2019 IEEE International Work Conference on Bioinspired Intelligence (IWOBI)最新文献

Power consumption aware big.LITTLE scheduler for Linux operating system 耗电量意识大。Linux操作系统的小调度程序

2019 IEEE International Work Conference on Bioinspired Intelligence (IWOBI) Pub Date : 2019-07-01 DOI: 10.1109/IWOBI47054.2019.9114403

Zsolt Bringye, D. Sima, M. Kozlovszky

引用次数: 1

Real Time Surrounding Identification for Visually Impaired using Deep Learning Technique 使用深度学习技术的视障人士实时周围识别

2019 IEEE International Work Conference on Bioinspired Intelligence (IWOBI) Pub Date : 2019-07-01 DOI: 10.1109/IWOBI47054.2019.9114475

Hardik Gupta, Dhruv Dahiya, M. Dutta, C. Travieso-González, J. L. Vásquez-Nuñez

{"title":"Real Time Surrounding Identification for Visually Impaired using Deep Learning Technique","authors":"Hardik Gupta, Dhruv Dahiya, M. Dutta, C. Travieso-González, J. L. Vásquez-Nuñez","doi":"10.1109/IWOBI47054.2019.9114475","DOIUrl":"https://doi.org/10.1109/IWOBI47054.2019.9114475","url":null,"abstract":"Navigating around unfamiliar places and performing other day to day physical tasks are some of the biggest challenges faced by visually impaired people. It is extremely difficult for visually impaired people to commute or perform daily tasks without physical assistance. The conventional methods to aid visually impaired people mostly uses sensors to estimate distances from objects which is very inefficient, expensive and difficult to use without assistance. The proposed work presents a way to provide sight to visually impaired in real time using deep learning by identifying some familiar places used in day to day life like Restrooms, Pharmacies and Metro Stations. This method uses convolutional neural networks to identify signs of public places which are similar around the globe. The proposed work was tested on large varying database and achieved a high accuracy of 90.992 percent. The experimental results show that this method for identifying Restrooms, Pharmacies and Metro Station signs is efficient, has low computational time and fulfils the needs of visually impaired people up to a large extent.","PeriodicalId":427695,"journal":{"name":"2019 IEEE International Work Conference on Bioinspired Intelligence (IWOBI)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116122132","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Compensation Methods for Inhomogeneous Illumination in Whole Slide Imaging System 全玻片成像系统中非均匀光照的补偿方法

2019 IEEE International Work Conference on Bioinspired Intelligence (IWOBI) Pub Date : 2019-07-01 DOI: 10.1109/IWOBI47054.2019.9114429

Róbert Paulik, Lilla Élo, G. Kiszler, M. Kozlovszky, B. Molnár

引用次数: 1

[Copyright notice] (版权)

2019 IEEE International Work Conference on Bioinspired Intelligence (IWOBI) Pub Date : 2019-07-01 DOI: 10.1109/iwobi47054.2019.9114421

引用次数: 0

Parameter Optimization of Deep Learning Models by Evolutionary Algorithms 基于进化算法的深度学习模型参数优化

2019 IEEE International Work Conference on Bioinspired Intelligence (IWOBI) Pub Date : 2019-07-01 DOI: 10.1109/IWOBI47054.2019.9114508

Levente Peto, J. Botzheim

引用次数: 2

The Effect of the Different Data Aggregation Methods and their Detail Levels to the Prediction of Bitcoin's Exchange Rate 不同数据聚合方法及其细节程度对比特币汇率预测的影响

2019 IEEE International Work Conference on Bioinspired Intelligence (IWOBI) Pub Date : 2019-07-01 DOI: 10.1109/IWOBI47054.2019.9114442

Tamas Miseta, Ágnes Vathy-Fogarassy

{"title":"The Effect of the Different Data Aggregation Methods and their Detail Levels to the Prediction of Bitcoin's Exchange Rate","authors":"Tamas Miseta, Ágnes Vathy-Fogarassy","doi":"10.1109/IWOBI47054.2019.9114442","DOIUrl":"https://doi.org/10.1109/IWOBI47054.2019.9114442","url":null,"abstract":"Recently a growing interest can be observed in the field of financial forecasting and especially in the field of cryptocurrency market forecasting. This proved to be an outstandingly complex problem because of the many special characteristics of these markets. Making accurate predictions requires the proper usage and fine tuning of the most modern algorithms. The goal of our research was to find the optimal data division method for the LSTM neural network-based prediction of the exchange rate of Bitcoin and fine-tune the model to achieve the lowest mean percentage error possible. To fulfill this goal, two binning methods, namely transaction time-based, and transaction quantity-based binning methods were evaluated from the viewpoint of the Bitcoin exchange rate prediction. We came to the conclusion that time-based binning method outperforms the other tested method and the granularity of the optimal time division was also established. Experimental results show, that the 20-minute and 30-minute prediction interval are the most suitable choices in case of a limited amount of training data and for making more trading decisions. In case of markets with a higher commission, or when more training data are available the 2-hour prediction is recommended. Our results show that on the proper time division-based LSTM prediction method is suitable for developing successful short term trading strategies for Bitcoin markets.","PeriodicalId":427695,"journal":{"name":"2019 IEEE International Work Conference on Bioinspired Intelligence (IWOBI)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128041787","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Fuzzy Model for Early Warning Score System 预警评分系统的模糊模型

2019 IEEE International Work Conference on Bioinspired Intelligence (IWOBI) Pub Date : 2019-07-01 DOI: 10.1109/IWOBI47054.2019.9114532

Abdallah Benhamida, M. Takács, M. Kozlovszky, Hemza Redjimi, Ogbolu Melvin Omone

引用次数: 1

Deep Learning application to learn models in Cognitive Robotics 深度学习在认知机器人学习模型中的应用

2019 IEEE International Work Conference on Bioinspired Intelligence (IWOBI) Pub Date : 2019-07-01 DOI: 10.1109/IWOBI47054.2019.9114531

Ariel Rodríguez-Jiménez, J. Becerra, Francisco Bellas-Bouza, Esteban Arias-Méndez

{"title":"Deep Learning application to learn models in Cognitive Robotics","authors":"Ariel Rodríguez-Jiménez, J. Becerra, Francisco Bellas-Bouza, Esteban Arias-Méndez","doi":"10.1109/IWOBI47054.2019.9114531","DOIUrl":"https://doi.org/10.1109/IWOBI47054.2019.9114531","url":null,"abstract":"When an artificial neural network (ANN) has to learn in real time, it is not good to train it with ordinary methods (Batch Learning [1]). The problem is that it is difficult to achieve convergence because the data is almost always different and in our experiments, we did not have enough storage available to create a big dataset; also the ANN never stops its learning process. Nowadays, there is an Online Learning [2] available. Real-time learning of a cognitive model can be achieved using Deep Learning [3] with Online training. In addition, there are different techniques that help to make this learning more efficient. The type of training used for an ANN will depend on factors such as data availability, training time, available hardware resources, among others. The training can be offline or online. In the present article, online training has experimented on a robot whose main characteristic is that it uses a Darwinian cognitive mechanism for its survival. The robot learning occurs in real time. It has deep artificial neural networks to predict actions to be performed, training with the least amount of storage space and in the shortest possible time without sacrificing confidence of the deep artificial neural network. The experienced training is Online Deep Learning, Online Deep Learning with memory and Online Mini-Batch Deep Learning with memory.","PeriodicalId":427695,"journal":{"name":"2019 IEEE International Work Conference on Bioinspired Intelligence (IWOBI)","volume":"351 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122840166","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Collaborative Robotic Approach to Gaze-Based Upper-Limb Assisted Reaching 基于注视的上肢辅助伸展的协作机器人方法

2019 IEEE International Work Conference on Bioinspired Intelligence (IWOBI) Pub Date : 2019-07-01 DOI: 10.1109/IWOBI47054.2019.9114485

Luca Fortini, Pietro Balatti, Edoardo Lamon, E. Momi, A. Ajoudani

{"title":"A Collaborative Robotic Approach to Gaze-Based Upper-Limb Assisted Reaching","authors":"Luca Fortini, Pietro Balatti, Edoardo Lamon, E. Momi, A. Ajoudani","doi":"10.1109/IWOBI47054.2019.9114485","DOIUrl":"https://doi.org/10.1109/IWOBI47054.2019.9114485","url":null,"abstract":"Robotic treatment has been recognized as a powerful tool to face the consequences of neurological impairments such as stroke. Among several potential benefits, the possibility to program high-intensity and repetitive movements increased the popularity of this type of rehabilitation technologies for upper limb disabilities. Nevertheless, although the results are encouraging, we are still far from guaranteeing a complete recovery to all patients, and some degree of external assistance is required to enable them to execute their activities of daily living. Hence, we aim to build a system which may serve not only as a rehabilitative tool, but also as a complement to assist the users in everyday tasks. In this direction, we present a novel Human-Robot Interface (HRI), which can detect and learn repetitive user movements through gaze, and provide assistance via a collaborative robot. The robot, which provides support to the user's wrist using a comfortable interface, executes the learnt trajectories, enabling the user to perform repetitive movements with reduced effort. The experiments are carried out on ten healthy subjects. We demonstrate that the proposed HRI is not only flexible and intuitive, but also accurate in guiding the users' limb to the desired positions.","PeriodicalId":427695,"journal":{"name":"2019 IEEE International Work Conference on Bioinspired Intelligence (IWOBI)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132934533","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Deep Periocular Recognition: A Case Study 深眼周识别:一个案例研究

2019 IEEE International Work Conference on Bioinspired Intelligence (IWOBI) Pub Date : 2019-07-01 DOI: 10.1109/IWOBI47054.2019.9114509

Peter Rot, Matej Vitek, Blaž Meden, Ž. Emeršič, P. Peer

引用次数: 1