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Found 4 papers, 1 papers with code
Compressing Deep CNNs using Basis Representation and Spectral Fine-tuning
We propose an efficient and straightforward method for compressing deep convolutional neural networks (CNNs) that uses basis filters to represent the convolutional layers, and optimizes the performance of the compressed network directly in the basis space.
Biosensors and Machine Learning for Enhanced Detection, Stratification, and Classification of Cells: A Review
Biological cells, by definition, are the basic units which contain the fundamental molecules of life of which all living things are composed.
BasisConv: A method for compressed representation and learning in CNNs
Specifically, any convolution layer of the CNN is easily replaced by two successive convolution layers: the first is a set of fixed filters (that represent the knowledge space of the entire layer and do not change), which is followed by a layer of one-dimensional filters (that represent the learned knowledge in this space).
Towards a Crowd Analytic Framework For Crowd Management in Majid-al-Haram
The scared cities of Makkah Al Mukarramah and Madina Al Munawarah host millions of pilgrims every year.
