A Deeper Look at Dataset Bias

Estimating the Data Origin of Fingerprint Samples

Schuch, P., May, J. M., & Busch, C. (2018) · International Conference of the Biometrics Special Interest Group (BIOSIG) · doi:10.23919/biosig.2018.8553235

Dynamic Adaptation on Non-Stationary Visual DomainsPreprint

Shkodrani, S., Hofmann, M., & Gavves, E. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1808.00736

Towards Effective Data Augmentations via Unbiased GAN Utilization

Verma, S., Wang, C., Zhu, L., & Liu, W. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-29894-4_45 · Cited by 1

MUTE: Data-Similarity Driven Multi-hot Target Encoding for Neural Network DesignPreprint

Jaiswal, M. S., Kang, B., Lee, J., & Cho, M. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1910.07042 · Cited by 1

Mitigating the Effect of Dataset Bias on Training Deep Models for Biomedical Images.Preprint

Zhang, Y., Wu, H., Liu, H., Li, T., & Wang, M. D. (2019) · arXiv (Cornell University)

Qualification and Quantification on Viewpoint Biases in Large Scale Image Datasets for General Object Recognition

Qiu, Y., Satoh, Y., Suzuki, R., Kataoka, H., & Iwata, K. (2019) · Journal of the Japan Society for Precision Engineering · doi:10.2493/jjspe.85.1087

Impression Space from Deep Template NetworkPreprint

Fang, G., Wang, X., Zhang, H., Song, J., & Song, M. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2007.05441

Towards All-around Knowledge Transferring: Learning From Task-irrelevant LabelsPreprint

Li, Y., Liu, R., Zhang, Z., Ding, N., Shen, Y., Tao, L., & Zheng, H.-T. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2011.08470

Domain Adaptation and Privileged Information for Visual Recognition

Motiian, S. (2019) · The Research Repository @ WVU (West Virginia University) · doi:10.33915/etd.6271

Fault Diagnosis for Rolling Element Bearing in Dataset Bias Scenario

Hou, L., & Zhang, J. (2021) · Journal of Shanghai Jiaotong University (Science) · doi:10.1007/s12204-021-2320-6

Learning Individual Class Representation From Biased Multi-Label Data

Adiya, T., & Lee, S. (2021) · IEEE Access · doi:10.1109/access.2021.3096822

Transfer Learning and Hyperparameter Optimization for Instance Segmentation with RGB-D Images in Reflective Elevator Environments

Reithmeier, L., Krauß, O., & Zwettler, G. A. (2021) · Computer Science Research Notes · doi:10.24132/csrn.2021.3002.30 · Cited by 1

The mathematics of bias for people prediction

Dev, J. (2022) · XRDS Crossroads The ACM Magazine for Students · doi:10.1145/3538539

Applications of a Bayesian Approach with Deep Learning to Solving Inverse Problems

Alexander, P. (2022) · doi:10.26686/wgtn.20463138

Is the U-Net Directional-Relationship Aware?Preprint

Riva, M., Gori, P., Yger, F., & Isabelle Bloch, A. (2022) · arXiv (Cornell University) · doi:10.48550/arxiv.2207.02574

Extended a Priori Probability (EAPP): A Data-Driven Approach for Machine Learning Binary Classification Tasks

Castelló, V. O., Pérez‐Benito, F. J., Catalá, O. D. T., Igual, I. S., Llobet, R., & Pérez-Cortés, J.-C. (2022) · IEEE Access · doi:10.1109/access.2022.3221936

Unsupervised Domain Adaptation with Differentially Private Gradient Projection

Zheng, M., Zhang, Z., & Ma, X. (2023) · International Journal of Intelligent Systems · doi:10.1155/2023/8426839

Can We Teach Functions to an Artificial Intelligence by Just Showing It Enough “Ground Truth”?

Courtois, A., Ehret, T., Arias, P., & Morel, J. (2022) · Lecture notes in mathematics · doi:10.1007/978-3-031-12244-6_31

Accurate Face Annotations utilizing Deep CNN

Shah, H., & Pandey, A. K. (2023) · International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE) · doi:10.1109/icacite57410.2023.10182628

RK-CORE: An Established Methodology for Exploring the Hierarchical Structure within Datasets

Lu, Y., Huang, Y., Nie, J., Chen, Z., & Xuan, Q. (2024) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp48485.2024.10447791 · Cited by 1

Towards Improved Perception System’s Generalization Through Generative Artificial Intelligence

Wang, J., Campos, J. R., & Madeira, H. (2024) · IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW) · doi:10.1109/issrew63542.2024.00101

Unsupervised Learning of Unbiased Visual Representations

Barbano, C. A., Tartaglione, E., & Grangetto, M. (2024) · IEEE Transactions on Artificial Intelligence · doi:10.1109/tai.2024.3514554

Disentanglement-Based Unsupervised Domain Adaptation for Nuclei Instance Segmentation

Long, J., Liu, D., Tang, Z., & Cai, W. (2024) · International Conference on Image and Vision Computing New Zealand (IVCNZ) · doi:10.1109/ivcnz64857.2024.10794490

Detecting Unforeseen Data Properties with Diffusion Autoencoder Embeddings Using Spine MRI Data

Graf, R., Hunecke, F., Pohl, S., Atad, M., Möller, H., Starck, S., Kroencke, T. J., Bette, S. J., Bamberg, F., Pischon, T., et al. (2025) · Lecture notes in computer science · doi:10.1007/978-3-031-77610-6_8

Deep learning-driven automated high-content dSTORM imaging with a scalable open-source toolkit

Linke, J., Appeltshauser, L., Doppler, K., & Heinze, K. G. (2025) · Biophysical Reports · doi:10.1016/j.bpr.2025.100201

Runtime Monitoring and Enforcement of Conditional Fairness in Generative AIs

Cheng, C., Wu, C., Zhao, X., Bensalem, S., & Rueß, H. (2025) · Lecture notes in computer science · doi:10.1007/978-3-032-05435-7_5

HitoMi-Cam: A Shape-Agnostic Person Detection Method Using the Spectral Characteristics of Clothing

Ono, S. (2025) · Journal of Imaging · doi:10.3390/jimaging11110399

Hybrid Feature-Hash Module for Image Duplicate Detection

Pathirana, W. P. C. P., & Talagala, P. D. (2025) · International Conference on Information Technology Research (ICITR) · doi:10.1109/icitr69413.2025.11353756

Prise en compte du contexte inter-phrastique pour l'extraction d'événements supervisée

Kodelja, D. (2020) · theses.fr (ABES) · doi:10.70675/1cdf7c4cz5d18z4b68zbcf9z8fb475bf31a5

Memorization and learning to index with neural network

Sablayrolles, A. (2020) · theses.fr (ABES) · doi:10.70675/4f00f478z9a1cz4df6z8444zddc40d1e597b

Structured deep learning for video analysis

Baradel, F. (2020) · theses.fr (ABES) · doi:10.70675/2a8e4991z61e3z4030z8b4cz030a297ed81c

Social Media Stories. Event detection in heterogeneous streams of documents applied to the study of information spreading across social and news media

Mazoyer, B. (2020) · theses.fr (ABES) · doi:10.70675/44b771a8ze470z4c54zbdd7z1ffa400cfafe

Handling the speed-accuracy trade-off in deep-learning based pedestrian detection systems

Ujjwal, U. (2019) · theses.fr (ABES) · doi:10.70675/04f27b78ze0c6z442azb7b1zcac3bbaeb4db

Active and Incremental Deep learning with class imbalanced data

Aggarwal, U. (2022) · theses.fr (ABES) · doi:10.70675/e6d51380zef20z4bd7z85eez594673d44967

Spatial Relational Reasoning in Machine Learning : Deep Learning and Graph Clustering

Riva, M. (2022) · doi:10.70675/deca620czd90bz4163zbbd4z1001025c5b79

Addressing interpretability fairness & privacy in machine learning through combinatorial optimization methods

Ferry, J. (2023) · theses.fr (ABES) · doi:10.70675/9719f9b2za9f9z4e0fza756ze63dcf2f6b32

Collateral-Free Learning of Deep Representations : From Natural Images to Biomedical Applications

Barbano, C. A. (2023) · theses.fr (ABES) · doi:10.70675/d0edb18bzae2bz48f8zba04z48d7240e8e0d

CLASH-CTTA: Class-Wise Shift-Aware Hierarchical Continual Test-Time Adaptation

Li, J.-C., & Feng, S.-H. (2026) · IEEE Transactions on Image Processing · doi:10.1109/tip.2026.3705195

Clothing Classification for Textile Recycling and Evaluation of Dataset Supplementation

Saad, C., Böhm, T., Roth, T., & Geißelsöder, S. (2026) · Communications in computer and information science · doi:10.1007/978-3-032-30826-9_46

Discriminative prototypical clustering transport with mean teacher for visual domain adaptation

Dan, Y., & Zhou, D. (2026) · Complex & Intelligent Systems · doi:10.1007/s40747-026-02375-4

Person search: a comprehensive survey on image-based person search using deep learning

Bakaye, B., Hannane, R., Oirrak, A. E., & Elboushaki, A. (2026) · International Journal of Multimedia Information Retrieval · doi:10.1007/s13735-026-00416-9

Data for Machine Learning

Law, E., & Yin, M. (2026) · Cambridge University Press eBooks · doi:10.1017/9781108872225.008

Doing Human-Centered Machine Learning

Fiebrink, R., Gillies, M. F. P., & Ramos, G. (2026) · Cambridge University Press eBooks · doi:10.1017/9781108872225.006

Thermal imaging-based characterization of fruit bruising using deep learning: a cross-dataset evaluation study

Nogay, H. S., & Noğay, N. H. (2026) · European Food Research and Technology · doi:10.1007/s00217-026-05324-0

Detection and profiling of dataset bias in CNN analysis of images

Martínez, E., Okonoda, M., Dalal, A., & Shamir, L. (2026) · Computing in Science & Engineering · doi:10.1109/mcse.2026.3675925

Examining CNN Representations With Respect to Dataset Bias

Zhang, Q., Wang, W., & Zhu, S. C. (2018) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v32i1.11833 · Cited by 95

Identifying Bias in Deep Neural Networks Using Image Transforms

Erukude, S. T., Joshi, A., & Shamir, L. (2024) · Computers · doi:10.3390/computers13120341 · Cited by 13

A Testbed for Cross-Dataset AnalysisPreprint

Tommasi, T., Tuytelaars, T., & Barbara Caputo, B. (2014) · arXiv (Cornell University) · doi:10.48550/arxiv.1402.5923 · Cited by 50

A Conservative Approach for Unbiased Learning on Unknown Biases

Jeon, M., Kim, D., Lee, W., Kang, M., & Lee, J. (2022) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52688.2022.01625 · Cited by 13