7 citations · 10 across the 4 of their papers we have counts for
3 papers · 1 filter
AI on the Bog: Monitoring and Evaluating Cranberry Crop Risk
Peri Akiva, Benjamin Planche, Aditi Roy +3
Machine vision for precision agriculture has attracted considerable research interest in recent years. The goal of this paper is to develop an end-to-end cranberry health monitorin…
H2O-Net: Self-Supervised Flood Segmentation via Adversarial Domain Adaptation and Label Refinement
Peri Akiva, Matthew Purri, Kristin Dana +2
Accurate flood detection in near real time via high resolution, high latency satellite imagery is essential to prevent loss of lives by providing quick and actionable information.…
Finding Berries: Segmentation and Counting of Cranberries using Point Supervision and Shape Priors
Peri Akiva, Kristin Dana, Peter Oudemans +1
Precision agriculture has become a key factor for increasing crop yields by providing essential information to decision makers. In this work, we present a deep learning method for…