Application of Rotating Machinery Fault Diagnosis Based on Deep Learning by Wei Cui, Guoying Meng, Aiming Wang, Xinge Zhang, Jun Ding

“…The fault diagnosis technology of rotating machinery is one of the key means to ensure the normal operation of equipment and safe production, which has very important significance. Deep learning is a useful tool for analyzing and processing big data, which has been widely used in various fields. …”
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Feature Extraction and Classification of Music Content Based on Deep Learning by Qianqiu Shi, Young Chun Ko

“…To study the use of in-depth training in extracting and classifying the content of music samples, the work offers an algorithm for identifying and classifying musical genres based on a deep network of beliefs, enabling it to be used to extract and classify traditional Chinese musical instruments, and using real-world experiments to test its performance after training. …”
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Analysis of the Application of Deep Learning in Model Reconstruction of Ancient Buildings by Zhihong Wang, Hao Xiong

“…With the rapid development of interactive 3D graphics technology, as well as the growing demand for virtual reality, digital urbanization and digital cultural heritage protection and time-consuming and inefficient traditional artificial building modeling methods have been far from meeting the rapid and intelligent needs of the application market and automatic. …”
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Blood cancer prediction model based on deep learning technique by Amr I. Shehta, Mona Nasr, Alaa El Din M. El Ghazali

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Multimodal Deep Feature Fusion (MMDFF) for RGB-D Tracking by Ming-xin Jiang, Chao Deng, Ming-min Zhang, Jing-song Shan, Haiyan Zhang

“…We propose a novel RGB-D tracker based on multimodal deep feature fusion (MMDFF) in this paper. MMDFF model consists of four deep Convolutional Neural Networks (CNNs): Motion-specific CNN, RGB- specific CNN, Depth-specific CNN, and RGB-Depth correlated CNN. …”
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Deep Transfer Learning for Biology Cross-Domain Image Classification by Chunfeng Guo, Bin Wei, Kun Yu

“…Recently, due to the record-shattering performance, deep convolutional neural networks (DCNNs) have been used more often in biology image classification. …”
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LEED for Homes: Explanation of the Landscape Irrigation Budget Calculation for Florida by Michael D. Dukes

“…Dukes, explains the landscape irrigation budget found under “Landscaping” in the LEED for Homes Rating System. Published by the UF Department of Agricultural and Biological Engineering, January 2009. …”
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Cull Cow Beef Quality Issues: Cow Condition and Muscling by Amie Imler, Matt Hersom, Todd Thrift, Joel Yelich, Max Irsik

“…This 3-page article is one of the Cull Cow Beef Quality Issues series, which addresses liability and food safety concerns. …”
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Keeping Food Safe: Choosing and Using Food Thermometers in Homes by Claudia L. Peñuela, Amy Simonne, Isabel Valentin-Oquendo

“…Several types of food thermometers are available for purchase and choosing the right one when cooking at home will help to keep food safe for your family. This revised 3-page fact sheet provides specific information on how to use different thermometers in different foods. …”
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Research on Human Pose Capture Based on the Deep Learning Algorithm by Wenbin Xie, Xueyun Gu, Xiuming Li, Luqi Zheng, Guodong Li, Haisheng Lu, Huakang Li

“…A method based on the deep learning algorithm is proposed to accurately capture the posture of the human body. …”
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Analysis of The Role of Deep Learning Models in Image Classification Applications by Li Xiang

“…Traditional methods for image classification, however, have been limited by their slow processing speed, rigidity, and high costs. …”
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Beet Armyworm, Spodoptera exigua (Hübner) (Insecta: Lepidoptera: Noctuidae) by John L. Capinera

“…Published: July 1999. EENY105/IN262: Beet Armyworm, Spodoptera exigua (Hübner) (Insecta: Lepidoptera: Noctuidae) (ufl.edu) …”
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A Comprehensive Survey of Deep Learning Approaches in Image Processing by Maria Trigka, Elias Dritsas

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Modification of the materials of the welded zone in the ultra‑deep penetration mode by Yu. S. Usherenko, S. M. Usherenko, A. L. Tarasevich, A. N. Panko

Subjects: “…ultra‑deep penetration…”
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MAGInet based on deep learning for magnetic multi-parameter inversion by Wudi Wen, Yi Li, Zhongle Liu

“…The results of these experiments demonstrate that the accuracy of multi-parameter prediction for complex structures can reach up to 97.5% under zero-error conditions. Furthermore, the efficacy of the MAGInet inversion approach is contrasted with the traditional, deep, fully connected neural network methodologies. …”
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The Fault Diagnosis of Rolling Bearing Based on Improved Deep Forest by Xiwen Qin, Dingxin Xu, Xiaogang Dong, Xueteng Cui, Siqi Zhang

“…At present, the technology of intelligent identification of bearing mostly relies on deep neural network, which has high requirements for computer equipment and great effort in hyperparameter tuning. …”
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Bayesian deep learning applied to diabetic retinopathy with uncertainty quantification by Masoud Muhammed Hassan, Halbast Rashid Ismail

Subjects: “…Bayesian deep learning…”
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Causal processes of shallow and deep seismicity at Campi Flegrei caldera by Genny Giacomuzzi, Rossella Fonzetti, Aladino Govoni, Pasquale De Gori, Claudio Chiarabba

“…The direct involvement of magma has been invoked to explain the deformation and space/time changes of velocity anomalies at shallow crustal depths. …”
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Probability of Escherichia coli contamination spread in ground beef production by Petko M. Kitanov, Allan R. Willms

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Low-Cost Driver Monitoring System Using Deep Learning by Hady A. Khalil, Sherif A. Hammad, Hossam E. Abd El Munim, Shady A. Maged

Subjects: “…Deep learning…”
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