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An Efficient Image Captioning Method Based on Generative Adversarial Networks 4

An Efficient Image Captioning Method Based on Generative Adv...

引用

4th international conference on Artificial intelligence and pattern Recognition, AIPR 2021

作者： Lin, Zhenxian Feng, Feirong Yang, Xiaobao Ding, Chen School of Science Xi'an University of Posts and Telecommunications China School of Telecommunication and Information Engineering Xi'an University of Posts and Telecommunications China School of Computer Science and Technology Northwestern Polytechnical University China School of Computer Science and Technology Xi'an University of Posts and Telecommunications China Shaanxi Key Laboratory of Network Data Analysis and Intelligent Processing Xi'an University of Posts and Telecommunications China

ISBN: (纸本)9781450384087

Image captioning is usually based on the mainstream encoder-decoder framework, the accuracy of the encoders and the generation capability of the decoders directly affect the quality of image captions. But no matter how the encoders and the decoders are combined, the generated captions will only imitate the ground-truth captions, and its diversity is suppressed. To generate more accurate and diverse captions while exploring the impact of different encoder-decoder frameworks for the quality of the generated captions, we conducted an exploration of an efficient image captioning method based on GAN. Specifically, we use ResNet152, EfficientNet-B0, and EfficientNet-B2 as the encoders to extract image features, GRU or Transformer as the decoders to generate captions, respectively. Based on MS COCO2014 dataset, a large number of experiment results show that the EfficientNet-B2+GRU framework has best performance, training time is reduced, BLUE-4 score increases by 0.6, parameters reduce by 0.66 million, which can be used as an efficient encoder-decoder framework for generating diverse captions. © 2021 ACM.

关键词： Generative adversarial networks

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Realization of Multi Parameter Measuring Device Based on ATT7022E and STM32 10

Realization of Multi Parameter Measuring Device Based on ATT...

引用

10th international conference on Computing and pattern Recognition, ICCPR 2021

作者： Gao, Zhaoling Yu, Guang School of Intelligence and Electronic Engineering Dalian Neusoft University of Information China

ISBN: (纸本)9781450390439

This article introduces in detail a multi-parameter measurement device that can measure six-channel voltage, current and other information with the three-phase multi-function measurement chip ATT7022E, and can transmit the measured data to the high-performance ARM_Cortex_M4 microcontroller through the serial port of the STM32 single-chip microcomputer. This controller is equipped with an industrial Ethernet interface to connect to the Internet. In addition to the data acquisition part, it also realizes the remote configuration and precise control of the entire device. This article mainly introduces the content of the data acquisition part, including the acquisition of three-phase input and output Terminal voltage, current, active power, reactive power, apparent power, power factor and other parameters. Describes the design of this part of the hardware schematic diagram: including voltage sampling circuit, current sampling circuit, ATT7022E basic circuit, STM32F103RBT6 microcontroller basic circuit, serial communication interface and other circuit designs. It also describes the software calibration method, the realization of serial communication with the host computer ARM_Cortex_M4 microcontroller and the analysis of the measurement results. After experiments, the voltage is calibrated near the grid voltage, and the voltage value can reach the accuracy requirement within 0.5 level in the technical indicators of the power monitor. © 2021 ACM.

关键词： Microcontrollers

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Prediction of Sit-to-Stand Time Using Trunk Angle and Lower Limb EMG for Assistance System

Prediction of Sit-to-Stand Time Using Trunk Angle and Lower ...

引用

2020 IEEE international conference on Artificial intelligence in Engineering and Technology, IICAIET 2020

作者： Inoue, Tsuyoshi Matsuo, Ryota Osaka Institute of Technology Faculty of Robotics Design Osaka Japan

ISBN: (纸本)9781728169460

Herein, we propose a method to predict the sit-to-stand time of a user movement assist system. The proposed method predicts the sit-to-stand time using changes in the trunk angle and lower limb muscle activity, based on multiple regression analysis. To verify the accuracy of the proposed method and evaluate data regarding various standing speeds, we conducted experiments on nine participants. The evaluation results show that the proposed method reduced the average error by approximately 35.6% when compared to the conventional method. © 2020 IEEE.

关键词： Motion estimation

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Human Machine Interaction Platform for Home Care Support System

Human Machine Interaction Platform for Home Care Support Sys...

引用

IEEE international conference on Systems, Man, and Cybernetics (SMC)

作者： Nasr, Mahmoud Karray, Fakhri Quintana, Yuri Univ Waterloo Ctr Pattern Anal & Machine Intelligence Waterloo ON Canada Harvard Med Sch Beth Israel Deaconess Med Ctr Div Clin Informat Boston MA 02115 USA

ISBN: (纸本)9781728185262

There has been a tremendous increase in the costs of caring for older adults owing to the fact that societies are aging around around the world. This has led to a decrease in the number of caregivers who are able to assist. Investigative studies indicate that older adults require social as well as physical support for their well-being which prompted researchers to use social and cognitive robots and advanced human machine interaction devices. However, most of these studies have shortcomings when it comes to providing means of a natural interaction with the machine. With speech being the most natural way for human communication and the huge developments in the Internet of Things and smart homes, equipping a robotic system with powerful natural speech interaction capabilities to maintain a conversation with an elderly while being linked to other smart home devices shows a promising direction. This paper describes a scalable and expandable system with main goal of designing a natural speech-enabled system for older adults that is capable of linking to multiple active agents with minimal integration efforts. The system makes use of the power of commercially available digital assistant systems, integrated with an intelligent conversational agent, robotics, and smart wearables. The main advantage of the system is that it could provide a portion of the population, namely older adults and the disabled, the flexibility of interacting naturally with powerful social robots in smart home environments, hence providing them with much needed independence.

关键词： Social robots Human-Robot Interaction Elderly care Artificial intelligence Speech Interaction Ambient Assisted Living

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A Systematic Review on Latest Approaches of Automated Sleep Staging System Using Machine intelligence Techniques 1

引用

1st international conference on Advanced Computing, Machine Learning, robotics and Internet Technologies, AMRIT 2023

作者： Sahu, Suren Kumar Satapathy, Santosh Kumar Mohapatra, Sudhir Kumar Faculty of Emerging Technologies Sri Sri University Odisha Cuttack754006 India Information and Communication Technology Pandit Deendayal Energy University Gujarat Gandhinagar382007 India

ISBN: (数字)9783031472244

ISBN: (纸本)9783031472237

Background and Objective: Sleep staging plays a vital role in sleep research because sometimes sleep recording errors may cause severe problems like misinterpretations of the changes in characteristics of the sleep stages, medication errors, and, finally, errors in the diagnosis process. Because of these errors in recordings and analysis, the sleep behavior and automated sleep staging system are adopted by different researchers with different methodologies. This study identifies specific challenges with the existing studies and highlights certain points that support the improvement of automated sleep staging-based polysomnography signals. Methods: This work provides a comprehensive review of an automated sleep staging system, which was contributed by the different researchers in the recent research developments using Electroencephalogram, Electrocardiogram, Electromyogram, and combinations of these signals. Results: Our review in this research area shows that single-model and multimodal signals are used for sleep staging, and also we have observed some great points from the existing methodologies: (1) It has been noticed that 30-s length of the epoch of EEG signals may not be sufficient to extract enough information for discriminating the sleep patterns but in the other hand that a 10-s and 15-s length epoch is well suitable for sleep staging, (2) due to similar characteristics on N1 and REM sleep stages, most of the traditional classification models misclassified N1 sleep stages as REM stage, which alternatively degrades the sleep stagging performance, (3) consideration of heterogeneous form signal fusions can give the improvement results on sleep staging, and (4) applying deeplearning based models, combinedly to significant PSG signals can lead to more robust automatic sleep staging results. Conclusions: The review mentioned above points simultaneously improves automated sleep staging by polysomnography signals. These points can help to focus our research work fro

关键词： Electroencephalography

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Predicting Dynamic Product Price by Online analysis: Modified K-Means Cluster 1

引用

2nd international conference on Computational intelligence in pattern Recognition (CIPR)

作者： Nayak, Manjushree Narain, Bhavana MATS Univ MATS Sch Informat Technol Raipur 492004 Chhattisgarh India

ISBN: (数字)9789811524493

ISBN: (纸本)9789811524493;9789811524486

In data mining, various techniques are applied on large sets of data. These large sets of data are known as big data. For extraction and retrieval of desired information or pattern from big amount of data and quantity of knowledge, we tend to use huge data processing. To maintain working of "big data," various logics are used. Today, because of many online applications, product price is highly dynamic and current price can be compared by the customers by using different applications. In our work, we have used modified K-means clustering method and divided online data. Dataset is divided into 10 clusters for analysis. In the last section, the conclusion based on I/O time and computational time is given.

关键词： K-means Big data Algorithm Online analysis

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A Practical SVD-based Ellipsoid Estimation Method for Active Modeling of Robotic Ureteroscope

A Practical SVD-based Ellipsoid Estimation Method for Active...

引用

IEEE international conference on robotics and Biomimetics

作者： Xiangyu Wang Qingyi Zeng Yanding Qin Yongchun Fang Institute of Robotics and Automatic Information Systems College of Artificial Intelligence Tianjin Key Laboratory of Intelligent Robotics Nankai University Tianjin China

ISBN: (纸本)9781665405362

Instead of the Kalman-type filters requiring strict assumption on noise distributions, the extended set membership filter (ESMF) only assumes unknown but bounded (UBB) noises, therefore is more practical and applicable for the active modeling of robotic ureteroscope. However, the ESMF calculation needs the ellipsoid analysis that usually suffers from numerical instability, especially during the real-time processing of sensory measurements, and may further result in the divergence of the whole control system. In this paper, we propose the singular value decomposition for ESMF to handle this problem. The ESMF is firstly introduced as a preknowledge. Then, a singular value decomposition-based extended set membership filtering algorithm (SVD-ESMF) is constructed based on the sequential processing technique. Finally, we verify the performance of the proposed algorithm combined with the active modeling method on a self-built robotic flexible ureteroscope platform. Compared with the normal ESMF algorithm, the SVD-ESMF successfully eliminates the influence of unstable points and guarantees the confidence of the estimated bounds.

关键词： Filtering Estimation Filtering algorithms Robot sensing systems Real-time systems Stability analysis Probability distribution

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analysis of the Exposing Media pattern that Affect Accessing Own Website 12th

Analysis of the Exposing Media Pattern that Affect Accessing...

引用

12th international conference on Social Computing and Social Media (SCSM) part of the 22nd international conference on Human-Computer Interaction (HCI)

作者： Katagiri, Yuho Otake, Kohei Namatame, Takashi Chuo Univ Grad Sch Sci & Engn 1-13-27KasugaBunkyo Ku Tokyo 1128551 Japan Tokai Univ Sch Informat & Telecommun Engn 2-3-23 TakanawaMinato Ku Tokyo 1088619 Japan Chuo Univ Fac Sci & Engn 1-13-27 KasugaBunkyo Ku Tokyo 1128551 Japan

ISBN: (纸本)9783030495695;9783030495701

Recently, due to the expansion of TV or smart phone, the frequency of exposing media has increased. Also, the way of interacting with the media is diversifying by life stages or life balance. In such situations, people get much information about products and services on media. Therefore, it is important to select the best media for advertisement. In this study, we analyze the characteristics of exposing media using media exposure data. First, we performed Non-negative Matrix Factorization (NMF) to extract pattern of exposing media. Second, we used random forest to analyze the characteristics of the exposing media pattern. From our result, we discussed how to advertise on TV and website.

关键词： Exposing media pattern Nonnegative matrix factorization Random forest

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Organ Segmentation with Recursive Data Augmentation for Deep Models 25th

Organ Segmentation with Recursive Data Augmentation for Deep...

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25th international conference on pattern Recognition Workshops, ICPR 2020

作者： Akbar, Muhammad Usman Yamin, Muhammad Abubakar Murino, Vittorio Sona, Diego Pattern Analysis and Computer Vision Istituto Italiano di Tecnologia Genova Italy Department of Electrical Electronics and Telecommunication Engineering Università di Genova Genova Italy Huawei Technologies Ltd. Ireland Research Center Dublin Ireland Department of Computer Science Università di Verona Verona Italy Neuroinformatics Laboratory Fondazione Bruno Kessler Trento Italy

ISBN: (纸本)9783030687625

The precise segmentation of organs from computed tomography is a fundamental and pivotal task for correct diagnosis and proper treatment of diseases. Neural network models are widely explored for their promising performance in the segmentation of medical images. However, the small dimension of available datasets is affecting the biomedical imaging domain significantly and has a huge impact in training of deep learning models. In this paper we try to address this issue by iteratively augmenting the dataset with auxiliary task-based information. This is obtained by introducing a recursive training approach, where a new set of segmented images is generated at each iteration and then concatenated with the original input data as organ attention maps. In the experimental evaluation two different datasets were tested and the results produced from the proposed approach have shown significant improvements in organ segmentation as compared to a standard non-recursive approach. © 2021, Springer Nature Switzerland AG.

关键词： Deep learning

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Classification of Handwritten Devanagari Number - An analysis of pattern Recognition Tool using Neural Network and CNN

Classification of Handwritten Devanagari Number - An analysi...

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international conference on Computational intelligence and Data Science (ICCIDS)

作者： Prashanth, Duddela Sai Mehta, R. Vasanth Kumar Sharma, Nisha SCSVMV Univ Kanchipuram 631561 India Sahyadri Coll Engn & Management Mangaluru 575005 India

This paper majorly concerns the classification of handwritten numerals of Devanagari Script. The major contributions in this paper are 1) Development of a dataset for handwritten numerals similar to MNIST dataset, 2) analysis of pattern Recognitions tools based on NN and Convolution Neural Network, 3) Detailed discussion on the results by calculating the Precision, recall and F-measure values and compared with the other dataset available online. The present dataset includes 4,282 handwritten numerals of Devanagari which are collected from people of different ages. In the methodology developed in this paper, all the numerals are extracted from the image. After pre-processing, the images are resized to 30X30 which are later converted to vectors. These vectors with labels are the inputs for the classifiers. ANN classifier is designed by using PRToo1 and Deep Learning network is designed to make comparison with ANN. Data for training and testing splits into different ratios 80:20, 70:30, 60:40 and 50:50. This research has achieved accuracy of more than 95%. The results of the dataset generated are compared with the dataset available online. (C) 2020 The Authors. Published by Elsevier B.V.

关键词： pattern Recognition Handwritten Character Recognition Convolution Neural Network Devanagari Numerals

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