...., 2018). On the other hand, deep learning has achieved remarkable success in image recognition (LeCun et al., 2015), among which convolutional neural network (CNN) is the most widely used. Based on CNN, a series of deep learning methods are produced, such as AlexNet (Krizhevsky et al...

... the fault identification and classification with the optimized convolutional neural network. After the nonstationary vibration signal passes the time-frequency transform, the relationship between frequency and amplitude can be highlighted more. In traditional bearing fault diagnosis, time-frequency...

... 2023 © Emerald Publishing Limited 2023 Emerald Publishing Limited Licensed re-use rights only Hot-rolled steel strip Surface defect classification Convolutional neural network Mixed attention mechanism Network model comparison method The morphology of the characteristics...

...Jianbin Xiong; Jinji Nie; Jiehao Li Purpose This paper primarily aims to focus on a review of convolutional neural network (CNN)-based eye control systems. The performance of CNNs in big data has led to the development of eye control systems. Therefore, a review of eye control systems based...

... and shadows becomes a challenge. Design/methodology/approach A new learning framework based on an integration of extreme learning machine (ELM) and an inception structure named multiscale ELM is proposed, making full use of the advantages that ELM has faster convergence and convolutional neural network...

...Jiang Daqi; Wang Hong; Zhou Bin; Wei Chunfeng Purpose This paper aims to save time spent on manufacturing the data set and make the intelligent grasping system easy to deploy into a practical industrial environment. Due to the accuracy and robustness of the convolutional neural network...