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Found 5 papers, 1 papers with code
Deep Lake: a Lakehouse for Deep Learning
Traditional data lakes provide critical data infrastructure for analytical workloads by enabling time travel, running SQL queries, ingesting data with ACID transactions, and visualizing petabyte-scale datasets on cloud storage.
Hyper: Distributed Cloud Processing for Large-Scale Deep Learning Tasks
Training and deploying deep learning models in real-world applications require processing large amounts of data.
Siamese Encoding and Alignment by Multiscale Learning with Self-Supervision
We show that siamese encoding enables more accurate alignment than the image pyramids of SPyNet, a previous deep learning approach to coarse-to-fine alignment.
PZnet: Efficient 3D ConvNet Inference on Manycore CPUs
Convolutional nets have been shown to achieve state-of-the-art accuracy in many biomedical image analysis tasks.
Deep Learning Improves Template Matching by Normalized Cross Correlation
Template matching by normalized cross correlation (NCC) is widely used for finding image correspondences.
