ThriftyNets: Convolutional Neural Networks with Tiny Parameter Budget
Deep Neural Networks are state-of-the-art in a large number of challenges in machine learning. However, to reach the best performance they require a huge pool of parameters. Indeed, typical deep convolutional architectures present an increasing number of feature maps as we go deeper in the network,...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-03-01
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| Series: | IoT |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2624-831X/2/2/12 |