20 citations · 39 across the 20 of their papers we have counts for
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Leveraging Computational Pathology AI for Noninvasive Optical Imaging Analysis Without Retraining
Danny Barash, Emilie Manning, Aidan Van Vleck +10
Noninvasive optical imaging modalities can probe patient's tissue in 3D and over time generate gigabytes of clinically relevant data per sample. There is a need for AI models to an…
Gaussian Splashing: Direct Volumetric Rendering Underwater
Nir Mualem, Roy Amoyal, Oren Freifeld +1
In underwater images, most useful features are occluded by water. The extent of the occlusion depends on imaging geometry and can vary even across a sequence of burst images. As a…
Wavelet Convolutions for Large Receptive Fields
Shahaf E. Finder, Roy Amoyal, Eran Treister +1
In recent years, there have been attempts to increase the kernel size of Convolutional Neural Nets (CNNs) to mimic the global receptive field of Vision Transformers' (ViTs) self-at…
Trainable Highly-expressive Activation Functions
Irit Chelly, Shahaf E. Finder, Shira Ifergane +1
Nonlinear activation functions are pivotal to the success of deep neural nets, and choosing the appropriate activation function can significantly affect their performance. Most net…
SpaceJAM: a Lightweight and Regularization-free Method for Fast Joint Alignment of Images
Nir Barel, Ron Shapira Weber, Nir Mualem +2
The unsupervised task of Joint Alignment (JA) of images is beset by challenges such as high complexity, geometric distortions, and convergence to poor local or even global optima.…