activity
20082026
most citedDeepSign: Deep Learning for Automatic Malware Signature Generation and Classification

224 citations · 614 across the 33 of their papers we have counts for

collaborators

33 papers

cs.CV2026

Spatio-Temporal Transformers for Long-Term NDVI Forecasting

Ido Faran, Nathan S. Netanyahu, Maxim Shoshany

Long-term satellite image time series (SITS) analysis in heterogeneous landscapes faces significant challenges, particularly in Mediterranean regions where complex spatial patterns…

cs.CV2026

Multi-Sensor Matching with HyperNetworks

Eli Passov, Nathan S. Netanyahu, Yosi Keller

Hypernetworks are models that generate or modulate the weights of another network. They provide a flexible mechanism for injecting context and task conditioning and have proven bro…

cs.CV2025

A Generic Hybrid Framework for 2D Visual Reconstruction

Daniel Rika, Dror Sholomon, Eli David +2

This paper presents a versatile hybrid framework for addressing 2D real-world reconstruction tasks formulated as jigsaw puzzle problems (JPPs) with square, non-overlapping pieces.…

eess.IV2023

XVertNet: Unsupervised Contrast Enhancement of Vertebral Structures with Dynamic Self-Tuning Guidance and Multi-Stage Analysis

Ella Eidlin, Assaf Hoogi, Hila Rozen +2

Chest X-rays remain the primary diagnostic tool in emergency medicine, yet their limited ability to capture fine anatomical details can result in missed or delayed diagnoses. To ad…

q-bio.QM2023★ 1 cited

PathRTM: Real-time prediction of KI-67 and tumor-infiltrated lymphocytes

Steven Zvi Lapp, Eli David, Nathan S. Netanyahu

In this paper, we introduce PathRTM, a novel deep neural network detector based on RTMDet, for automated KI-67 proliferation and tumor-infiltrated lymphocyte estimation. KI-67 prol…

cs.CV2022

Edge2Vec: A High Quality Embedding for the Jigsaw Puzzle Problem

Daniel Rika, Dror Sholomon, Eli David +1

Pairwise compatibility measure (CM) is a key component in solving the jigsaw puzzle problem (JPP) and many of its recently proposed variants. With the rapid rise of deep neural net…