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On the ability of CNNs to extract color invariant intensity based features for image classification
Convolutional neural networks (CNNs) have demonstrated remarkable success in vision-related tasks.
Semantic Segmentation of Porosity in 4D Spatio-Temporal X-ray μCT of Titanium Coated Ni wires using Deep Learning
A fully convolutional neural network was used to measure the evolution of the volume fraction of two different Kirkendall pores during the homogenization of Ti coated Ni wires.
Learning Generalized Hybrid Proximity Representation for Image Recognition
Recently, deep metric learning techniques received attention, as the learned distance representations are useful to capture the similarity relationship among samples and further improve the performance of various of supervised or unsupervised learning tasks.
A Novel Feature Representation for Malware Classification
In this study we have presented a novel feature representation for malicious programs that can be used for malware classification.
On the Combinality of Evidence in the Dempster-Shafer Theory
In the current versions of the Dempster-Shafer theory, the only essential restriction on the validity of the rule of combination is that the sources of evidence must be statistically independent.
