiologist's eye? A comprehensive comparison of feature types for saliency prediction.
Proceedings of the Medical Imaging 2010: Computer-Aided Diagnosis, 2010


Dynamic Batch Size Selection for Batch Mode Active Learning in Biometrics.
Proceedings of the Ninth International Conference on Machine Learning and Applications, 2010

Kernel Learning for Efficiency Maximization in the Conformal Predictions Framework.
Proceedings of the Ninth International Conference on Machine Learning and Applications, 2010

Learning from summaries of videos: Applying batch mode active learning to face-based biometrics.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2010

2009
Generalized Query by Transduction for online active learning.
Proceedings of the 12th IEEE International Conference on Computer Vision Workshops, 2009

Predicting risk of complications following a drug eluting stent procedure: A SVM approach for imbalanced data.
Proceedings of the Twenty-Second IEEE International Symposium on Computer-Based Medical Systems, 2009

2008
Person-Independent Head Pose Estimation Using Biased Manifold Embedding.
EURASIP J. Adv. Signal Process., 2008

Enriched human-centered multimedia computing through inspirations from disabilities and deficit-centered computing solutions.
Proceedings of the 3rd ACM Workshop on Human-Centered Computing, 2008

Multiple cue integration in transductive confidence machines for head pose classification.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2008

A wearable wireless RFID system for accessible shopping environments.
Proceedings of the 3rd International ICST Conference on Body Area Networks, 2008

2007
Biased manifold embedding for person-independent head pose estimation.
Proceedings of the VISAPP 2007: Proceedings of the Second International Conference on Computer Vision Theory and Applications, Barcelona, Spain, March 8-11, 2007, 2007

Biased Manifold Embedding: Supervised Isomap for Person-Independent Head Pose Estimation.
Proceedings of the Computer Vision and Computer Graphics. Theory and Applications, 2007

Biased Manifold Embedding: A Framework for Person-Independent Head Pose Estimation.
Proceedings of the 2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2007), 2007

2006
Measuring movement expertise in surgical tasks.
Proceedings of the 14th ACM International Conference on Multimedia, 2006


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