| Commercial visual analytics systems–advances in the big data analytics field M Behrisch, D Streeb, F Stoffel, D Seebacher, B Matejek, SH Weber, ... IEEE transactions on visualization and computer graphics 25 (10), 3011-3031, 2018 | 84 | 2018 |
| Learning hierarchical semantic segmentations of LIDAR data D Dohan, B Matejek, T Funkhouser 2015 International Conference on 3D Vision, 273-281, 2015 | 44 | 2015 |
| Scalable Interactive Visualization for Connectomics D Haehn, J Hoffer, B Matejek, A Suissa-Peleg, AK Al-Awami, L Kamentsky, ... Informatics 4 (3), 29, 2017 | 30 | 2017 |
| Biologically-Constrained Graphs for Global Connectomics Reconstruction B Matejek, D Haehn, H Zhu, D Wei, T Parag, H Pfister Computer Vision and Pattern Recognition, 2019 | 25 | 2019 |
| Two Stream Active Query Suggestion for Active Learning in Connectomics Z Lin, D Wei, WD Jang, S Zhou, X Chen, X Wang, R Schalek, D Berger, ... | 20* | |
| Axonem dataset: 3d axon instance segmentation of brain cortical regions D Wei, K Lee, H Li, R Lu, JA Bae, Z Liu, L Zhang, M dos Santos, Z Lin, ... Medical Image Computing and Computer Assisted Intervention–MICCAI 2021: 24th …, 2021 | 18 | 2021 |
| K-median algorithms: theory in practice D Dohan, S Karp, B Matejek | 16 | 2015 |
| Efficient correction for em connectomics with skeletal representation K Dmitriev12, T Parag, B Matejek, AE Kaufman12, H Pfister British Machine Vision Conferemce (BMVC), 2018 | 14 | 2018 |
| Anisotropic EM Segmentation by 3D Affinity Learning and Agglomeration T Parag, F Tschopp, W Grisaitis, SC Turaga, X Zhang, B Matejek, ... arXiv preprint arXiv:1707.08935, 2017 | 14 | 2017 |
| Compresso: Efficient compression of segmentation data for connectomics B Matejek, D Haehn, F Lekschas, M Mitzenmacher, H Pfister Medical Image Computing and Computer Assisted Intervention− MICCAI 2017 …, 2017 | 14 | 2017 |
| Synapse-aware skeleton generation for neural circuits B Matejek, D Wei, X Wang, J Zhao, K Palágyi, H Pfister Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019 | 8 | 2019 |
| Algorithmic tools for understanding the motif structure of networks T Chen, B Matejek, M Mitzenmacher, CE Tsourakakis Joint European Conference on Machine Learning and Knowledge Discovery in …, 2022 | 6 | 2022 |
| Edge-colored directed subgraph enumeration on the connectome B Matejek, D Wei, T Chen, CE Tsourakakis, M Mitzenmacher, H Pfister Scientific Reports 12 (1), 11349, 2022 | 6 | 2022 |
| Direct Amortized Likelihood Ratio Estimation AD Cobb, B Matejek, D Elenius, A Roy, S Jha Proceedings of the AAAI Conference on Artificial Intelligence 38 (18), 20362 …, 2024 | 2 | 2024 |
| Safeguarding Network Intrusion Detection Models from Zero-day Attacks and Concept Drift B Matejek, A Gehani, ND Bastian, D Clouse, B Kline, S Jha AAAI Workshop on Artificial Intelligence for Cyber Security (AICS), 2024 | 2 | 2024 |
| Melanoma Detection with Uncertainty Quantification SH Kim, E Gaibor, B Matejek, D Haehn arXiv preprint arXiv:2411.10322, 2024 | | 2024 |
| Addressing Uncertainty in LLMs to Enhance Reliability in Generative AI R Kaur, C Samplawski, AD Cobb, A Roy, B Matejek, M Acharya, D Elenius, ... arXiv preprint arXiv:2411.02381, 2024 | | 2024 |
| Resource-Constrained Heuristic for Max-SAT B Matejek, D Elenius, C Gentry, D Stoker, A Cobb arXiv preprint arXiv:2410.09173, 2024 | | 2024 |
| Non-Invasive Stress Monitoring From Video A Tiwari, B Matejek, D Haehn 2024 IEEE International Symposium on Biomedical Imaging (ISBI), 1-5, 2024 | | 2024 |
| Scalable Biologically-Aware Skeleton Generation for Connectomic Volumes B Matejek, T Franzmeyer, D Wei, X Wang, J Zhao, K Palágyi, JW Lichtman, ... IEEE transactions on medical imaging 41 (9), 2360-2370, 2022 | | 2022 |
Daniel HaehnUniversity of Massachusetts BostonVerified email at cs.umb.edu
