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Found 4 papers, 3 papers with code
Advanced wood species identification based on multiple anatomical sections and using deep feature transfer and fusion
In recent years, we have seen many advancements in wood species identification.
Prediction of Activated Sludge Settling Characteristics from Microscopy Images with Deep Convolutional Neural Networks and Transfer Learning
Activated sludge settling characteristics, for example, are affected by microbial community composition, varying by changes in operating conditions and influent characteristics of wastewater treatment plants (WWTPs).
RADAM: Texture Recognition through Randomized Aggregated Encoding of Deep Activation Maps
Texture analysis is a classical yet challenging task in computer vision for which deep neural networks are actively being applied.
Ranked #1 on
Image Classification
on DTD
(using extra training data)
Improving Deep Neural Network Random Initialization Through Neuronal Rewiring
In this sense, PA rewiring only reorganizes connections, while preserving the magnitude and distribution of the weights.
