1 citations · 1 across the 1 of their papers we have counts for
4 papers
Noise Estimation Using Density Estimation for Self-Supervised Multimodal Learning
Elad Amrani, Rami Ben-Ari, Daniel Rotman +1
One of the key factors of enabling machine learning models to comprehend and solve real-world tasks is to leverage multimodal data. Unfortunately, annotation of multimodal data is…
Learning to Detect and Retrieve Objects from Unlabeled Videos
Elad Amrani, Rami Ben-Ari, Tal Hakim +1
Learning an object detector or retrieval requires a large data set with manual annotations. Such data sets are expensive and time consuming to create and therefore difficult to obt…
Classification and Detection in Mammograms with Weak Supervision via Dual Branch Deep Neural Net
Ran Bakalo, Rami Ben-Ari, Jacob Goldberger
The high cost of generating expert annotations, poses a strong limitation for supervised machine learning methods in medical imaging. Weakly supervised methods may provide a soluti…
Weakly and Semi Supervised Detection in Medical Imaging via Deep Dual Branch Net
Ran Bakalo, Jacob Goldberger, Rami Ben-Ari
This study presents a novel deep learning architecture for multi-class classification and localization of abnormalities in medical imaging illustrated through experiments on mammog…