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Removing motion blur using natural image statistics

Removing motion blur using natural image statistics

引用

3rd International conference on Pattern Recognition Applications and Methods, ICPRAM 2014

作者： Herwig, Johannes Linder, Timm Pauli, Josef Intelligent Systems Group University of Duisburg-Essen Bismarckstr. 90 47057 Duisburg Germany

ISBN: (纸本)9789897580185

We tackle deconvolution of motion blur in hand-held consumer photography with a Bayesian framework combining sparse gradient and color priors for regularization. We develop a closed-form optimization utilizing iterated re-weighted least squares (IRLS) with a Gaussian approximation of the regularization priors. The model parameters of the priors can be learned from a set of natural images which resemble common image statistics. We throughly evaluate and discuss the effect of different regularization factors and make suggestions for reasonable values. Both gradient and color priors are current state-of-the-art. In natural images the magnitude of gradients resembles a kurtotic hyper-Laplacian distribution, and the two-color model exploits the observation that locally any color is a linear approximation between some primary and secondary colors. Our contribution is integrating both priors into a single optimization framework and providing a more detailed derivation of their optimization functions. Our re-implementation reveals different model parameters than previously published, and the effectiveness of the color priors alone are explicitly examined. Finally, we propose a context-adaptive parameterization of the regularization factors in order to avoid over-smoothing the deconvolution result within highly textured areas. Copyright © 2014 SCITEPRESS.

关键词： Color

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Research on Online Teaching Emotion Detection based on Federated learning 23

Research on Online Teaching Emotion Detection based on Feder...

引用

3rd International conference on Bioinformatics and intelligent Computing, BIC 2023

作者： Chen, Caiyun Dept. of Intelligent Science and Technology Xiamen University Tan Kah Kee College Xiamen China

ISBN: (纸本)9798400700200

With the integration of artificial intelligence and education, online education has received unprecedented attention. The new infrastructure system is improved, and artificial intelligence is widely used in teaching, management, resource construction and other fields. At present, the research on intelligent education is still focused on improving students' learning efficiency, intelligent education monitoring and other aspects, but there is no relevant research on the evaluation system of AI-assisted teachers' teaching level and effect. In fact, students' learning effect is not only related to their own efforts, advanced educational equipment or not, but also closely related to the education level and style of teachers. We propose a Federated-learning based online teaching emotion recognition detection for teachers. Through the recognition of teachers' teaching emotion, it can realize the auxiliary analysis of the teaching level of teachers, help to find the problems in the process of online teaching and improve the teaching level of teachers. At the same time, on the basis of protecting the privacy security and legal compliance of teachers' teaching data, the Federated learning realization realizes data sharing, joint modeling, and improves the recognition effect. The experimental results show that the modified model can realize the collaborative training of participants under the independent and unbalanced data, and realize the effective recognition of facial emotion in online education teaching of teachers. © 2023 ACM.

关键词： Emotion Recognition

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The learning Task Within Serious Games Simulation: Theoretical Model of Interactive Scenarisation 3

The Learning Task Within Serious Games Simulation: Theoretic...

引用

3rd International conference on intelligent Systems and Advanced Computing Sciences, ISACS 2019

作者： Azmi, Kamal Laraqui, Abderrahmane Boussedra, Faouzi LARGESS Faculty of SJES El-Jadida UCD B.P 356 Morocco

ISBN: (纸本)9781728148137

The new purpose of the 'teacher/accompanying person' at Hassan Ist University is to accompany the learner to be auto-effective regarding learning and communication according to his project of learning. The classic modes of teaching and the classic methodologies of researches on this topic are outdated. The present article so tells our experience in a contextualized way, our methodological repositioning before explaining the steps of a theoretical model which re-configures the phase of the production to favor an accompaniment stimulating the auto-efficacy of the learner. The Training Games and Simulation environment is a better solution for this circumstance. The scenarisation tasks in this type of game is a major issue for the development of self-efficacy;and that will be the goal of this communication. © 2019 IEEE.

关键词： Serious games

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Machine learning Approaches for Prediction of Nutrition Deficiency among Women of Different Age Groups 3

Machine Learning Approaches for Prediction of Nutrition Defi...

引用

3rd International conference on Innovations in Computer Science and Software Engineering, ICONICS 2022

作者： Ali, Javeria Waseemullah Khan, Masood Ahmed Khan, Najeed Ahmed NED University of Engineering and Technology Dept of Mechanical Engineering Karachi Pakistan NED University of Engineering and Technology Dept of Computer Science and Information Technology Karachi Pakistan

ISBN: (纸本)9781665461412

Malnutrition has been a major health concern widely especially when it comes to Asian women. Due to the lack of access to healthcare facilities for the women of underdeveloped and developing countries, the women of these regions suffer the most. For this purpose, an effort is made to predict the nutritional status of the women in one such country Pakistan. The research aims to build an intelligent model for the prediction of nutritional deficiency among women. Machine learning algorithms namely Support vector machine, random forest, Logistic Regression, KNN, and Naïve Bayes have been used to build the nutritional predictor in relevance to Pakistani women. The result shows that the Random Forest Model has the highest accuracy and is the most suitable one for future predictions. The model would enable us to know the health condition in particular of Pakistani women. The testing of the model on a similar dataset has further confirmed the reliability factor. © 2022 IEEE.

关键词： Forecasting

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A transfer learning fusion model for semi-physical simulation and filed accuracy data 3

A transfer learning fusion model for semi-physical simulatio...

引用

3rd International conference on Artificial Intelligence, Information Processing and Cloud Computing, AIIPCC 2022

作者： Geng, Huapin Li, Xiaolu Li, Ziwei Suo, Bin Science and Technology on Complex System Control and Intelligent Agent Cooperative Laboratory Beijing100083 China Beijing Electro-mechanical Engineering Institute Beijing100083 China School of Information Engineering Southwest University of Science and Technology Mianyang621010 China

ISBN: (纸本)9783800759330

In order to solve the problem that the accuracy assessment of a single data source is subject to multiple constraints, data fusion reliability evaluation model based on transfer learning was established. Take the high-confidence but small sample field test data as the target domain, the semi-simulation test data as the source domain. Using the principal component analysis to extract the features separately, then embedding the feature distribution in glassman manifold space as two points, construct geodesic flow curve to attach them. So as to achieve data fusion, map the source and target domain to a common space through the geodesic flow curve. Accuracy evaluation can be calculated by constructing confidence region of semi-simulation data. The example verifies the feasibility and effectiveness of this model. © VDE VERLAG GMBH.

关键词： Data fusion

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optimization of Conversion Method from Free-form Surface to Ruled Surface of Centrifugal Compressor Impellers 3

Optimization of Conversion Method from Free-form Surface to ...

引用

3rd International conference on Applied Mathematics, Modelling, and intelligent Computing, CAMMIC 2023

作者： Guo, Feng Li, Qinan Zhang, Xuezhi Xu, Jincheng Zong, Xuyang Wang, Jie Systems Engineering Research Institute of CSSC 1 Fengxian East Road Beijing100094 China

ISBN: (数字)9781510667617

ISBN: (纸本)9781510667600

In the process of converting the free-form surface of the blade of the centrifugal compressor impeller to the ruled surface, the cutter rotation method is a rotating search with the search center as the center of the circle and the radius is sequentially changed. The search in the meridian and circumferential directions of the blade is not completely independent, resulting in a certain range Search blind spots. We propose a new search method. The search of the cutter in the blade meridian direction and the tangential direction are independent of each other, which further expands the search range of the best position of the flank milling ruled surface cutter. The mathematical calculation method of this method is introduced, and two different free-form surface centrifugal compressor impellers are used as test examples. The results show that this method can improve the accuracy of transforming the free-form surface of the impeller blade into a ruled surface. © 2023 SPIE.

关键词： Centrifugation

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Detecting Criminal Activities from CCTV by using Object Detection and machine learning Algorithms 3

Detecting Criminal Activities from CCTV by using Object Dete...

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3rd IEEE International conference on intelligent Technologies, CONIT 2023

作者： Singla, Surbhi Chadha, Raman CSE AIML University Institute of Engineering Chandigarh University Mohali India CSE University Institute of Engineering Chandigarh University Mohali India

ISBN: (纸本)9798350338607

Now, a day's Crime in every country is increasing day by day. Generally, Every day we listen to the news of different crimes of different categories like rape, assault, Kidnapping ,Robbery ,ATM Theft, Murders etc happening in different states, cities , countries. Almost all the newspapers, TV channels', social media are filled with the news of Criminal activities happening all around the Whole World. In earlier times there is no method to detect Crime. After That the CCTV cameras were used to detect Crimes. But Watching these Videos manually by humans for detecting crimes is a very time Consuming process especially in today's world of Artificial Intelligence and Machine *** this crime detection in CCTV surveillance becomes an important area of research in the field of machine learning. So, there is a very urgent need of the intelligent system which will detect the crimes from the real time CCTV Feed and classify them and provides an alert system to the nearest police stations and ambulances etc. So, that system will help in reducing the crime rate in any country. This paper reviews all prior research in this area, including approaches for object recognition and finding priority frames, techniques and algorithms like Yolo used to detect crimes , various datasets used and algorithms used to analyze crime data and train the *** covers the various recent trends in researches in this field and analyzing the challenges faced and various research gaps and this paper also discuss how we can overcome these gaps in research so as to develop a better intelligence surveillance system in ml field. © 2023 IEEE.

关键词： Object detection

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A fault feature extraction method for machine health diagnosis using manifold learning

A fault feature extraction method for machine health diagnos...

引用

2012 3rd International conference on Digital Manufacturing and Automation, ICDMA 2012

作者： Liu, Yongbin Zhu, Lin He, Qingbo Zhang, Ping Zhao, Jiwen School of Electrical Engineering and Automation Anhui University Hefei Anhui 230039 China Department of Precision Machinery and Precision Instrumentation University of Science and Technology of China Hefei Anhui 230027 China

ISBN: (纸本)9780769547725

The fault signature can be revealed by vibration analysis in machine fault detection and diagnosis. It is difficult to evaluate the status of machine for that non-stationary and non-linear vibrations are often caused in machine working process. Manifold learning is a new method for dimensionality reduction and information mining of nonlinear data. In this paper, four statuses of rolling bearing were simulated to investigate status features extraction using manifold learning method. Compared to principal component analysis (PCA), the low dimensional embedded features extracted by the Local tangent space alignment (LTSA) algorithm have excellent clustering quality. Experimental results indicated that the LTSA algorithm has great merit in good clustering with small within-class distance, and thus provides an effective method for intelligent diagnosis of rolling bearing. © 2012 IEEE.

关键词： Feature extraction

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2021 3rd International conference on Artificial Intelligence and Computer Science, AICS 2021

2021 3rd International Conference on Artificial Intelligence...

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2021 3rd International conference on Artificial Intelligence and Computer Science, AICS 2021

The proceedings contain 106 papers. The topics discussed include: short-term global horizontal irradiance forecasting using a hybrid convolutional neural network-gate recurrent unit method;TCN-HBP: a deep learning method for identifying hormone-binding proteins from amino acid sequences based on a temporal convolution neural network;feature selection and reduction of lower limb activity recognition based on surface electromyography and motion data;a modified online intelligent method to calibrate radar and camera sensors for data fusing;detection of sick laying hens by infrared thermal imaging and deep learning;a new method for geophysical induced polarization inversion based on stochastic medium model and sample-compressed artificial neural network;a recommended method based on the weighted RippleNet network mode;and business anomaly detection method of power dispatching automation system based on clustering under-sampling in the boundary region.

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Research on learning Terminal System for English Teaching Practice in Artificial Intelligence 3

Research on Learning Terminal System for English Teaching Pr...

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3rd IEEE International conference on Electrical Engineering, Big Data and Algorithms, EEBDA 2024

作者： Cao, Yu Xi'an Eurasia University Global Language Center Xi'an710065 China

ISBN: (纸本)9798350380989

This paper is mainly for the English test terminal research and development. It has realized the functions of question bank, examination, examination statistics and so on. The main feature of the system is that the whole process of using cryptography and digital signature technology, the paper generation process and the content of the examination questions are more fully processed, and also provides a safe and flexible authorized access control mechanism, a complete function of dynamic query and statistical analysis, intelligent paper design. It converts speech recognition and English into Chinese intonation, and designs and develops English translation system at the same time. The deviation between the basic frequency curve of the established tone system and the original sound is only 0.02, and the basic frequency curve is very close. This method can obtain good speech production results, and the generated sounds are diversified and accurate. The CPU usage of this system is 27.8%. Compared with the mobile terminal system and the WEB system, the CPU usage decreased by 19.0%. © 2024 IEEE.

关键词： Artificial intelligence English teaching English test learning terminal system spoken language

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