2018 4th International Conference on Frontiers of Signal Processing (ICFSP)最新文献_第2页

Features for Evaluating Gastric Atrophy Using X-ray Images x线影像评价胃萎缩的特点

2018 4th International Conference on Frontiers of Signal Processing (ICFSP) Pub Date : 2018-09-01 DOI: 10.1109/ICFSP.2018.8552048

K. Abe, Kota Shirakawa, Masahide Minami, Daiki Miura

引用次数: 0

Building an Automatic Defect Verification System Using Deep Neural Network for PCB Defect Classification 基于深度神经网络的PCB缺陷分类自动检测系统的构建

2018 4th International Conference on Frontiers of Signal Processing (ICFSP) Pub Date : 2018-09-01 DOI: 10.1109/ICFSP.2018.8552045

Yu-Shan Deng, An-Chun Luo, M. Dai

引用次数: 36

Anomaly Detection of System Logs Based on Natural Language Processing and Deep Learning 基于自然语言处理和深度学习的系统日志异常检测

2018 4th International Conference on Frontiers of Signal Processing (ICFSP) Pub Date : 2018-09-01 DOI: 10.1109/ICFSP.2018.8552075

Mengying Wang, Lele Xu, Lili Guo

{"title":"Anomaly Detection of System Logs Based on Natural Language Processing and Deep Learning","authors":"Mengying Wang, Lele Xu, Lili Guo","doi":"10.1109/ICFSP.2018.8552075","DOIUrl":"https://doi.org/10.1109/ICFSP.2018.8552075","url":null,"abstract":"System logs record the execution trajectory of the system and exist in all components of the system. Nowadays, the systems are deployed in a distributed environment and they generate logs which contain complex format and rich semantic information. Simple statistical analysis methods cannot fully capture log information for effective abnormal detection of software systems. In this paper, we propose to analyze the logs by combining feature extraction methods from natural language processing and anomaly detection methods from deep learning. Two feature extraction algorithms, Word2vec and Term Frequency-Inverse Document Frequency (TF-IDF), are respectively adopted and compared here to obtain the log information, and then one deep learning method named Long Short-Term Memory (LSTM) is applied for the anomaly detection. To validate the effectiveness of the proposed method, we compare LSTM with other machine learning algorithms, including Gradient Boosting Decision Tree (GBDT) and Naïve Bayes, the results show that LSTM can perform the best for anomaly detection of system logs with both of the two feature extraction methods, indicating that LSTM can capture contextual semantic information effectively in log anomaly detection and will be a promising tool for log analysis.","PeriodicalId":355222,"journal":{"name":"2018 4th International Conference on Frontiers of Signal Processing (ICFSP)","volume":"72 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123132915","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: 25

ICFSP 2018 Title Page ICFSP 2018标题页

2018 4th International Conference on Frontiers of Signal Processing (ICFSP) Pub Date : 2018-09-01 DOI: 10.1109/icfsp.2018.8552071

引用次数: 0

ICFSP 2018 Cover Page ICFSP 2018封面

2018 4th International Conference on Frontiers of Signal Processing (ICFSP) Pub Date : 2018-09-01 DOI: 10.1109/icfsp.2018.8552040

引用次数: 0

Low Cost Perovskite Solar Cell Performance under Ambient Condition 环境条件下低成本钙钛矿太阳能电池性能

2018 4th International Conference on Frontiers of Signal Processing (ICFSP) Pub Date : 2018-09-01 DOI: 10.1109/ICFSP.2018.8552072

N. R. Poespawati, A. Bastian, Elang Aji Defrianto, Michael Hariadi, T. Abuzairi, R. W. Purnamaningsih

引用次数: 1

Thin Cloud Removal Using Local Minimization and Logarithm Image Transformation in HSI Color Space HSI色彩空间中使用局部最小化和对数图像变换的薄云去除

2018 4th International Conference on Frontiers of Signal Processing (ICFSP) Pub Date : 2018-09-01 DOI: 10.1109/ICFSP.2018.8552064

Thanet Markchom, R. Lipikorn

{"title":"Thin Cloud Removal Using Local Minimization and Logarithm Image Transformation in HSI Color Space","authors":"Thanet Markchom, R. Lipikorn","doi":"10.1109/ICFSP.2018.8552064","DOIUrl":"https://doi.org/10.1109/ICFSP.2018.8552064","url":null,"abstract":"In observation of land information using satellite images, clouds are one of the most serious obstacles due to their opacity property which can block the visibility of ground objects and can also be blended with the underlying details. Hence, retrieval the actual information covered by clouds is frequently necessary. In this paper, we propose a novel method to remove clouds by taking an advantage of HSI color space instead of directly removing clouds in RGB color space. The proposed method uses a concept of dark channel prior method to estimate the cloud appearance called the scattering light and perform a subtraction in only the intensity channel to avoid an effect to the original color and also enhance the intensity with gamma correction to recover some information accidentally removed from the previous step and restore obscure details distorted by clouds. Furthermore, since clouds involve in both intensity and saturation channel, we increase the saturation that was reduced as a result from clouds by using logarithm image transformation as well. From the results, the proposed method can remove clouds that are not extremely opaque and preserve the actual information such as color and texture due to the higher contrast gain in the experiments comparing to the results obtained from other single-image methods.","PeriodicalId":355222,"journal":{"name":"2018 4th International Conference on Frontiers of Signal Processing (ICFSP)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124176759","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: 7

Video Scene Detection of Burst Swimming by Fry of Farmed-raised Bluefin Tuna 养殖蓝鳍金枪鱼鱼苗突发游动的视频场景检测

2018 4th International Conference on Frontiers of Signal Processing (ICFSP) Pub Date : 2018-09-01 DOI: 10.1109/ICFSP.2018.8552079

K. Abe, Masaru Tanaka, H. Habe, Y. Taniguchi, N. Iguchi

{"title":"Video Scene Detection of Burst Swimming by Fry of Farmed-raised Bluefin Tuna","authors":"K. Abe, Masaru Tanaka, H. Habe, Y. Taniguchi, N. Iguchi","doi":"10.1109/ICFSP.2018.8552079","DOIUrl":"https://doi.org/10.1109/ICFSP.2018.8552079","url":null,"abstract":"As a method for supporting aquaculture for bluefin tuna, this paper presents a video scene detection when a burst swimming is provoked by fry of farmed-raised bluefin tuna in land-based tanks due to environmental stimuli. From the fact the fry often die crashing to the tank’s wall and between the fry because of the burst swimming, this automated monitoring could use for analyzing environmental stimuli around the tanks when the burst swimming occurs and result in decrease of the death number of the fry. In the proposed method, the fry which swim in a land-based tank are monitored by a video camera and the video scenes at the burst swimming are detected by discriminant analysis with a feature value which represents fry’s acceleration using sequential frames of the moving image. Preparing the moving images which include scenes of the burst swimming by the fry, performances of the proposed method were examined. From experimental results, recall ratio of the scene detection has shown more than 57% in linear discriminant analysis and more than 98% in discriminant analysis by Mahalanobis distance.","PeriodicalId":355222,"journal":{"name":"2018 4th International Conference on Frontiers of Signal Processing (ICFSP)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130433115","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

Super-Resolved and Blurred Decoded Pictures for Improving Coding Efficiency in Inter-Frame Prediction 提高帧间预测编码效率的超分辨和模糊解码图像

2018 4th International Conference on Frontiers of Signal Processing (ICFSP) Pub Date : 2018-09-01 DOI: 10.1109/ICFSP.2018.8552056

Y. Matsuo, A. Ichigaya, Kikufumi Kanda

引用次数: 1

The Peculiarities of Collinear Acousto-optic Filtration in the Presence of Optoelectronic Feedback 光电反馈存在下共线声光滤波的特性

2018 4th International Conference on Frontiers of Signal Processing (ICFSP) Pub Date : 2018-09-01 DOI: 10.1109/ICFSP.2018.8552061

S. Mantsevich, V. Balakshy

引用次数: 2