Peter Bajcsy
Affiliations: | University of Illinois, Urbana-Champaign, Urbana-Champaign, IL |
Area:
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"Peter Bajcsy"
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Publications
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Sathe PS, Wolf CM, Kim Y, et al. (2024) Data-driven simulations for training AI-based segmentation of neutron images. Scientific Reports. 14: 6614 |
Jain A, Laidlaw DH, Bajcsy P, et al. (2023) Memory-efficient semantic segmentation of large microscopy images using graph-based neural networks. Microscopy (Oxford, England) |
Bajcsy P, Feldman S, Majurski M, et al. (2020) Approaches to training multi-class semantic image segmentation of damage in concrete. Journal of Microscopy |
Padi S, Manescu P, Schaub N, et al. (2020) Comparison of Artificial Intelligence based approaches to cell function prediction Informatics in Medicine Unlocked. 18: 100270 |
Schaub NJ, Hotaling NA, Manescu P, et al. (2019) Deep learning predicts function of live retinal pigment epithelium from quantitative microscopy. The Journal of Clinical Investigation |
Bajcsy P, Yoon S, Florczyk SJ, et al. (2017) Modeling, validation and verification of three-dimensional cell-scaffold contacts from terabyte-sized images. Bmc Bioinformatics. 18: 526 |
Pazmino Betancourt B, Florczyk S, Simon M, et al. (2017) Effect of the Scaffold Microenvironment on Cell Polarizability and Capacitance Determined by Probabilistic Computations. Biomedical Materials (Bristol, England) |
Chalfoun J, Majurski M, Blattner T, et al. (2017) MIST: Accurate and Scalable Microscopy Image Stitching Tool with Stage Modeling and Error Minimization. Scientific Reports. 7: 4988 |
Manescu P, Jong Lee Y, Camp C, et al. (2017) Accurate and interpretable classification of microspectroscopy pixels using artificial neural networks. Medical Image Analysis. 37: 37-45 |
Bajcsy P, Vandecreme A, Amelot J, et al. (2016) Enabling Interactive Measurements from Large Coverage Microscopy. Computer. 49: 70-79 |