Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Gowdra, Nidhi"'
Publikováno v:
Pattern Recognition 119(2021), pp.108057
Convolutional Neural Networks (CNNs) such as ResNet-50, DenseNet-40 and ResNeXt-56 are severely over-parameterized, necessitating a consequent increase in the computational resources required for model training which scales exponentially for incremen
Externí odkaz:
http://arxiv.org/abs/2106.14190
Publikováno v:
Proceedings of the 46th Annual Conference of the IEEE Industrial Electronics Society (IECON2020). IEEE Computer Society Press, pp.465-470
Neural saturation in Deep Neural Networks (DNNs) has been studied extensively, but remains relatively unexplored in Convolutional Neural Networks (CNNs). Understanding and alleviating the effects of convolutional kernel saturation is critical for enh
Externí odkaz:
http://arxiv.org/abs/2105.04128
Publikováno v:
Proceedings of the 46th Annual Conference of the IEEE Industrial Electronics Society (IECON2020). IEEE Computer Society Press, pp.471-476
Convolutional Neural Networks (CNNs) specialize in feature extraction rather than function mapping. In doing so they form complex internal hierarchical feature representations, the complexity of which gradually increases with a corresponding incremen
Externí odkaz:
http://arxiv.org/abs/2105.04097