Modeling, validation and verification of cell-scaffold contact measurements over terabyte-sized 3D image collection. - Peter Bajcsy; Soweon Yoon; Mylene Simon; Mary Brady; Ram D. Sriram; Nathan Hotaling; Nicholas Schaub; Carl G. Simon; Piotr M. Szczypinski; Stephen J. Florczyk (IEEE BigData, 2016)

Modeling, validation and verification of three-dimensional cell-scaffold contacts from terabyte-sized images. - Peter Bajcsy; Soweon Yoon; Stephen J. Florczyk; Nathan Hotaling; Mylene Simon; Piotr M. Szczypinski; Nicholas Schaub; Carl G. Simon; Mary Brady; Ram D. Sriram (BMC Bioinform., 2017)

Cell Image Segmentation Using Generative Adversarial Networks, Transfer Learning, and Augmentations. - Michael Majurski; Petru Manescu; Sarala Padi; Nicholas Schaub; Nathan Hotaling; Carl Simon Jr; Peter Bajcsy (CVPR Workshops, 2019)

Assessing Intelligence in Artificial Neural Networks. - Nicholas J. Schaub; Nathan Hotaling (CoRR, 2020)

Neural Network Calculator for Designing Trojan Detectors. - Peter Bajcsy; Nicholas J. Schaub; Michael Majurski (CoRR, 2020)

Quantifying Variability in Microscopy Image Analyses for COVID-19 Drug Discovery. - Mylene Simon; Sunny Yu; Jayapriya Nagarajan; Peter Bajcsy; Nicholas J. Schaub; Mohamed Ouladi; Sudharsan Prativadi; Nathan Hotaling (CVPR Workshops, 2021)

Theia: Bleed-Through Estimation with Interaction Terms and Convolutional Kernels. - Najib Ishaq; Nathan Hotaling; Nicholas Schaub (ISBI, 2022)

Theia: Bleed-Through Estimation with Convolutional Neural Networks. - Najib Ishaq; Nathan Hotaling; Nicholas Schaub (CVPR Workshops, 2023)

Unbiased image segmentation assessment toolkit for quantitative differentiation of state-of-the-art algorithms and pipelines. - Vishakha Goyal; Nicholas J. Schaub; Ty C. Voss; Nathan Hotaling (BMC Bioinform., 2023)