Výsledky vyhledávání - "autoencoder convolutional neural network"

Image dehazing using autoencoder convolutional neural network Autor Singh, Richa, Dubey, Ashwani Kumar, Kapoor, Rajiv

“…In hazy weather, the image in the scene suffers from noise which makes them less visible and to detect an object in hazy weather becomes a challenging task in…”
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BEARING FAULT DETECTION BY USING AUTOENCODER CONVOLUTIONAL NEURAL NETWORK Autor Kysarin, M. K.

“…Context. Bearings are an important part for the functioning of various means of transportation. They have the property of wear and failure, which requires…”
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Rapid and Accurate Prediction of Soil Texture Using an Image-Based Deep Learning Autoencoder Convolutional Neural Network Random Forest (DLAC-CNN-RF) Algorithm Autor Zhao, Zhuan, Feng, Wenkang, Xiao, Jinrui, Liu, Xiaochu, Pan, Shusheng, Liang, Zhongwei

“… This study proposed a flexible smartphone-based machine vision system using a deep learning autoencoder convolutional neural network random forest (DLAC-CNN-RF…”
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Deep reference autoencoder convolutional neural network for damage identification in parallel steel wire cables Autor Xue, Songling, Sun, Yidan, Su, Teng, Zhao, Xiaoqing

“… To tackle this issue, we propose an unsupervised deep learning damage identification technique called Deep Reference Autoencoder Convolutional Neural Network (DRACNN…”
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AutoEncoder Convolutional Neural Network for Pneumonia Detection Autor Nosa-Omoruyi, Michael, Oghenekaro, Linda U

“…This study presents an innovative approach utilising Autoencoder Convolutional Neural Networks (AECNNs…”
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Computer-Aided Diagnosis of Acute Lymphoblastic Leukemiaby Using a Novel CAE-CNN Framework Autor Mansoor Alhammadi, Mohammed

“…Acute lymphoblastic leukemia (ALL) is a main health problem throughout the world. Therefore, fast and exact diagnosis is the most crucial factor for providing…”
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Within-project and cross-project just-in-time defect prediction based on denoising autoencoder and convolutional neural network Autor Zhu, Kun, Zhang, Nana, Ying, Shi, Zhu, Dandan

“…Just-in-time defect prediction is an important and useful branch in software defect prediction. At present, deep learning is a research hotspot in the field of…”
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Seismic Random Noise Attenuation Using a Tied-Weights Autoencoder Neural Network Autor Zhou, Huailai, Guo, Yangqin, Guo, Ke

“…Random noise is unavoidable in seismic data acquisition due to anthropogenic impacts or environmental influences. Therefore, random noise suppression is a…”
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Improving the Efficiency of Automated Latent Fingerprint Identification Using Stack of Convolutional Auto-encoder Autor Chhabra, Megha, Shukla, Manoj Kumar, Ravulakollu, Kiran Kumar

“…In this paper, a method for improving the efficiency of latent fingerprint segmentation and detection system is presented. Structural detection and precise…”
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Impact of Patch-Size on Classification Accuracy of Latent Fingerprint Image in Stacked Convolutional Auto-encoder based Segmentation and Detection Autor Chhabra, Megha, Shukla, Manoj Kumar, Ravulakollu, Kiran Kumar

“…Latent fingerprints are (un)intentional finger skin impressions left as ridge patterns at crime scenes. The significant challenge in latent fingerprint…”
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Video Analytics in Train Cabin Using Deep Learning Autor Hsien, Lur Tze, Atmosukarto, Indriyati

“… Our proposed solution is to process extracted images from train cabin security footages using Convolutional Denoising Autoencoder-Convolutional Neural Network (CDAE-CNN…”
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Time-Averaged Wind Turbine Wake Flow Field Prediction Using Autoencoder Convolutional Neural Networks Autor Zhang, Zexia, Santoni, Christian, Herges, Thomas, Sotiropoulos, Fotis, Khosronejad, Ali

“…A convolutional neural network (CNN) autoencoder model has been developed to generate 3D realizations of time-averaged velocity in the wake of the wind…”
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Detection of Heavy Metal Copper Stress in Apple Rootstocks Using Surface-Enhanced Raman Spectroscopy Autor Li, Junmeng, Guan, Hongpu, Zhou, Yibo, Pei, Shouhao, Yu, Keqiang, Zhao, Yanru

“… to develop a one-dimensional stacked autoencoder convolutional neural network (1D-SAE-CNN) for classifying Cu stress levels, resulting in evaluation indices greater than 0.9…”
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Modified kernel MLAA using autoencoder for PET-enabled dual-energy CT Autor Li, Siqi, Wang, Guobao

“…Combined use of PET and dual-energy CT provides complementary information for multi-parametric imaging. PET-enabled dual-energy CT combines a low-energy X-ray…”
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Prediction of Parkinson Disease using Autoencoder Convolutional Neural Networks Autor Hema, M S, Maheshprabhu, R, Nageswara Guptha, M, Mary G, Prema Arokia, Sharma, Aditi

“…Parkinson's Disease (PD) diagnosis is a challenging task for doctors because of the non-availability of separate testing and prediction methodology. PD is…”
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End-to-end deep learning for smart maritime threat detection: an AE–CNN–LSTM-based approach Autor Anuja, R., Annrose, J.

“… To improve detection fidelity under these conditions, we present a hybrid Autoencoder–Convolutional Neural Network…”
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Breast tumor segmentation in ultrasound using distance-adapted fuzzy connectedness, convolutional neural network, and active contour Autor Biesok, Marta, Juszczyk, Jan, Badura, Pawel

“… The core of the three-stage method is based on the autoencoder convolutional neural network…”
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Improving Short-term Daily Streamflow Forecasting Using an Autoencoder Based CNN-LSTM Model Autor Kumshe, Umar Muhammad Mustapha, Abdulhamid, Zakariya Muhammad, Mala, Baba Ahmad, Muazu, Tasiu, Muhammad, Abdullahi Uwaisu, Sangary, Ousmane, Ba, Abdoul Fatakhou, Tijjani, Sani, Adam, Jibril Muhammad, Ali, Mosaad Ali Hussein, Bello, Aliyu Uthman, Bala, Muhammad Muhammad

“…), and the Long Short Term Memory (LSTM) networks. Thirty years daily dataset were served to the Autoencoder Convolutional Neural Network Long Short Term Memory (AE-CNN-LSTM…”
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A survey of deep neural network architectures and their applications Autor Liu, Weibo, Wang, Zidong, Liu, Xiaohui, Zeng, Nianyin, Liu, Yurong, Alsaadi, Fuad E.

“… An up-to-date overview is provided on four deep learning architectures, namely, autoencoder, convolutional neural network, deep belief network, and restricted Boltzmann machine…”
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Multimodal NASH prognosis using 3D imaging flow cytometry and artificial intelligence to characterize liver cells Autor Subramanian, Ramkumar, Tang, Rui, Zhang, Zunming, Joshi, Vaidehi, Miner, Jeffrey N., Lo, Yu-Hwa

“… regression with disease progression. By developing a customized autoencoder convolutional neural network (CNN…”
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