Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021

Vecnet: A Spectral and Multi-Scale Spatial Fusion Deep Network for Pixel-Level Cloud Type Classification in Himawari-8 Imagery.

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[DOI]

Zhaoqing Wang

Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2021

Towards Defending against Adversarial Examples via Attack-Invariant Features.

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[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

Class2Simi: A Noise Reduction Perspective on Learning with Noisy Labels.

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[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

Provably End-to-end Label-noise Learning without Anchor Points.

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[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

Maximum Mean Discrepancy Test is Aware of Adversarial Attacks.

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[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

Learning Diverse-Structured Networks for Adversarial Robustness.

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[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

Confidence Scores Make Instance-dependent Label-noise Learning Possible.

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[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

Robust early-learning: Hindering the memorization of noisy labels.

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[DOI]

Proceedings of the 9th International Conference on Learning Representations, 2021

Boosting Fairness for Masked Face Recognition.

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[DOI]

Proceedings of the IEEE/CVF International Conference on Computer Vision Workshops, 2021

Removing Adversarial Noise in Class Activation Feature Space.

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[DOI]

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Me-Momentum: Extracting Hard Confident Examples from Noisily Labeled Data.

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[DOI]

Yingbin Bai

Tongliang Liu

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

A Second-Order Approach to Learning With Instance-Dependent Label Noise.

[BibT_eX]

[DOI]

Zhaowei Zhu

Tongliang Liu

Yang Liu

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Revisiting Knowledge Distillation: An Inheritance and Exploration Framework.

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[DOI]

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

A Machine Learning Approach for Predicting Human Preference for Graph Layouts<sup>*</sup>.

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[DOI]

Proceedings of the 14th IEEE Pacific Visualization Symposium, 2021

Learning with Group Noise.

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[DOI]

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Tackling Instance-Dependent Label Noise via a Universal Probabilistic Model.

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[DOI]

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Harnessing Side Information for Classification Under Label Noise.

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[DOI]

IEEE Trans. Neural Networks Learn. Syst., 2020

Why ResNet Works? Residuals Generalize.

[BibT_eX]

[DOI]

Fengxiang He

Tongliang Liu

Dacheng Tao

IEEE Trans. Neural Networks Learn. Syst., 2020

Two-Stream Deep Hashing With Class-Specific Centers for Supervised Image Search.

[BibT_eX]

[DOI]

IEEE Trans. Neural Networks Learn. Syst., 2020

Towards Efficient Front-End Visual Sensing for Digital Retina: A Model-Centric Paradigm.

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[DOI]

IEEE Trans. Multim., 2020

Group Feedback Capsule Network.

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[DOI]

IEEE Trans. Image Process., 2020

Adversarial Examples for Hamming Space Search.

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[DOI]

IEEE Trans. Cybern., 2020

Multiple Kernel $k$k-Means with Incomplete Kernels.

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[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., 2020

Absent Multiple Kernel Learning Algorithms.

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[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., 2020

COVID-MTL: Multitask Learning with Shift3D and Random-weighted Loss for Automated Diagnosis and Severity Assessment of COVID-19.

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[DOI]

CoRR, 2020

Extended T: Learning with Mixed Closed-set and Open-set Noisy Labels.

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[DOI]

CoRR, 2020

A Survey of Label-noise Representation Learning: Past, Present and Future.

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[DOI]

CoRR, 2020

Maximum Mean Discrepancy is Aware of Adversarial Attacks.

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[DOI]

CoRR, 2020

Experimental Quantum Generative Adversarial Networks for Image Generation.

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[DOI]

CoRR, 2020

Weakly Supervised Temporal Action Localization with Segment-Level Labels.

[BibT_eX]

[DOI]

CoRR, 2020

Parts-dependent Label Noise: Towards Instance-dependent Label Noise.

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[DOI]

CoRR, 2020

Class2Simi: A New Perspective on Learning with Label Noise.

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[DOI]

CoRR, 2020

Repulsive Mixture Models of Exponential Family PCA for Clustering.

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[DOI]

CoRR, 2020

Quantum noise protects quantum classifiers against adversaries.

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[DOI]

CoRR, 2020

Multi-Class Classification from Noisy-Similarity-Labeled Data.

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[DOI]

CoRR, 2020

Towards Mixture Proportion Estimation without Irreducibility.

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[DOI]

CoRR, 2020

Domain Generalization via Entropy Regularization.

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[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Dual T: Reducing Estimation Error for Transition Matrix in Label-noise Learning.

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[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Part-dependent Label Noise: Towards Instance-dependent Label Noise.

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[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Deep Heterogeneous Multi-Task Metric Learning for Visual Recognition and Retrieval.

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[DOI]

Proceedings of the MM '20: The 28th ACM International Conference on Multimedia, 2020

Dual-Path Distillation: A Unified Framework to Improve Black-Box Attacks.

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[DOI]

Proceedings of the 37th International Conference on Machine Learning, 2020

Label-Noise Robust Domain Adaptation.

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[DOI]

Proceedings of the 37th International Conference on Machine Learning, 2020

LTF: A Label Transformation Framework for Correcting Label Shift.

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[DOI]

Proceedings of the 37th International Conference on Machine Learning, 2020

Learning with Bounded Instance and Label-dependent Label Noise.

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[DOI]

Jiacheng Cheng

Tongliang Liu

Kotagiri Ramamohanarao

Dacheng Tao

Proceedings of the 37th International Conference on Machine Learning, 2020

Sub-center ArcFace: Boosting Face Recognition by Large-Scale Noisy Web Faces.

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[DOI]

Proceedings of the Computer Vision - ECCV 2020, 2020

Generative-Discriminative Complementary Learning.

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[DOI]

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Diversified Bayesian Nonnegative Matrix Factorization.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Eigenfunction-Based Multitask Learning in a Reproducing Kernel Hilbert Space.

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[DOI]

IEEE Trans. Neural Networks Learn. Syst., 2019

Large-Margin Label-Calibrated Support Vector Machines for Positive and Unlabeled Learning.

[BibT_eX]

[DOI]

IEEE Trans. Neural Networks Learn. Syst., 2019

Adaptive Morphological Reconstruction for Seeded Image Segmentation.

[BibT_eX]

[DOI]

IEEE Trans. Image Process., 2019

Unsupervised Semantic-Preserving Adversarial Hashing for Image Search.

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[DOI]

IEEE Trans. Image Process., 2019

Transferring Knowledge Fragments for Learning Distance Metric from a Heterogeneous Domain.

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[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., 2019

Truncated Cauchy Non-Negative Matrix Factorization.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., 2019

Advances in data representation and learning for pattern analysis.

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[DOI]

Neurocomputing, 2019

Where is the Bottleneck of Adversarial Learning with Unlabeled Data?

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[DOI]

CoRR, 2019

A Quantum-inspired Algorithm for General Minimum Conical Hull Problems.

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[DOI]

CoRR, 2019

Multi-View Matrix Completion for Multi-Label Image Classification.

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[DOI]

CoRR, 2019

On Better Exploring and Exploiting Task Relationships in Multi-Task Learning: Joint Model and Feature Learning.

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[DOI]

CoRR, 2019

Robust Angular Local Descriptor Learning.

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[DOI]

CoRR, 2019

Are Anchor Points Really Indispensable in Label-Noise Learning?

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[DOI]

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Control Batch Size and Learning Rate to Generalize Well: Theoretical and Empirical Evidence.

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[DOI]

Fengxiang He

Tongliang Liu

Dacheng Tao

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Skipping Two Layers in ResNet Makes the Generalization Gap Smaller than Skipping One or No Layer.

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[DOI]

Yasutaka Furusho

Tongliang Liu

Kazushi Ikeda

Proceedings of the Recent Advances in Big Data and Deep Learning, 2019

Positive and Unlabeled Learning with Label Disambiguation.

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[DOI]

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Towards Digital Retina in Smart Cities: A Model Generation, Utilization and Communication Paradigm.

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[DOI]

Proceedings of the IEEE International Conference on Multimedia and Expo, 2019

DistillHash: Unsupervised Deep Hashing by Distilling Data Pairs.

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2018

Multiclass Learning With Partially Corrupted Labels.

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[DOI]

Ruxin Wang

Tongliang Liu

Dacheng Tao

IEEE Trans. Neural Networks Learn. Syst., 2018

Continuous Dropout.

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[DOI]

IEEE Trans. Neural Networks Learn. Syst., 2018

On Better Exploring and Exploiting Task Relationships in Multitask Learning: Joint Model and Feature Learning.

[BibT_eX]

[DOI]

IEEE Trans. Neural Networks Learn. Syst., 2018

Supervised Discrete Hashing With Relaxation.

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[DOI]

IEEE Trans. Neural Networks Learn. Syst., 2018

Deep Blur Mapping: Exploiting High-Level Semantics by Deep Neural Networks.

[BibT_eX]

[DOI]

IEEE Trans. Image Process., 2018

A Regularization Approach for Instance-Based Superset Label Learning.

[BibT_eX]

[DOI]

IEEE Trans. Cybern., 2018

Fast Supervised Discrete Hashing.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., 2018

An Optimal Transport View on Generalization.

[BibT_eX]

[DOI]

Jingwei Zhang

Tongliang Liu

Dacheng Tao

CoRR, 2018

The Expressive Power of Parameterized Quantum Circuits.

[BibT_eX]

[DOI]

CoRR, 2018

Implementable Quantum Classifier for Nonlinear Data.

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[DOI]

CoRR, 2018

Instance-Dependent PU Learning by Bayesian Optimal Relabeling.

[BibT_eX]

[DOI]

CoRR, 2018

Domain Generalization via Conditional Invariant Representation.

[BibT_eX]

[DOI]

CoRR, 2018

An Information-Theoretic View for Deep Learning.

[BibT_eX]

[DOI]

Jingwei Zhang

Tongliang Liu

Dacheng Tao

CoRR, 2018

Semantic Structure-based Unsupervised Deep Hashing.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Online Heterogeneous Transfer Metric Learning.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Quantum Divide-and-Conquer Anchoring for Separable Non-negative Matrix Factorization.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Learning with Biased Complementary Labels.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2018, 2018

Correcting the Triplet Selection Bias for Triplet Loss.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2018, 2018

Deep Domain Generalization via Conditional Invariant Adversarial Networks.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2018, 2018

An Efficient and Provable Approach for Mixture Proportion Estimation Using Linear Independence Assumption.

[BibT_eX]

[DOI]

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

Robust Angular Local Descriptor Learning.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ACCV 2018, 2018

Reliable Multi-View Clustering.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

Domain Generalization via Conditional Invariant Representations.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

Large-Cone Nonnegative Matrix Factorization.

[BibT_eX]

[DOI]

Tongliang Liu

Mingming Gong

Dacheng Tao

IEEE Trans. Neural Networks Learn. Syst., 2017

Spectral Ensemble Clustering via Weighted K-Means: Theoretical and Practical Evidence.

[BibT_eX]

[DOI]

IEEE Trans. Knowl. Data Eng., 2017

dipIQ: Blind Image Quality Assessment by Learning-to-Rank Discriminable Image Pairs.

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[DOI]

IEEE Trans. Image Process., 2017

Elastic Net Hypergraph Learning for Image Clustering and Semi-Supervised Classification.

[BibT_eX]

[DOI]

IEEE Trans. Image Process., 2017

Joint Sparse Representation and Multitask Learning for Hyperspectral Target Detection.

[BibT_eX]

[DOI]

IEEE Trans. Geosci. Remote. Sens., 2017

Algorithm-Dependent Generalization Bounds for Multi-Task Learning.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., 2017

General Heterogeneous Transfer Distance Metric Learning via Knowledge Fragments Transfer.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Understanding How Feature Structure Transfers in Transfer Learning.

[BibT_eX]

[DOI]

Tongliang Liu

Qiang Yang

Dacheng Tao

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Algorithmic Stability and Hypothesis Complexity.

[BibT_eX]

[DOI]

Proceedings of the 34th International Conference on Machine Learning, 2017

On Compressing Deep Models by Low Rank and Sparse Decomposition.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

2016

The complexity of algorithmic hypothesis class

[BibT_eX]

[DOI]

Tongliang Liu

PhD thesis, 2016

On the Performance of Manhattan Nonnegative Matrix Factorization.

[BibT_eX]

[DOI]

Tongliang Liu

Dacheng Tao

IEEE Trans. Neural Networks Learn. Syst., 2016

Video Face Editing Using Temporal-Spatial-Smooth Warping.

[BibT_eX]

[DOI]

ACM Trans. Intell. Syst. Technol., 2016

Local Rademacher Complexity for Multi-Label Learning.

[BibT_eX]

[DOI]

IEEE Trans. Image Process., 2016

Dual Diversified Dynamical Gaussian Process Latent Variable Model for Video Repairing.

[BibT_eX]

[DOI]

IEEE Trans. Image Process., 2016

Representative Vector Machines: A Unified Framework for Classical Classifiers.

[BibT_eX]

[DOI]

IEEE Trans. Cybern., 2016

Classification with Noisy Labels by Importance Reweighting.

[BibT_eX]

[DOI]

Tongliang Liu

Dacheng Tao

IEEE Trans. Pattern Anal. Mach. Intell., 2016

Dimensionality-Dependent Generalization Bounds for <i>k</i>-Dimensional Coding Schemes.

[BibT_eX]

[DOI]

Tongliang Liu

Dacheng Tao

Dong Xu

Neural Comput., 2016

Local Blur Mapping: Exploiting High-Level Semantics by Deep Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2016

Dimensionality-Dependent Generalization Bounds for $k$-Dimensional Coding Schemes.

[BibT_eX]

[DOI]

Tongliang Liu

Dacheng Tao

Dong Xu

CoRR, 2016

Domain Adaptation with Conditional Transferable Components.

[BibT_eX]

[DOI]

Proceedings of the 33nd International Conference on Machine Learning, 2016

Diversified Dynamical Gaussian Process Latent Variable Model for Video Repair.

[BibT_eX]

[DOI]

Hao Xiong

Tongliang Liu

Dacheng Tao

Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015

Deformed Graph Laplacian for Semisupervised Learning.

[BibT_eX]

[DOI]

IEEE Trans. Neural Networks Learn. Syst., 2015

Multiview Matrix Completion for Multilabel Image Classification.

[BibT_eX]

[DOI]

IEEE Trans. Image Process., 2015

No Reference Quality Assessment for Multiply-Distorted Images Based on an Improved Bag-of-Words Model.

[BibT_eX]

[DOI]

IEEE Signal Process. Lett., 2015

Spectral Ensemble Clustering.

[BibT_eX]

[DOI]

Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

Multi-Task Model and Feature Joint Learning.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

2014

Decomposition-Based Transfer Distance Metric Learning for Image Classification.

[BibT_eX]

[DOI]

IEEE Trans. Image Process., 2014

Learning relative features through adaptive pooling for image classification.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Multimedia and Expo, 2014

Tongliang Liu

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