13 papers
Learnable Spectral Activations
Tamir Shor, Or Litany, Alex Bronstein
Implicit neural representations (INRs) are shaped by the spectral structure induced by their input encodings and activation functions. Existing methods improve fitting primarily by…
Awaken, Then Scale: Tiny Adaptation for MRI Reconstruction
Mohammed Wattad, Tamir Shor, Alexander M. Bronstein
Dormant Awakening (DA) specializes a magnetic resonance imaging (MRI) reconstruction model by fitting a small set of zero weights to one labeled slice. Across fourteen U-shaped con…
Beyond Sparsity: Weight Location and Network Context in Pruned MRI Reconstruction
Mohammed Wattad, Tamir Shor, Alexander M. Bronstein
Pruning reduces the number of weights in magnetic resonance imaging (MRI) reconstruction networks. Equal sparsity, however, can retain weights with different computational roles an…
RS-OVC: Open-Vocabulary Counting for Remote-Sensing Data
Tamir Shor, George Leifman, Genady Beryozkin
Object-Counting for remote-sensing (RS) imagery is attracting increasing research interest due to its crucial role in a wide and diverse set of applications. While several promisin…
On The Role of K-Space Acquisition in MRI Reconstruction Domain-Generalization
Mohammed Wattad, Tamir Shor, Alex Bronstein
Recent work has established learned k-space acquisition patterns as a promising direction for improving reconstruction quality in accelerated Magnetic Resonance Imaging (MRI). Desp…
T1-PILOT: Optimized Trajectories for T1 Mapping Acceleration
Tamir Shor, Moti Freiman, Chaim Baskin +1
Cardiac T1 mapping provides critical quantitative insights into myocardial tissue composition, enabling the assessment of pathologies such as fibrosis, inflammation, and edema. How…
On Adversarial Attacks In Acoustic Drone Localization
Tamir Shor, Chaim Baskin, Alex Bronstein
Multi-rotor aerial autonomous vehicles (MAVs, more widely known as "drones") have been generating increased interest in recent years due to their growing applicability in a vast an…
Adversarial Attacks in Weight-Space Classifiers
Tamir Shor, Ethan Fetaya, Chaim Baskin +1
Implicit Neural Representations (INRs) have been recently garnering increasing interest in various research fields, mainly due to their ability to represent large, complex data in…
TEAM PILOT -- Learned Feasible Extendable Set of Dynamic MRI Acquisition Trajectories
Tamir Shor, Chaim Baskin, Alex Bronstein
Dynamic Magnetic Resonance Imaging (MRI) is a crucial non-invasive method used to capture the movement of internal organs and tissues, making it a key tool for medical diagnosis. H…
Leveraging Latents for Efficient Thermography Classification and Segmentation
Tamir Shor, Chaim Baskin, Alex Bronstein
Breast cancer is a prominent health concern worldwide, currently being the secondmost common and second-deadliest type of cancer in women. While current breast cancer diagnosis mai…
Active propulsion noise shaping for multi-rotor aircraft localization
Gabriele Serussi, Tamir Shor, Tom Hirshberg +2
Multi-rotor aerial autonomous vehicles (MAVs) primarily rely on vision for navigation purposes. However, visual localization and odometry techniques suffer from poor performance in…
Single Image Test-Time Adaptation for Segmentation
Klara Janouskova, Tamir Shor, Chaim Baskin +1
Test-Time Adaptation (TTA) methods improve the robustness of deep neural networks to domain shift on a variety of tasks such as image classification or segmentation. This work expl…
Multi PILOT: Learned Feasible Multiple Acquisition Trajectories for Dynamic MRI
Tamir Shor, Tomer Weiss, Dor Noti +1
Dynamic Magnetic Resonance Imaging (MRI) is known to be a powerful and reliable technique for the dynamic imaging of internal organs and tissues, making it a leading diagnostic too…