The icing monitoring of transmission lines is of great significance to prevent freezing
disasters of transmission lines and ensure the security and stability of power system …

Deep neural networks (DNNs) have shown great success in completing complex tasks.
However, DNNs inevitably bring high computational cost and storage consumption due to …

Searching for a more compact network width recently serves as an effective way of channel
pruning for the deployment of convolutional neural networks (CNNs) under hardware …

Searching for a more compact network width recently serves as an effective way of channel
pruning for the deployment of convolutional neural networks (CNNs) under hardware …

Deep neural networks are suffering from over parameterized high storage and high
consumption problems. Pruning can effectively reduce storage and computation costs of …

Deep learning has been widely applied in many fields, such as big data analysis, natural
language processing, and image processing, etc. However, the number of parameters in the …

This thesis presents a comprehensive investigation into Neural Architecture Search (NAS),
an instrumental strategy in the formulation of proficient deep learning models. The study …

Convolutional neural network compression technology plays an extremely important role in
model transplantation and deployment, especially in mobile and embedded hardware …

With the continuous development of the deep learning model, the prediction accuracy of the
model has reached a high enough level. The high memory consumption in the prediction of …

Aiming at the problem of single detection scene and poor detection speed, a multi-threshold
channel pruning method based on L1 regularization is proposed. L1 regularization is …