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Network Comparison Study of Deep Activation Feature Discriminability with Novel Objects
[article]
2022
arXiv
pre-print
Feature extraction has always been a critical component of the computer vision field. More recently, state-of-the-art computer visions algorithms have incorporated Deep Neural Networks (DNN) in feature extracting roles, creating Deep Convolutional Activation Features (DeCAF). The transferability of DNN knowledge domains has enabled the wide use of pretrained DNN feature extraction for applications with novel object classes, especially those with limited training data. This study analyzes the
arXiv:2202.03695v1
fatcat:kaguggvbfnbvncwsulovcycl4a