Meet the Team
Peri Akiva
Senior R&D Engineer
Kitware Remote
Ph.D., Computer Engineering
Rutgers University
M.Sc., Computer Engineering
Rutgers University
B.S. in Computer Engineering
Rutgers University
Peri Akiva is a Senior R&D Engineer working remotely on Kitware’s Computer Vision Team. He is focused on machine learning tasks where he’ll be collaborating with researchers and training algorithms to solve challenging problems.
He is a previous Kitware intern in the summer of 2021. After his stint at Kitware, he interned at Meta AI as a Research scientist intern. There he focused on research in the topic of self-supervised object detection from egocentric videos. He also interned for Samsung Research America, where he focused on research in the topics of high resolution video frame interpolation and extrapolation. He also interned for Siemens Corporate Research, and Goldman Sachs.
Peri received bachelor’s, master’s and Ph.D. degrees in Computer Engineering from Rutgers University.
Publications
- P. Akiva and K. Dana, "Single Stage Weakly Supervised Semantic Segmentation of Complex Scenes," in 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2023. [URL]
- P. Akiva, B. Planche, A. Roy, P. Oudemans, and K. Dana, "Vision on the bog: Cranberry crop risk evaluation with deep learning," Computers and Electronics in Agriculture, vol. 203, pp. 107444, Dec. 2022. [URL]
- P. Akiva, M. Purri, and M. Leotta, "Self-Supervised Material and Texture Representation Learning for Remote Sensing Tasks," in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022. [URL]
- P. Akiva and K. Dana, "Towards Single Stage Weakly Supervised Semantic Segmentation," arXiv, 2021. [URL]
- P. Akiva, B. Planche, A. Roy, K. Dana, P. Oudemans, and M. Mars, "AI on the Bog: Monitoring and Evaluating Cranberry Crop Risk," in Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2021. [URL]
- P. Akiva, M. Purri, K. Dana, B. Tellman, and T. Anderson, "H2O-Net: Self-Supervised Flood Segmentation via Adversarial Domain Adaptation and Label Refinement," in Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2021. [URL]
- P. Akiva, K. Dana, P. Oudemans, and M. Mars, "Finding Berries: Segmentation and Counting of Cranberries using Point Supervision and Shape Priors," in 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2020. [URL]
- P. Akiva, M. Purri, T. Anderson, V. Sunkara, B. Tellman, and Kristin Dana, "Automating Labels to Train Deep Neural Networks for Water Segmentation on Sentinel-2 and Planetscope Imagery," in AGU Fall Meeting Abstracts, 2020. [URL]
- J. Mahmud, R. Singh, P. Akiva, S. Kundu, K. Peng, and J. Frahm, "ViewSynth: Learning Local Features from Depth using View Synthesis," arViv, 2019. [URL]