Search Results - Modified stacked sparse autoencoder*

Nondestructive evaluation of Zn content in rape leaves using MSSAE and hyperspectral imaging by Fu, Lvhui, Sun, Jun, Wang, Simin, Xu, Min, Yao, Kunshan, Zhou, Xin

“…). The dropout mechanism was introduced to improve the stacked sparse autoencoder (SSAE) and named modified SSAE (MSSAE…”
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Modified metaheuristics with stacked sparse denoising autoencoder model for cervical cancer classification by Vaiyapuri, Thavavel, Alaskar, Haya, Syed, Liyakathunisa, Aljohani, Eman, Alkhayyat, Ahmed, Shankar, K., Kumar, Sachin

“…•Propose modified firefly optimization algorithm for hyperparameter tuning.•Validate the performance of proposed model on Herlev database…”
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Tool Wear Prediction via Multidimensional Stacked Sparse Autoencoders With Feature Fusion by Shi, Chengming, Luo, Bo, He, Songping, Li, Kai, Liu, Hongqi, Li, Bin

“… stacked sparse autoencoders is used for feature fusion and deeper features learning. And a modified loss function is applied that improves the learning ability…”
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Modified Stacked Autoencoder Using Adaptive Morlet Wavelet for Intelligent Fault Diagnosis of Rotating Machinery by Shao, Haidong, Xia, Min, Wan, Jiafu, de Silva, Clarence W.

“… In this article, a modified stacked autoencoder (MSAE) that uses adaptive Morlet wavelet is proposed to automatically diagnose various fault types and severities of rotating machinery…”
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A Structure for Automatically Extracting and Identifying Internal Overvoltage Measured in Distribution Networks Based on FSWT-SSAE by Zhang, Xun, Zhang, Han, Xie, Rongbin, Fu, Zhengzheng, Zhao, Lijin, Zeng, Huarong, Wen, Yi, Sima, Wenxia

“… The measured overvoltage feature automatically extraction and classification is achieved based on modified Stacked Sparse Autoencoders…”
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Infrared and Visible Image Fusion Based on Deep Decomposition Network and Saliency Analysis by Jian, Lihua, Rayhana, Rakiba, Ma, Ling, Wu, Shaowu, Liu, Zheng, Jiang, Huiqin

“…). First, the modified residual dense network (MRDN) is trained with a publicly available dataset to learn the decomposition process…”
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Denoising Letter Images from Scanned Invoices Using Stacked Autoencoders by Ibrahim, Muhammad, Hanif, Muhammad, Ahmad, Shabir, Jamil, Faisal, Sehar, Tayyaba, Lee, YunJung, Kim, DoHyeun

“… This affects the OCR (optical character recognition) detection accuracy. In this paper, letter data obtained from images of invoices are denoised using a modified autoencoder based deep learning method…”
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Filtering normal papanicolaou smear with multi-instance learning by Jie Wang, Xun Liu, Yunjie Chen, Yuan Liu, Lei Pan, Huijuan Zhang, Xiang Ji, Su Zhang

“…). We tried and compared several feature extraction methods, including textural features, manual features and Stacked sparse autoencoder(SSAE…”
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Modified Bald Eagle Search Algorithm with Deep Learning-Driven Sleep Quality Prediction for Healthcare Monitoring Systems by Alabdan, Rana, Mengash, Hanan Abdullah, Maray, Mohammed, Alotaibi, Faiz, Abdelbagi, Sitelbanat, Mahmud, Ahmed

“… In this aspect, the article offers the design of a Modified Bald Eagle Search Algorithm with Deep Learning-Driven Sleep Quality Prediction (MBES-DLSQP…”
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A New Pan-Sharpening Method With Deep Neural Networks by Huang, Wei, Xiao, Liang, Wei, Zhihui, Liu, Hongyi, Tang, Songze

“… Inspired by this observation, a modified sparse denoising autoencoder (MSDA) algorithm is proposed to train the relationship between high-resolution (HR…”
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Using Multiple-Feature-Spaces-Based Deep Learning for Tool Condition Monitoring in Ultraprecision Manufacturing by Shi, Chengming, Panoutsos, George, Luo, Bo, Liu, Hongqi, Li, Bin, Lin, Xu

“… In this paper, a novel deep learning data-driven modeling framework is presented, which includes a fusion of multiple stacked sparse autoencoders for tool condition monitoring in ultraprecision machining…”
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Secure and Privacy-Preserving Framework for IoT-Enabled Smart Grid Environment by Kumar, Chandan, Chittora, Prakash

“…Due to recent technical breakthroughs in wireless communication and the Internet of Things (IoT), the smart grid (SG) has been recognized as a next-generation…”
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