Cart
Create Account
Sign In
Already purchased this program?
Login to View
This video program is a part of the Premium package:
Corrdrop: Correlation Based Dropout For Convolutional Neural Networks
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Corrdrop: Correlation Based Dropout For Convolutional Neural Networks
Convolutional neural networks (CNNs) can be easily over-fitted when they are over-parametered. The popular dropout that drops feature units randomly can't always work well for CNNs, due to the problem of under-dropping. To eliminate this problem, some str
Convolutional neural networks (CNNs) can be easily over-fitted when they are over-parametered. The popular dropout that drops feature units randomly can't always work well for CNNs, due to the problem of under-dropping. To eliminate this problem, some str
