13 citations · 31 across the 4 of their papers we have counts for
5 papers
Deep Lake: a Lakehouse for Deep Learning
Sasun Hambardzumyan, Abhinav Tuli, Levon Ghukasyan +8
Traditional data lakes provide critical data infrastructure for analytical workloads by enabling time travel, running SQL queries, ingesting data with ACID transactions, and visual…
Hyper: Distributed Cloud Processing for Large-Scale Deep Learning Tasks
Davit Buniatyan
Training and deploying deep learning models in real-world applications require processing large amounts of data. This is a challenging task when the amount of data grows to a hundr…
Siamese Encoding and Alignment by Multiscale Learning with Self-Supervision
Eric Mitchell, Stefan Keselj, Sergiy Popovych +2
We propose a method of aligning a source image to a target image, where the transform is specified by a dense vector field. The two images are encoded as feature hierarchies by sia…
PZnet: Efficient 3D ConvNet Inference on Manycore CPUs
Sergiy Popovych, Davit Buniatyan, Aleksandar Zlateski +2
Convolutional nets have been shown to achieve state-of-the-art accuracy in many biomedical image analysis tasks. Many tasks within biomedical analysis domain involve analyzing volu…
Deep Learning Improves Template Matching by Normalized Cross Correlation
Davit Buniatyan, Thomas Macrina, Dodam Ih +2
Template matching by normalized cross correlation (NCC) is widely used for finding image correspondences. We improve the robustness of this algorithm by preprocessing images with "…