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检索条件"任意字段=3rd International Conference on Machine Learning and Data Mining in Pattern Recognition"

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Challenges in Sensor-based Human Activity recognition and a Comparative Analysis of Benchmark datasets: A Review 8

Challenges in Sensor-based Human Activity Recognition and a ...

引用

Joint 8th international conference on Informatics, Electronics and Vision (ICIEV) / 3rd international conference on Imaging, Vision and pattern recognition (icIVPR) / international conference on Activity and Behavior Computing (ABC)

作者： Das Antar, Anindya Ahmed, Masud Ahad, Md Atiqur Rahman Univ Dhaka Dept Elect & Elect Engn Dhaka Bangladesh

ISBN: (纸本)9781728107882

Human Activity recognition using embedded sensors has lately made renowned development and is drawing growing attention in numerous application domains including machine learning, pattern recognition, context awareness, and human-centric sensing. Due to the lacking of a prominent analysis of this topic that can acquaint concomitant communities of the research avant-garde, there are still vital perspectives that, if pleaded, would create a vital turn in the way of interaction among people and mobile devices. In this paper, we have presented a comprehensive survey along with the prevailing state of various challenges of human activity recognition based on wearable, environmental, and smartphone sensors. Firstly, we have shown numerous factors to be considered for the data pre-processing part regarding noise filtering and segmentation methods. Besides, we have made a list of sensing devices, sensors, and applications that can be used for collecting activity data along with a discussion on sensor position and requirements. Moreover, we have made a comprehensive analysis of some benchmark datasets, which includes information about sensors, attributes, activity classes, etc. Finally, we have shown an analysis of activity recognition approaches on some of the benchmark datasets based on existing works.

关键词： Benchmark datasets data pre-processing human activity recognition smartphone sensors survey wearable sensors

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data mining by Navigation - An Experience with Systems Biology

Data Mining by Navigation - An Experience with Systems Biolo...

引用

3rd international conference on pattern recognition and machine Intelligence

作者： Gupta, Amarnath Baitaluk, Michael Ray, Animesh Bagchi, Aditya Univ Calif San Diego San Diego Supercomp Ctr La Jolla CA 92093 USA Keck Grad Inst Claremont CA 91711 USA Indian Stat Inst Kolkata 700108 India

ISBN: (纸本)9783642111631

This paper proposes a navigational method for mining by collecting evidences from diverse data sources. Since the representation method and even semantics of data elements differ widely from one data source to the other, consolidation of data under a single platform doesn't become cost effective. Instead, this paper has proposed a method of mining in steps where knowledge gathered in one step or from one data source is transferred to the next step or next data source exploiting a distributed environment. This incremental mining process ultimately helps in arriving at the desired result. The entire work has been done in the domain of systems biology. Indication has been given how this process can be followed in other application areas as well.

关键词： data mining

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Bangla Handwritten Character recognition using Convolutional Neural Network with data Augmentation 8

Bangla Handwritten Character Recognition using Convolutional...

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作者： Chowdhury, Rumman Rashid Hossain, Mohammad Shahadat Ul Islam, Raihan Andersson, Karl Hossain, Sazzad Univ Chittagong Dept Comp Sci & Engn Chittagong Bangladesh Lulea Univ Technol Skelleftea Dept Comp Sci Elect & Space Engn Skelleftea Sweden Univ Liberal Arts Bangladesh Dept Comp Sci & Engn Dhaka Bangladesh

ISBN: (纸本)9781728107882

This paper proposes a process of Handwritten Character recognition to recognize and convert images of individual Bangla handwritten characters into electronically editable format, which will create opportunities for further research and can also have various practical applications. The dataset used in this experiment is the BanglaLekha-Isolated dataset [1]. Using Convolutional Neural Network, this model achieves 91.81% accuracy on the alphabets (50 character classes) on the base dataset, and after expanding the number of images to 200,000 using data augmentation, the accuracy achieved on the test set is 95.25%. The model was hosted on a web server for the ease of testing and interaction with the model. Furthermore, a comparison with other machine learning approaches is presented.

关键词： Convolutional Neural Network handwritten character recognition Bangla handwritten characters data augmentation

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Comparative pattern analysis of cretan folk songs

Comparative pattern analysis of cretan folk songs

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3rd ACM international Workshop on machine learning and Music, MML'10, Co-located with ACM Multimedia 2010

作者： Conklin, Darrell Anagnostopoulou, Christina Department of Computer Science Al Universidad del País Vasco San Sebastián Spain IKERBASQUE: Basque Foundation for Science Bilbao Spain Department of Music Studies University of Athens Athens Greece

ISBN: (纸本)9781450301619

This paper reports on data mining of Cretan folk songs for distinctive patterns. A pattern is distinctive if it occurs with higher probability in a corpus as compared to an anticorpus. A small set of Cretan folk songs was collected, organized using a small knowledge base of classes, and mined using distinctive pattern discovery methods. Several highly distinctive and confident patterns emerge.

关键词： data mining

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Design of Intelligent Pest Monitoring System Based on Image Classification Algorithm 3

Design of Intelligent Pest Monitoring System Based on Image ...

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3rd international conference on Control and Robots (ICCR)

作者： Yu Lina Yue Xiuming Shandong Xiehe Univ Coll Comp Jinan Peoples R China

ISBN: (数字)9781728175621

ISBN: (纸本)9781728175621

The emergence of pattern recognition, artificial intelligence and machine learning. Bring new height to the development of smart agriculture. This paper studies an image classification algorithm, An intelligent pest monitoring system is built based on this algorithm. The system adopts UAV monitoring equipment carrying artificial intelligence module and intelligent recognition algorithm and ground monitoring equipment. Realize diseases and insect pests accurate prediction and intelligent diagnosis. To solve the current industry monitoring mode is single, low level of intelligence, monitoring type limitations and other issues. With the power of wisdom, drive China's agriculture to flourish.

关键词： image classification machine learning diseases and insect pests monitor

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Proceedings of the 3rd international conference on Intelligent Sustainable Systems, ICISS 2020

Proceedings of the 3rd International Conference on Intellige...

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3rd international conference on Intelligent Sustainable Systems, ICISS 2020

ISBN: (纸本)9781728170893

The proceedings contain 273 papers. The topics discussed include: intelligent automation based gas valve control mechanism in biogas plant;analysis of guiding quality evaluation model based on regional ecological safety performance evaluation and information mining;review on materials and methods for supercapacitors;performance analysis of current-fed DAB converter for DC microgrid with active power control;computer data processing mode in the era of big data: from pattern recognition to intelligent sensing;road conditions and obstacles indication and autonomous braking system;a study of big data analytics using apache spark with python and Scala;implementing a DC UPS with battery’s state of charge estimation based on coulomb-counting method;cascaded GSM detector-jammer design;diabetes prediction by using big data tool and machine learning approaches;and an efficient design of fault tolerant reversible multiplexer using QCA technology.

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Proceedings of the 2020 3rd international conference on Artificial Intelligence and pattern recognition, AIPR 2020

Proceedings of the 2020 3rd International Conference on Arti...

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3rd international conference on Artificial Intelligence and pattern recognition, AIPR 2020

ISBN: (纸本)9781450375511

The proceedings contain 43 papers. The topics discussed include: application research of model-free reinforcement learning under the condition of conditional transfer function with coupling factors;expected regret minimization for Bayesian optimization with student’s-t processes;a mining frequent itemsets algorithm in stream data based on sliding time decay window;experimental and theoretical scrutiny of the geometric derivation of the fundamental matrix;dual-precision deep neural network;annotating documents using active learning methods for a maintenance analysis application;offline handwritten Chinese character recognition based on improved Googlenet;a network combining local features and attention mechanisms for vehicle re-identification;and a spatial attention-enhanced multi-timescale graph convolutional network for skeleton-based action recognition.

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Integrating Activity recognition and Nursing Care Records: the System, Experiment, and the dataset 8

Integrating Activity Recognition and Nursing Care Records: t...

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作者： Inoue, Sozo Mairittha, Tittaya Mairittha, Nattaya Hossain, Tahera Kyushu Inst Technol 1-1 Sensui Cho Tobata Kitakyushu Fukuoka 8048550 Japan

ISBN: (纸本)9781728107882

In this paper, we introduce a system that integrates activity recognition, which collects various activities of the elderly people of a nursing care facility in Japan. This system incorporates various activity levels, sensor data through smartphones, and records by nurses for a period of 4 months. There are 28 activity labels, recorded by a number of staffs/nurses. The system architecture has mobile application to encode data and a networked system in the 6-floored facility, covering a number of residents. The system is designed in such a manner that even a non-expert nurse or user can manage this system. After introducing the entire system and data collection procedure, we recognized the acitivities by exploiting some statistical features and Extremely Randomized Tree. We noticed that there are discrepancies between start and end recording time-stamps. Therefore, we explored a time correction technique. The dataset is an extensive one and it can be explored for various activity recognition in smart-homes or elder care facilities. The dataset includes the sensor data from staffs' smartphones, activity labels, and care details input using the system.

关键词： Smart phones Medical services Activity recognition Cloud computing Servers machine learning Metadata

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Optimal Double-Kernel Combination for Classification

引用

6th international conference on machine learning and data mining in pattern recognition

作者： Wang, Feng Zhang, Hongbin Beijing Univ Sci & Technol Coll Comp Sci Beijing 100124 Peoples R China

ISBN: (纸本)9783642030697

Traditional kernelised classification methods Could not perforin well sometimes because of the using of a single and fixed kernel, especially oil sonic complicated data sets. In this paper. a novel optimal double-kernel combination (ODKC) method is proposed for complicated classification tasks. Firstly, data sets are mapped by two basic kernels into different feature spaces respectively, and then three kinds of optimal composite kernels are constructed by integrating information of the two feature spaces. Comparative experiments demonstrate the effectiveness of our methods.

关键词： Classification kernel learning pattern recognition

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Comparative Study of Classifier for Chronic Kidney Disease prediction using Naive Bayes, KNN and Random Forest 3

Comparative Study of Classifier for Chronic Kidney Disease p...

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3rd international conference on Computing Methodologies and Communication (ICCMC)

作者： Devika, R. Avilala, Sai Vaishnavi Subramaniyaswamy, V SASTRA Deemed Univ Sch Comp Thanjavur Tamil Nadu India

ISBN: (纸本)9781538678084

Chronic kidney disease (CKD), is also known as chronic nephritic sickness. It defines constrains which affects your kidneys and reduces your potential to stay healthy. There will be various complication concerns like increased levels in your blood, anemia (low blood count), weak bones, and nerve injury. Detection and treatment should be done prior so it will typically keep chronic uropathy from obtaining a worse condition. data processing is the term used for information discovery from big databases. The task of knowledge mining is to generate regular patterns from historical data and emphasize future conclusions, follows from the convergence of many recent trends: the decreased value of huge knowledge storage devices and therefore the tremendous ease of aggregation knowledge over networks;the development of robust and economical machine learning algorithms to method this data;and therefore the decrease value of machine power, enabling use of computationally intensive strategies for knowledge analysis. machine learning is an important task as it benefits many applications such as analyzing life science outcomes, sleuthing fraud, sleuthing faux users etc. varied knowledge mining classification approaches and machine learning algorithms are applied for prediction of chronic diseases. Therefore, this paper examines the performance of Naive Bayes, K-Nearest Neighbour (KNN) and Random Forest classifier on the basis of its accuracy, preciseness and execution time for CKD prediction. Finally, the outcome after conducted research is that the performance of Random Forest classifier is finest than Naive Bayes and KNN

关键词： data mining machine learning Chronic kidney disease Classification K-Nearest Neighbour Naive Bayes Random Forest

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