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Found 5 papers, 4 papers with code
Sketched RT3D: How to reconstruct billions of photons per second
Single-photon light detection and ranging (lidar) captures depth and intensity information of a 3D scene.
Compressive Independent Component Analysis: Theory and Algorithms
Compressive learning forms the exciting intersection between compressed sensing and statistical learning where one exploits forms of sparsity and structure to reduce the memory and/or computational complexity of the learning task.
Surface Detection for Sketched Single Photon Lidar
The computational load of the proposed detection algorithm depends solely on the size of the sketch, in contrast to previous algorithms that depend at least linearly in the number of collected photons or histogram bins, paving the way for fast, accurate and memory efficient lidar estimation.
A Sketching Framework for Reduced Data Transfer in Photon Counting Lidar
Single-photon lidar has become a prominent tool for depth imaging in recent years.
Compressive Learning for Semi-Parametric Models
In the compressive learning theory, instead of solving a statistical learning problem from the input data, a so-called sketch is computed from the data prior to learning.
