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…”
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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…”
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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…”
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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…”
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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…”
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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…”
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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…”
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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…”
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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…”
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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…”
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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…”
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Enhancing transfer performance across datasets for brain-computer interfaces using a combination of alignment strategies and adaptive batch normalization by Xu, Lichao, Xu, Minpeng, Ma, Zhen, Wang, Kun, Jung, Tzyy-Ping, Ming, Dong

“…). However, current TL and DL algorithms are usually validated within a single dataset, assuming that data of the test subjects are acquired under the same condition as that of training (source) subjects…”
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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…”
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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…”
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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…”
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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…”
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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…”
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Adaptive Scaling Filter Pruning Method for Vision Networks With Embedded Devices by Ko, Hyunjun, Kang, Jin-Ku, Kim, Yongwoo

“… because it only performs pruning once on the unpruned network. Therefore, in this paper, we utilize a single learning process and propose an adaptive scaling method…”
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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…”
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The Neural Network of One-Dimensional Convolution-An Example of the Diagnosis of Diabetic Retinopathy by Sun, Yunlei

“…Diabetes is a serious threat to health development, because diabetes is a disease that caused most other diseases (complications). Diabetic retinopathy is the…”
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