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Found 5 papers, 4 papers with code
Im2win: Memory Efficient Convolution On SIMD Architectures
However, the im2col data transformation can lead to at least 2$\times$ memory footprint compared to not using data transformation at all, thus limiting the size of neural network models running on memory-limited systems.
Im2win: An Efficient Convolution Paradigm on GPU
Convolution is the most time-consuming operation in deep neural network operations, so its performance is critical to the overall performance of the neural network.
Ultra Efficient Transfer Learning with Meta Update for Cross Subject EEG Classification
The pattern of Electroencephalogram (EEG) signal differs significantly across different subjects, and poses challenge for EEG classifiers in terms of 1) effectively adapting a learned classifier onto a new subject, 2) retaining knowledge of known subjects after the adaptation.
Hybrid Feature Learning for Handwriting Verification
Experiments are performed by complementing one of the HEF methods with one ALF method on 150000 pairs of samples of the word "AND" cropped from handwritten notes written by 1500 writers.
Indoor Frame Recovery from Refined Line Segments
First, the line segments are refined by four consecutive operations, i. e., reclassifying, connecting, fitting, and voting.
