Design of environment art design element mining system based on deep learning

2021 ◽  
Vol 7 (5) ◽  
pp. 4111-4121
Author(s):  
Peng Changrong ◽  
Song Nan ◽  
Zhang Xiaodong ◽  
Ma Yichu ◽  
Luo Chencheng
Keyword(s):  
Deep Learning ◽  
Design Method ◽  
Design Element ◽  
Environmental Art ◽  
Application Process ◽  
Mining System ◽  
Operation Algorithm ◽  
Hardware Configuration ◽  
Art Design ◽  
And Function

Combined with the development requirements of current environmental art mining system, the design method of environmental art design element mining system based on deep learning is optimized, and the hardware configuration of environmental art design element mining system is introduced. Combined with the principle of deep learning, the system software operation algorithm and function are improved, so as to improve the effect of environmental art design element mining, Ensure the operation effect of the system to the greatest extent. Finally, the experiment proves that the environment art design element mining system based on deep learning has high effectiveness in the practical application process, which can better guide the design of environment art and fully meet the research requirements.

scholarly journals The Inventory Control System of Reverse Logistics for E-Commerce Packaging Recovery Based on BP Neural Network

2022 ◽  
Vol 16 ◽  
pp. 413-425
Author(s):  
Zhidan Qin
Keyword(s):  
Neural Network ◽  
Control System ◽  
Inventory Control ◽  
Bp Neural Network ◽  
Reverse Logistics ◽  
Application Process ◽  
Before And After ◽  
Operation Algorithm ◽  
Hardware Configuration ◽  
Reverse Logistics Management

The paper combines BP neural network to optimize the control system of e-commerce packaging and reverse logistics inventory. Through improving the hardware configuration structure of the system, the system can be improved and the operation effect of the system can be improved. The software flow and operation algorithm of the storage control system of e-commerce packaging recycling reverse logistics are optimized step by step, and the logistics is delivered by following the vehicle on the spot and visiting the logistics The distribution personnel collect the relevant data and data in the process of logistics and transportation, draw the reverse logistics business flow chart, point out the situation of reverse logistics before and after the goods distribution and distribution due to the cancellation of orders or transactions by customers, and the application for return of goods after the transaction. Meanwhile, it points out that the sales return operation site in the reverse logistics management process is chaotic and not formed the clear business process specification and other problems can effectively control the reverse logistics inventory of e-commerce packaging recovery. Finally, the experiment proves that the e-commerce packaging recycling reverse logistics inventory control system is more practical in the practical application process, and fully meets the research requirements.

scholarly journals Fully Automated Colorimetric Analysis of the Optic Nerve Aided by Deep Learning and Its Association with Perimetry and OCT for the Study of Glaucoma

2021 ◽  
Vol 10 (15) ◽  
pp. 3231
Author(s):  
Marta Gonzalez-Hernandez ◽  
Daniel Gonzalez-Hernandez ◽  
Daniel Perez-Barbudo ◽  
Paloma Rodriguez-Esteve ◽  
Nisamar Betancor-Caro ◽  
...  
Keyword(s):  
Distribution Function ◽  
Deep Learning ◽  
Optic Nerve ◽  
Roc Analysis ◽  
Operating Characteristic ◽  
Learning Models ◽  
Colorimetric Analysis ◽  
Cirrus Oct ◽  
And Function ◽  
Usual Pattern

Background: Laguna-ONhE is an application for the colorimetric analysis of optic nerve images, which topographically assesses the cup and the presence of haemoglobin. Its latest version has been fully automated with five deep learning models. In this paper, perimetry in combination with Laguna-ONhE or Cirrus-OCT was evaluated. Methods: The morphology and perfusion estimated by Laguna ONhE were compiled into a “Globin Distribution Function” (GDF). Visual field irregularity was measured with the usual pattern standard deviation (PSD) and the threshold coefficient of variation (TCV), which analyses its harmony without taking into account age-corrected values. In total, 477 normal eyes, 235 confirmed, and 98 suspected glaucoma cases were examined with Cirrus-OCT and different fundus cameras and perimeters. Results: The best Receiver Operating Characteristic (ROC) analysis results for confirmed and suspected glaucoma were obtained with the combination of GDF and TCV (AUC: 0.995 and 0.935, respectively. Sensitivities: 94.5% and 45.9%, respectively, for 99% specificity). The best combination of OCT and perimetry was obtained with the vertical cup/disc ratio and PSD (AUC: 0.988 and 0.847, respectively. Sensitivities: 84.7% and 18.4%, respectively, for 99% specificity). Conclusion: Using Laguna ONhE, morphology, perfusion, and function can be mutually enhanced with the methods described for the purpose of glaucoma assessment, providing early sensitivity.

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