activity
20172024
most citedSupervised and Unsupervised End-to-End Deep Learning for Gene Ontology Classification of Neural In Situ Hybridization Images

6 citations · 12 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2024

MenakBERT -- Hebrew Diacriticizer

Ido Cohen, Jacob Gidron, Idan Pinto

Diacritical marks in the Hebrew language give words their vocalized form. The task of adding diacritical marks to plain Hebrew text is still dominated by a system that relies heavi…

cs.CL2022★ 2 cited

Understanding Transformer Memorization Recall Through Idioms

Adi Haviv, Ido Cohen, Jacob Gidron +3

To produce accurate predictions, language models (LMs) must balance between generalization and memorization. Yet, little is known about the mechanism by which transformer LMs emplo…

eess.SP2022

Unsupervised Detection of Sub-Territories of the Subthalamic Nucleus During DBS Surgery with Manifold Learning

Ido Cohen, Dan Valsky, Ronen Talmon

During Deep Brain Stimulation(DBS) surgery for treating Parkinson's disease, one vital task is to detect a specific brain area called the Subthalamic Nucleus(STN) and a sub-territo…

cs.CV2019★ 6 cited

Supervised and Unsupervised End-to-End Deep Learning for Gene Ontology Classification of Neural In Situ Hybridization Images

Ido Cohen, Eli David, Nathan S. Netanyahu

In recent years, large datasets of high-resolution mammalian neural images have become available, which has prompted active research on the analysis of gene expression data. Tradit…

cs.CV2017★ 4 cited

DeepBrain: Functional Representation of Neural In-Situ Hybridization Images for Gene Ontology Classification Using Deep Convolutional Autoencoders

Ido Cohen, Eli David, Nathan S. Netanyahu +2

This paper presents a novel deep learning-based method for learning a functional representation of mammalian neural images. The method uses a deep convolutional denoising autoencod…