Výsledky vyhledávání - "deep stacked sparse autoencoder"

Breath analysis based early gastric cancer classification from deep stacked sparse autoencoder neural network Autor Aslam, Muhammad Aqeel, Xue, Cuili, Chen, Yunsheng, Zhang, Amin, Liu, Manhua, Wang, Kan, Cui, Daxiang

“…Deep learning is an emerging tool, which is regularly used for disease diagnosis in the medical field. A new research direction has been developed for the…”
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Secondary Pulmonary Tuberculosis Identification Via pseudo-Zernike Moment and Deep Stacked Sparse Autoencoder: Secondary Pulmonary Tuberculosis Identification Via pseudo-Zernike Moment and Deep Stacked Sparse Autoencoder Autor Wang, Shui-Hua, Satapathy, Suresh Chandra, Zhou, Qinghua, Zhang, Xin, Zhang, Yu-Dong

“…) as the feature extractor and deep stacked sparse autoencoder (DSSAE) as the classifier. In addition, 18-way data augmentation is employed to avoid overfitting…”
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Pseudo Zernike Moment and Deep Stacked Sparse Autoencoder for COVID-19 Diagnosis Autor Zhang, Yu-Dong, Attique Khan, Muhammad, Zhu, Ziquan, Wang, Shui-Hua

“… Afterward, we use a deep-stacked sparse autoencoder (DSSAE) as the classifier. Besides, multiple-way data augmentation is chosen to overcome overfitting…”
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Five-category classification of pathological brain images based on deep stacked sparse autoencoder Autor Jia, Wenjuan, Muhammad, Khan, Wang, Shui-Hua, Zhang, Yu-Dong

“… Then, we used deep stacked sparse autoencoder with minibatch scaled conjugate gradient to train the network, and the softmax…”
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K-Means Clustering Optimizing Deep Stacked Sparse Autoencoder Autor Bi, Yandong, Wang, Peng, Guo, Xuchao, Wang, Zhijun, Cheng, Shuhan

“… How to speed up training is a problem deserving of study. In order to accelerate training, K-means clustering optimizing deep stacked sparse autoencoder (K-means sparse SAE…”
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Optimal Deep Stacked Sparse Autoencoder Based Osteosarcoma Detection and Classification Model Autor Fakieh, Bahjat, AL-Ghamdi, Abdullah S. AL-Malaise, Ragab, Mahmoud

“…Osteosarcoma is a kind of bone cancer which generally starts to develop in the lengthy bones in the legs and arms. Because of an increase in occurrence of…”
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Single stuck-at-faults detection using test generation vector and deep stacked-sparse-autoencoder Autor Malihi, Leila, Malihi, Razieh

“… This data-based method detects hundreds of single stuck-at faults in the ALU circuits, utilizing deep stacked-sparse-autoencoder (SSAE…”
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Hybrid Embedded Deep Stacked Sparse Autoencoder with w_LPPD SVM Ensemble Autor Li, Yongming, Yan, Lei, Wang, Pin, Liu, Yuchuan

“…Deep learning is a kind of feature learning method with strong nonliear feature transformation and becomes more and more important in many fields of artificial…”
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Deep Stacked Sparse Autoencoders – A Breast Cancer Classifier Autor Munir, Muhammad Asif, Aslam, Muhammad Aqeel, Shafique, Muhammad, Ahmed, Rauf, Mehmood, Zafar

“… In this article, Deep Stacked Sparse Autoencoders for breast cancer diagnostic and classification are proposed…”
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Optimizing MobileNetV2 for improved accuracy in early gastric cancer detection based on dynamic pelican optimizer Autor Zhou, Guoping, He, Qiyu, Liu, Xiaoli, Kai, Xinghua, Cao, Weikang, Ding, Junning, Zhuang, Bufeng, Xu, Shuhua, Thwin, Myo

“…This paper presents an innovative framework for the automated diagnosis of gastric cancer using artificial intelligence. The proposed approach utilizes a…”
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Myocardium Detection by Deep SSAE Feature and Within-Class Neighborhood Preserved Support Vector Classifier and Regressor Autor Niu, Yanmin, Qin, Lan, Wang, Xuchu

“… Then it adopts a deep stacked sparse autoencoder (SSAE) network to learn the discriminative deep feature to represent the regions…”
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A hybrid metaheuristic federated learning approach based attack detection system for multi-cloud environment Autor Verma, Rashmi, Jailia, Manisha

“…Multi-cloud strategy allows distribution of workloads across multiple cloud platforms. These cloud platforms that are served include, public, private, as well…”
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Sequential Feature-Augmented Deep Multilabel Learning for Compound Fault Diagnosis of Rotating Machinery With Few Labeled and Imbalanced Data Autor Wang, Xinyue, Xu, Gangyan, Zhou, Ziye, Zou, Yuli

“… Specifically, by integrating convolutional neural network with convolutional long short-term memory, a deep stacked sparse autoencoder is developed to extract high-dimensional marginal and time…”
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Duck optimization with enhanced capsule network based citrus disease detection for sustainable crop management Autor Arthi, A., Sharmili, N., Althubiti, Sara A., Laxmi Lydia, E., Alharbi, Meshal, Alkhayyat, Ahmed, Gupta, Deepak

“…Sustainable agriculture methodology seeks to apply natural resources whereby they could reconstruct their productive capacity and minimise adverse effects on…”
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Automatic Vertebrae Localization and Identification by Combining Deep SSAE Contextual Features and Structured Regression Forest Autor Wang, Xuchu, Zhai, Suiqiang, Niu, Yanmin

“… to localize and identify vertebrae by combining deep stacked sparse autoencoder (SSAE) contextual features and structured regression forest (SRF…”
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Learning Deep Latent Representation of Color Images Using Autoencoders for Efficient Image Retrieval Autor Kale, Mandar, Mukhopadhyay, Sudipta

“… In this light, the article proposes a feature learning framework using a deep stacked sparse autoencoder (SAE…”
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Learning deep neural networks for node classification Autor Li, Bentian, Pi, Dechang

“…•Propose a novel deep neural network method for node classification.•The model could overcome the existing problem of only getting the suboptimal solution.•A…”
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