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machine learning for Strategic Urban Planning 2

Machine Learning for Strategic Urban Planning

引用

2nd international conference of the IEEE-Nigeria-Computer-Chapter (NigeriaComputConf)

作者： Odaudu, S. N. Umoh, I. J. Mu'azu, M. B. Ahmadu Bello Univ Dept Comp Engn Zaria Kaduna Nigeria

ISBN: (纸本)9781728107134

Data mining is an important part of strategic planning for the development of modern urban settlement with capacities to accommodate population explosion. Developing countries arefast becoming urbanized giving the developments and opportunities that are lacking in rural areas. Data regarding urban development such as satellite image need to be analysed to ascertain the possibilities for further development or opening up of new settlements. This work presents a binary sub-pixel and feature based method of classification to detect water bodies and vegetation in earth observatory images. In this work, the images were subjected data pre-processing, feature extraction, and analysed the data using machine learning classification method to detection regions that support urban expansion or development of new settlement The proposed method achieved 88.93% accuracy and 0.06% RAISE

关键词： Satellite image object detection machine learning Haar-cascade feature engineering

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Customer Churn Prediction in Bank Based on Different machine learning Models 2

Customer Churn Prediction in Bank Based on Different Machine...

引用

2nd international signal processing, Communications and Engineering Management conference, ISPCEM 2022

作者： Li, Xiaofeng Chen, Zhongwei School of Information Engineering Guangxi University of Foreign Languages Guangxi Nanning530222 China

ISBN: (纸本)9781665492713

With the rise of internet finance, the competition in the banking industry has become increasingly fierce. Preventing the loss of customers and retaining old customers has become an important concern of major banks. Firstly, according to an existing open dataset, this paper makes a descriptive statistical analysis of each feature, and uses Logistic, Random Forest and Scv models to predict customer churn, such as AUC curves, Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Mean Absolute Error (MSE). The better-performing models listed above are then chosen. Finally, Svm is selected as the best performance model, and according to descriptive statistics and feature importance, some suggestions are put forward for banks to retain customers. © 2022 IEEE.

关键词： Sales

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learning Mixtures of Smooth Product Distributions: Identifiability and Algorithm 22

Learning Mixtures of Smooth Product Distributions: Identifia...

引用

22nd international conference on Artificial Intelligence and Statistics (AISTATS)

作者： Kargas, Nikos Sidiropoulos, Nicholas D. Univ Minnesota Minneapolis MN 55455 USA Univ Virginia Charlottesville VA 22903 USA

We study the problem of learning a mixture model of non-parametric product distributions. The problem of learning a mixture model is that of finding the component distributions along with the mixing weights using observed samples generated from the mixture. The problem is well-studied in the parametric setting, i.e., when the component distributions are members of a parametric family such as Gaussian distributions. In this work, we focus on multivariate mixtures of non-parametric product distributions and propose a two-stage approach which recovers the component distributions of the mixture under a smoothness condition. Our approach builds upon the identifiability properties of the canonical polyadic (low-rank) decomposition of tensors, in tandem with Fourier and Shannon-Nyquist sampling staples from signal processing. We demonstrate the effectiveness of the approach on synthetic and real datasets.

关键词： Mixtures

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CLASSIFICATION OF MASS SPECTROMETRY DATA Using Manifold and Supervised Distance Metric learning

CLASSIFICATION OF MASS SPECTROMETRY DATA <i>Using Manifold a...

引用

2nd international conference on Bio-Inspired Systems and signal processing

作者： Liu, Qingzhong Sung, Andrew H. Ribeiro, Bernardete M. Qiao, Mengyu Univ Coimbra Dept Informat Engn P-3000 Coimbra Portugal New Mexico Inst Min & Technol Inst Complex Addit Syst Anal Socorro NM 87801 USA Univ Coimbra Dept Informat Engn Coimbra Portugal

ISBN: (纸本)9789898111654

Mass spectrometry becomes the most widely used measurement in proteomics research. The quality of the feature set and applied learning classifier determine the reliability of the prediction of disease status. A well-known approach is to combine peak detection and support vector machine recursive feature elimination (SVMRFE). To compare the feature selection and to search for alternative learning classifier, in this paper, we employ a distance metric learning to classification of proteomics mass spectrometry (MS) data. Experimental results show that distance metric learning is promising for the classification of proteomics data;the results are comparable to the best results by applying SVM to the SVMRFE feature sets. Results also indicate that the good potential of manifold learning for feature reduction in MS data analysis.

关键词： Proteomics Mass spectrometry Manifold Distance metric learning Classification Support vector machine

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Research on Algorithms of Computer Image Intelligent Recognition and Deep learning 2

Research on Algorithms of Computer Image Intelligent Recogni...

引用

2nd international conference on signal Image processing and Communication, ICSIPC 2022

作者： Shao, Zheneenji Zhou, Jingxuan Sichuan University Chengdu China Dalian University of Technology Dalian China

ISBN: (纸本)9781510657694

In recent years, with the rapid development of science and technology in my country, people's requirements for computer information technology have become higher and higher. In order to better explore new things, engineers and technicians need to continuously optimize computer information processing systems to help people better solve practical problems. The article mainly analyzes the development process of computer intelligent image recognition algorithms, expounds the computer intelligent image recognition algorithm, and finally puts forward the technical application of computer intelligent image recognition algorithm, which provides a certain research foundation for related staff. © 2022 SPIE.

关键词： Image recognition

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2022 international conference on signal and Information processing, IConSIP 2022

2022 International Conference on Signal and Information Proc...

引用

2nd international conference on signal and Information processing, IConSIP 2022

ISBN: (纸本)9781728168852

The proceedings contain 85 papers. The topics discussed include: audio processing for tones validation using deep learning;effective generation of visual questions;elicitation of intracerebral hemorrhage using deep learning;underwater image enhancement using color constancy via homomorphic filtering and depth estimation;fusion based underwater image enhancement and detail preserving;FPGA based feature extraction in real time computer vision - a comprehensive survey;enhancement of liver ultrasound images by guided image filtering technique;exploration of horizontal and vertical components in polarimetric decomposition based on volume scattering;audio source count estimation using deep learning;detection of pneumonia from x-ray images using eigen decomposition and machine learning techniques;audio based detection of saw blade sharpness using machine learning;performance analysis and evaluation of estimator for RF cavity detuning measurement;speaker identification and verification using deep learning;and motor imagery based EEG signal classification using multi-scale CNN architecture.

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Damage Detection in Switch Rails via machine learning 2

Damage Detection in Switch Rails via Machine Learning

引用

2nd IEEE international conference on Pattern Recognition and machine learning, PRML 2021

作者： Liu, Weixu Tang, Zhifeng Zhang, Pengfei Chen, Xiangxian Yang, Bin Institute of Advanced Digital Technologies and Instrumentation Zhejiang University Hangzhou310027 China

ISBN: (纸本)9781665443838

Switch rail is a weak but essential component of high-speed rail (HSR) systems. Due to aging and the potential of fatigue damage accumulation, it has an urgent requirement for damage detection. An automatic classification method of switch rail damage based on feature integration and machine learning is proposed. According to the characteristics of switch rail and guided wave, several features extracted from different signal processing domains (such as time domain, power spectrum domain and time-frequency domain) are proposed and defined to characterize the complexity of switch rail damage. A damage index is defined to eliminate the effects of various environmental and operational conditions. A feature selection method based on binary particle swarm optimization (BPSO) is proposed. This method uses a new fitness function to select the most damage-sensitive features, eliminate the irrelevant and redundant features, and improve the classification performance. The least-squares support-vector machine (LS-SVM) is adopted to build an automatic classification model to reduce the probability of artificial error diagnosis and improve the generalization ability. Finally, experiment on the switch rail foot is conducted to verify the proposed method. The results show that the method has the ability of damage identification, which is better than traditional methods. © 2021 IEEE.

关键词： Particle swarm optimization (PSO)

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Developing Interactive Bible learning Model Based on Mobile for Children 2019

Developing Interactive Bible Learning Model Based on Mobile ...

引用

2nd international conference on Software Engineering and Information Management (ICSIM) / 2nd international conference on Big Data and Smart Computing (ICBDSC)

作者： Sutopo, Hadi Purnomo, Hindriyanto D. Maria, Silaen Sondang Lee, Swati Lobodally, Altobeli Prasida, Arie Setiawan Inst Teknol & Bisnis Kalbis Jl Pulomas Selatan Kav 22 Jakarta 13210 Indonesia Univ Kristen Satya Wacana Jl Dr O Notohamidjojo Blotongan 50714 Salatiga Indonesia Univ Persada Indonesia YAI Jl Diponegoro 74 Jakarta 10430 Indonesia Dr Lee Brain Acad Grand Slipi Tower Lt-23DJalan S Parman Kav 22-24 Jakarta 11480 Indonesia

ISBN: (纸本)9781450366427

Bible stories have been introduced to children at early ages and continuously learned. The learning process is conventionally conducted in classrooms with books as the main media and lately accompanied by video presentations. However, the current life style in the IT era may shift children learning style. For them, smartphones and other digital media are more interesting than books. This paper is intended to create a mobile-based Bible-learning for children and youth. In developing the application, the researchers conduct qualitative approaches combining Borg and Gall's Research and Development Method with Luther's Multimedia Development Life Cycle. It is the utmost hope that the new IT-based learning model could facilitate easier, more fun and more interesting learning for children and youth. This research is still on going and the researchers would like to present a smartphone-based Bible learning games. Collected data is processed using NVivo, a qualitative software data processing. Research findings show that mobile-based learning including games is the most feasible model.

关键词： mobile multimedia Bible learning game interactive

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Eye-2-I: Eye-Tracking for Just-in-Time Implicit User Profiling 2

Eye-2-I: Eye-Tracking for Just-in-Time Implicit User Profili...

引用

2nd IEEE international conference on signal and Image processing (ICSIP)

作者： Ma, Keng-Teck Xu, Qianli Lim, Rosary Li, Liyuan Sim, Terence Kankanhalli, Mohan ASTAR Inst Infocomm Res 1 Fusionopolis Way Singapore 138632 Singapore Natl Univ Singapore 13 Comp Dr Singapore 117417 Singapore

ISBN: (纸本)9781538609699

For many applications, such as targeted advertising and content recommendation, knowing users' traits and interests is a prerequisite. User profiling is a helpful approach for this purpose. However, current methods, i.e. self-reporting, web-activity monitoring and social media mining are either intrusive or require data over long periods of time. Recently, there is growing evidence in cognitive science that a variety of users' profile is significantly correlated with eye-tracking data. A novel just-in-time implicit profiling method, Eye-2-I, which learns the user's demographic and personality traits from the eye-tracking data while the user is watching videos is proposed. Although seemingly conspicuous by closely monitoring the user's eye behaviors, the proposed method is unobtrusive and privacy-preserving owing to its unique combination of speed and implicitness. As a proof-of-concept, the proposed method is evaluated in a user study with 51 subjects.

关键词： eye-gaze user profiling classification machine learning

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proceedings of the 2nd international conference on signal and Data processing 1

引用

丛书名： Lecture Notes in Electrical Engineering

1000年

作者： K. P. Ray Arati Dixit Debashis Adhikari Ribu Mathew

ISBN: (数字)9789819914104

ISBN: (纸本)9789819914098;9789819914128

This volume comprises the select proceedings of the 2nd international conference on signal & Data processing (ICSDP) 2022. The contents focus on the latest research and developments in the field of artificial intelligence & machine learning, Internet of things (IoT), cybernetics, advanced communication systems, VLSI embedded systems, power electronics and automation, MEMS/ nanotechnology, renewable energy, bioinformatics, data acquisition and mining, antenna & RF systems, power systems, biomedical engineering, aerospace & navigation. This volume will prove to be a valuable resource for those in academia and industry.

关键词： signal, Image and Speech processing Wireless and Mobile Communication Circuits and Systems Image processing and Computer Vision Energy Systems

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