Analyzing Filters Toward Efficient ConvNet

Deep convolutional neural network (ConvNet) is a promising approach for high-performance image classification. The behavior of ConvNet is analyzed mainly based on the neuron activations, such as by visualizing them... (read more)

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Methods used in the Paper


METHOD TYPE
Average Pooling
Pooling Operations
Global Average Pooling
Pooling Operations
1x1 Convolution
Convolutions
ReLU
Activation Functions
Batch Normalization
Normalization
Bottleneck Residual Block
Skip Connection Blocks
Max Pooling
Pooling Operations
Kaiming Initialization
Initialization
Residual Connection
Skip Connections
Residual Block
Skip Connection Blocks
ResNet
Convolutional Neural Networks
Convolution
Convolutions