J. Sinoway, L. Pearlstein, I. Pearlstein, Y. Hu, D. Mirtcheva Brodersen, Z. Gao, “A Novel Intervention for Smoking Cessation Tailored to Underserved Populations Based on an mHealth Device,” 2020 42nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2020.

L. Pearlstein. “A probabilistic analysis of connected component sizes in random binary images (Conference Presentation).” Automatic Target Recognition XXX. Vol. 11394. International Society for Optics and Photonics, 2020.

A. A. Alshehri, A. Lutz, S. Ezekiel, L. Pearlstein, J. Conlen. “DCNN Optimization Using Multi-Resolution Image Fusion.” KSII Transactions on Internet and Information Systems, vol. 14:11 (2020): 4290-4309.

H. Khajanchi, J. Bezold, M. Kilcher, A. Benasutti, B. Rentsch, L. Pearlstein, S. Maxwell, “PSIG-GAN: A parameterized synthetic image generator optimized via non-differentiable GAN,” 2019 IEEE Applied Imagery Pattern Recognition Workshop (AIPR), IEEE, 2019.

S. Ezekiel, L. Pearlstein, A. A. Alshehri, A. Lutz, J. Zaunegger, and W. Farag. “Investigating GAN and VAE to Train DCNN.” International Journal of Machine Learning and Computing 9, no. 6 (2019).

M. Giansiracusa, L. Pearlstein, T. Daws, S. Ezekiel, and A. A. Alshehri. “A comparative study of multi-focus, multi-resolution image fusion transforms and methods.” Compusoft 8, no. 9 (2019): 3374-3387.

L. Pearlstein, A. Benasutti, S. Maxwell, M. Kilcher, J. Bezold, and W. Seto, “Retrieval of color space conversion matrix via convolutional neural network,” Int’l J. Machine Learning & Computing, Vol.9(4): 393-400, 2019.

L. Pearlstein, S. Maxwell, and A. Aved, “Adaptive prediction resolution video coding for reduced DRAM bandwidth”, Elsevier Integration, the VLSI Journal, vol. 62, pp. 382-394, June 2018.

S. Maxwell, M. Kilcher, A. Benasutti, B. Siebert, W. Seto, O. Shanley, L. Pearlstein, “Automated detection of colorspace via convolutional neural network,” 2018 IEEE Applied Imagery Pattern Recognition Workshop (AIPR), IEEE, 2018.

S. Ezekiel, L. Pearlstein, D. Kornish, J. Geary, and L. Njilla, “Malware Classification Using Deep Learning,” 2018 IEEE Applied Imagery Pattern Recognition Workshop (AIPR), IEEE, 2018.

C. Long, S. Ezekiel, L. Pearlstein, and J. Raquepas, “Ballistic Missile Boost Phase Acceleration Reconstruction using Wavelet Multi-resolution Analysis,” 2017 IEEE Applied Imagery Pattern Recognition Workshop (AIPR), IEEE, 2017.

L. Pearlstein, A.J. Aved, and I. Patel, “Video coding layer optimization for target detection,” 2016 IEEE Applied Imagery Pattern Recognition Workshop (AIPR), IEEE, 2016.

L. Pearlstein, M. Kim, and W. Seto, “Convolutional neural network application to plant detection, based on synthetic imagery,” 2016 IEEE Applied Imagery Pattern Recognition Workshop (AIPR), IEEE, 2016.

R. Selvaggi and L. Pearlstein, “Broadcom mediaDSP: A Platform for Building Programmable Multicore Video Processors,” IEEE Micro, vol. 29, no. 2, pp. 30-45, March-April 2009

Y. Jia, Q.D. Le, L. Pearlstein, P. Swan, “Video Processing in HDTV Receivers for Recovery of Missing Picture Information: De-interlacing, Frame-Rate Conversion, and Super-Resolution,” Information Display, vol. 23, no. 11, Nov. 2007.

J. Boyce, L. Pearlstein, “Low-Cost All Format ATV Decoding with Improved Quality,” Proceedings of the 1996 SMPTE Winter Conference, Seattle.

J. Boyce, J. Henderson, and L. Pearlstein, An SDTV decoder with HDTV capability: an all-format ATV decoder,” Proceedings of the 1995 SMPTE Fall Conference, New Orleans.

J. Augenbraun, J. Boyce, L. Pearlstein and M. Plotnick, “A Comparative Analysis of Methods for Joint Coding of DCT Coefficients for Digital Video Compression,” Proceedings of the 1992 International Workshop on HDTV, Kawasaki, Japan.

K. Barner and L. Pearlstein, “Two New Methods for Adaptive Pre-Equalization: Bootstrapping and Adaptive Inversion,” Proceedings of the Johns Hopkins Conference on Information Sciences and Systems, 1989.

P. Mack and L. Pearlstein, “Asymptotic Accuracy of an Adaptive Notch Filter with Pseudolinear Regression Approximation,” Proceedings of the Johns Hopkins Conference on Information Sciences and Systems, 1989.

P. Mack and L. Pearlstein, “An Adaptive Notch Filter with Quadratic Performance at Linear Cost,”  Proceedings of the 22nd Annual Princeton Conference on Information Sciences and Systems, 1988.

L. Pearlstein and B. Liu, “Convergence Rate of the Adaptive Line Enhancer with Tap Failures,” Proceedings of the 1987 IEEE International Conference on Acoustics, Speech, and Signal Processing, Dallas, TX.

L. Pearlstein and B. Liu, “Retrieval of Sinusoidal Signals by Adaptive Notch Filtering,” Proceedings of the Twenty-Third Annual Allerton Conference on Communication, Control, and Computing, Monticello, IL, October 1985.