Search Results - adaptive batch normalization algorithm*

Development of Deep Convolutional Neural Network with Adaptive Batch Normalization Algorithm for Bearing Fault Diagnosis by Fu, Chao, Lin, Hsiung-Cheng, Lv, Qing

“… They, however, may suffer from time-consuming and low versatility. In this paper, a CNN integrated with the adaptive batch normalization (ABN) algorithm (ABN-CNN…”
Get full text

Ball Screw Fault Diagnosis Based on Wavelet Convolution Transfer Learning by Xie, Yifan, Liu, Chang, Huang, Liji, Duan, Hongchun

“…The ball screw is the core component of the CNC machine tool feed system, and its health plays an important role in the feed system and even in the entire CNC…”
Get full text

Adaptive diagnosis of DC motors using R-WDCNN classifiers based on VMD-SVD by Qin, Huabin, Liu, Mingliang, Wang, Jian, Guo, Zijian, Liu, Junbo

“… However, the other disadvantages of these methods are low efficiency and poor accuracy. To address these problems, a new adaptive and intelligent mechanical fault diagnosis method for DC motors based on variational mode decomposition (VMD…”
Get full text

A Migration Learning Method Based on Adaptive Batch Normalization Improved Rotating Machinery Fault Diagnosis by Li, Xueyi, Yu, Tianyu, Li, Daiyou, Wang, Xiangkai, Shi, Cheng, Xie, Zhijie, Kong, Xiangwei

“… To overcome this issue, this paper proposes a bearing fault diagnosis method based on the adaptive batch normalization algorithm, which aims to enhance the generalization ability of the model…”
Get full text

A New Adaptive Intelligent DC motors Fault Diagnosis System Using R-WDCNN Classifier by Xie, Yonghui, Qin, Huabin, Yin, Haihong, Hou, Xujie

“…). Utilizing residual learning techniques, this method adeptly identifies and classifies four distinct types of vibrational signals and is fine-tuned through an adaptive batch normalization algorithm (AdaBN…”
Get full text

A Novel Capsule Network Based on Wide Convolution and Multi-Scale Convolution for Fault Diagnosis by Wang, Yu, Ning, Dejun, Feng, Songlin

“… In addition, the adaptive batch normalization (AdaBN) algorithm is introduced to further enhance the adaptability of WMSCCN…”
Get full text

A Novel Fault Diagnosis Method Under Dynamic Working Conditions Based on a CNN With an Adaptive Learning Rate by Zhai, Xiaodong, Qiao, Fei, Ma, Yumin, Lu, Hong

“… This article studies a new adaptive fault diagnosis (AdaFD) scheme and proposes a deep learning-based model and algorithm to enhance both the timeliness of fault diagnosis and its adaptability to dynamic conditions…”
Get full text

A Lightweight Automatic Wildlife Recognition Model Design Method Mitigating Shortcut Learning by Zhong, Yujie, Li, Xiao, Xie, Jiangjian, Zhang, Junguo

“…Recognizing wildlife based on camera trap images is challenging due to the complexity of the wild environment. Deep learning is an optional approach to solve…”
Get full text

An accurate lightweight algorithm for bearings fault diagnosis based on DPW ATTCNN model by Li, Yongfei

“… The DPW ATTCNN model is improved based on the Adaptive Batch Normalization…”
Get full text

Fault Diagnosis of Rotating Machinery Based on One-Dimensional Deep Residual Shrinkage Network with a Wide Convolution Layer by Li, Shijie, Jiang, Shouda, Gao, Tianyu, Yang, Jingli, Tang, Qing

“… Moreover, an adaptive batch normalization algorithm (AdaBN) is introduced into the diagnosis model to enhance the adaptability to noise…”
Get full text

LightSleepNet: Design of a Personalized Portable Sleep Staging System Based on Single-Channel EEG by Liao, Yiqiao, Zhang, Chao, Zhang, Milin, Wang, Zhihua, Xie, Xiang

“…This brief proposed LightSleepNet - a light-weight, 1-d Convolutional Neural Network (CNN) based personalized architecture for real-time sleep staging, which…”
Get full text

Instance Segmentation Based on Improved Self-Adaptive Normalization by Yang, Sen, Wang, Xiaobao, Yang, Qijuan, Dong, Enzeng, Du, Shengzhi

“…The single batch normalization (BN) method is commonly used in the instance segmentation algorithms…”
Get full text

SlimDL: Deploying ultra-light deep learning model on sweeping robots by Sun, Xudong, Wang, Yu, Liu, Zhanglin, Gao, Shaoxuan, He, Wenbo, Tong, Chao

“… Additionally, we present a pruning algorithm, employing adaptive batch normalization and iterative pruning. Our evaluation…”
Get full text

LightSleepNet: Design of a Personalized Portable Sleep Staging System Based on Single-Channel EEG by Liao, Yiqiao, Zhang, Chao, Zhang, Milin, Wang, Zhihua, Xie, Xiang

“…This paper proposed LightSleepNet - a light-weight, 1-d Convolutional Neural Network (CNN) based personalized architecture for real-time sleep staging, which…”
Get full text

A Fast Inversion of Induction Logging Data in Anisotropic Formation Based on Deep Learning by Zhu, Gaoyang, Gao, Muzhi, Kong, Fanmin, Li, Kang

“… A deep neural network (DNN) architecture combined with an adaptive moment estimation (Adam) optimization algorithm is utilized…”
Get full text

Neural Networks With Linear Adaptive Batch Normalization and Swarm Intelligence Calibration for Real‐Time Gaze Estimation on Smartphones by Zhu, Gancheng, Li, Yongkai, Zhang, Shuai, Duan, Xiaoting, Huang, Zehao, Yao, Zhaomin, Wang, Rong, Wang, Zhiguo

“… The MGazeNet model introduced a linear adaptive batch normalization module to efficiently combine eye and face…”
Get full text

An innovative Multisource Lightweight Adaptive Replayed Online Deep Transfer Learning algorithm for tool wear monitoring by Gao, Zhilie, Chen, Ni, Yang, Yinfei, Li, Liang

“… (Multisource Lightweight Adaptive Replayed Online Deep Transfer Learning). In the MS-LARODTL algorithm, a lightweight convolution layer design is initially adopted, resulting in a reduction of 86.64…”
Get full text

Filter pruning based on evolutionary algorithms for person re-identification by Zhao, Jiaqi, Chen, Ying, Zhong, Yufeng, Zhou, Yong, Yao, Rui, Zhang, Lixu, Xia, Shixiong

“… In this paper, we formally put forward a scheme of filter pruning based on evolutionary algorithms (EAFPruner…”
Get full text

A Lightweight Convolutional Neural Network Model for Concrete Damage Classification using Acoustic Emissions by Zhang, Yuxuan, Bader, Sebastian, Oelmann, Bengt

“… Adaptive moment estimation (Adam) was used as the learning algorithm. Batch normalization and dropout layers were used to solve the overfitting problem generated in earlier versions of the model…”
Get full text

Research on numerical control machine fault diagnosis based on distribution adaptive one-dimensional convolutional neural network by Yuying, Zhang, Yi, Lu, Jing, Zhao

“…Numerical control machine is a high-precision and high-automation equipment, if the problem occurred in operation, it can affect the processing conditions of…”
Get full text