On the basis of data-driven, this paper fitted two models of different states which according to the initial data of China's fight against COVID-19 epidemic. Depending on the stage of the outbreak, we applied the ...
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ISBN:
(数字)9781728159225
ISBN:
(纸本)9781728159232
On the basis of data-driven, this paper fitted two models of different states which according to the initial data of China's fight against COVID-19 epidemic. Depending on the stage of the outbreak, we applied the two models to predict the cumulative number of confirmed covid-19 cases in the United States and Italy in the early stages of the outbreak. In the early days of the outbreak, the number of confirmed cases in the United States is expected to reach 250000 to 300,000. And if the control measures are effective, there is a high probability that the number of confirmed diagnoses in Italy will not exceed 210,000. Unity can put the difficult away. We should believe that only when countries respect each other and strengthen cooperation can they finally defeat the epidemic.
this paper focuses on the master and doctoral dissertations on "data-drivencontrol", "model-free adaptive control" and "iterative learningcontrol" collected by Chinese National Knowledg...
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ISBN:
(数字)9781728159225
ISBN:
(纸本)9781728159232
this paper focuses on the master and doctoral dissertations on "data-drivencontrol", "model-free adaptive control" and "iterative learningcontrol" collected by Chinese National Knowledge Infrastructure (CNKI) database before October 31, 2019. Exploiting big data technology, three topics mentioned above are studied in the form of mapping knowledge graph by Python, ROSTCM and Ucinet social network analysis software. Our research mainly explores and analyzes the temporal evolution as well as development status of the subject words, the cultivation organizations, the fund support, the co-occurrence of key words, the co-occurrence of dissertations topics and the characteristics of supervisor -student relationship, etc., which can provide references for relevant research fields.
this paper proposes a license plate recognition method based on YOLOv8-Pose and E-LPRNet for complex scenarios such as urban roadside and road inspection. E-LPRNet is a character recognition network formed by modifyin...
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ISBN:
(数字)9798350361674
ISBN:
(纸本)9798350361681
this paper proposes a license plate recognition method based on YOLOv8-Pose and E-LPRNet for complex scenarios such as urban roadside and road inspection. E-LPRNet is a character recognition network formed by modifying the activation function of the backbone network in LPRNet (License Plate Recognition Network). this method also includes a license plate correction feature, which accurately recognizes license plate characters even when the plates are at large angles, thereby increasing the recognition accuracy. A series of experiments using a large license plate dataset verified the effectiveness of this method.
the paper presents a novel approach for human-robot skill transferring. Firstly, we propose a method that combines dynamic time warping (DTW) withthe Gaussian mixture model (GMM) to reconstruct the demonstrated skill...
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ISBN:
(数字)9798350361674
ISBN:
(纸本)9798350361681
the paper presents a novel approach for human-robot skill transferring. Firstly, we propose a method that combines dynamic time warping (DTW) withthe Gaussian mixture model (GMM) to reconstruct the demonstrated skills, including reference path and pose, for each workpiece. Secondly, we integrate hand-eye coordination to facilitate dataset creation and employ YOLOv8 for model training. Finally, we utilize a neural network to obtain the current workpiece's category and pose information and then transform the previous skills into the current workpiece coordinate system. the effectiveness and robustness of our proposed method have been validated on a 7-DOF Sawyer robot equipped with a camera.
In this paper, a novel abnormal behavior analysis algorithm based on YOLOv8 is proposed for the target recognition problem of guide robot dog. the algorithm is based on the human posture estimation model of YOLOv8 for...
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ISBN:
(数字)9798350361674
ISBN:
(纸本)9798350361681
In this paper, a novel abnormal behavior analysis algorithm based on YOLOv8 is proposed for the target recognition problem of guide robot dog. the algorithm is based on the human posture estimation model of YOLOv8 for abnormal behavior analysis, and by extracting the coordinate information of the key points of the human body, it can make conditional decisions on abnormal behaviors such as falling forward, backward and sideways, so as to realize the real-time monitoring of the blind people and send out alarms in time. the proposed algorithm ensures the accuracy and speed of the recognition while not taking up a lot of computational resources of the computer. the proposed method is applied to a real quadruped robot platform, and the effectiveness and applicability of the proposed algorithm is verified through a large number of experiments, which in this paper are based on the actual data collected from different human posture pictures.
Prior authorization (or preauthorization) is a control mechanism used by a Health Maintenance Organization (HMO) to minimize the waste of resources by analyzing each medical request. One of the strategies used to opti...
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For vehicle navigation, an inertial navigation system (INS) is often used to assist the global positioning system (GPS);but the positioning accuracy is well known to be sensitive to boththe GPS sampling rate and iner...
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the incidence of skin cancer is increasing globally, with melanoma being the most formidable form of skin cancer. Melanoma originates from melanocytes, which exhibit a high degree of visual similarity. Moreover, dermo...
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ISBN:
(数字)9798350361674
ISBN:
(纸本)9798350361681
the incidence of skin cancer is increasing globally, with melanoma being the most formidable form of skin cancer. Melanoma originates from melanocytes, which exhibit a high degree of visual similarity. Moreover, dermoscopy image data often suffer from hair occlusion and the lesion area appears relatively small in the images, making it challenging for traditional methods to achieve accurate recognition and detection results. In this regard, we propose a YOLOv8 framework based on multi-scale sequence fusion(MSSF) for melanoma detection. this approach enhances the Neck structure of YOLOv8 and improves the network's ability to extract multi-scale information by introducing the Multi-scale Sequence Fusion module. In addition, we implemented a morphological black hat based hair processing method to reduce hair occlusion. In the ISIC datasets, compared withthe unimproved algorithm, the mean average precision(Map) at 50 IoU is increased by 5.7%, Map between 50 and 95 IoU is increased by 7.5%, and the number of parameters is decreased by 12.5%.
the proceedings contain 88 papers. the special focus in this conference is on Interplay Between Natural and Artificial Computation. the topics include: Computing the Missing Lexicon in Students Using Bayesian Networks...
ISBN:
(纸本)9783030196509
the proceedings contain 88 papers. the special focus in this conference is on Interplay Between Natural and Artificial Computation. the topics include: Computing the Missing Lexicon in Students Using Bayesian Networks;control of Transitory Take-Off Regime in the Transportation of a Pendulum by a Quadrotor;improving Scheduling Performance of a Real-Time System by Incorporation of an Artificial Intelligence Planner;convolutional Neural Networks for Olive Oil Classification;an Indoor Illuminance Prediction Model Based on Neural Networks for Visual Comfort and Energy Efficiency Optimization Purposes;using Probabilistic Context Awareness in a Deliberative Planner System;combining data-driven and Domain Knowledge Components in an Intelligent Assistant to Build Personalized Menus;robust Heading Estimation in Mobile Phones;crowding Differential Evolution for Protein Structure Prediction;a Principled Two-Step Method for Example-Dependent Cost Binary Classification;Bacterial Resistance Algorithm. An Application to CVRP;conceptual Description of Nature-Inspired Cognitive Cities: Properties and Challenges;genetic Algorithm to Evolve Ensembles of Rules for On-Line Scheduling on Single Machine with Variable Capacity;multivariate Approach to Alcohol Detection in Drivers by Sensors and Artificial Vision;optimization of Bridges Reinforcements with Tied-Arch Using Moth Search Algorithm;repairing Infeasibility in Scheduling via Genetic Algorithms;application of Koniocortex-Like Networks to Cardiac Arrhythmias Classification;content Based Image Retrieval by Convolutional Neural Networks;deep learning Networks with p-norm Loss Layers for Spatial Resolution Enhancement of 3D Medical Images;analysis of Dogs’s Abandonment Problem Using Georeferenced Multi-agent systems;symbiotic Autonomous systems with Consciousness Using Digital Twins;background Modeling by Shifted Tilings of Stacked Denoising Autoencoders;automatic Image-Based Waste Classification.
the greatest threat to global health is the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-Cov-2) currently. COVID-19 was declared as a global pandemic on March 11, 2020. For this highly contagious disease, the...
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