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dnn by liangfu

A light-weight yet efficient framework for deep learning. Download .tar.gz. The Deep Neural Nets (DNN) library is a deep learning framework designed to be small in size, computationally efficient and portable. We started the project as a fork of the popular OpenCV. The following features have been implemented:. Mini-batch based learning, with OpenMP support. YAML based network definition. Gradient checking for all implemented layers. The following modules are implemented in current version:. MaxPooling, ...

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dnn by liangfu | liangfu.github.io Reviews

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A light-weight yet efficient framework for deep learning. Download .tar.gz. The Deep Neural Nets (DNN) library is a deep learning framework designed to be small in size, computationally efficient and portable. We started the project as a fork of the popular OpenCV. The following features have been implemented:. Mini-batch based learning, with OpenMP support. YAML based network definition. Gradient checking for all implemented layers. The following modules are implemented in current version:. MaxPooling, ...

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3 deep neural nets

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10 performs max pooling operation

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dnn by liangfu | liangfu.github.io Reviews

https://liangfu.github.io

A light-weight yet efficient framework for deep learning. Download .tar.gz. The Deep Neural Nets (DNN) library is a deep learning framework designed to be small in size, computationally efficient and portable. We started the project as a fork of the popular OpenCV. The following features have been implemented:. Mini-batch based learning, with OpenMP support. YAML based network definition. Gradient checking for all implemented layers. The following modules are implemented in current version:. MaxPooling, ...

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liangfu.github.io

dnn by liangfu

A light-weight yet efficient framework for deep learning. Download .tar.gz. The Deep Neural Nets (DNN) library is a deep learning framework designed to be small in size, computationally efficient and portable. We started the project as a fork of the popular OpenCV. The following features have been implemented:. Mini-batch based learning, with OpenMP support. YAML based network definition. Gradient checking for all implemented layers. The following modules are implemented in current version:. MaxPooling, ...

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