2018 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)最新文献_第7页

Short-term Bus Passenger Flow Forecast Based On Deep Learning 基于深度学习的短期公交客流预测

2018 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC) Pub Date : 2018-12-01 DOI: 10.1109/SPAC46244.2018.8965619

Xiaoshuang Li, Ziyan Chen, F. Zhu, Wei Chang, Chang Tan, Gang Xiong

引用次数: 3

The error metric based on roughness 基于粗糙度的误差度量

2018 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC) Pub Date : 2018-12-01 DOI: 10.1109/SPAC46244.2018.8965569

Ping Yu, Songjiang Wang, Yanlei Zong, Chong Liang

引用次数: 0

Finite-Time Fault-Tolerant Control for a Nonlinear SISO System with Actuator Faults 带有执行器故障的非线性SISO系统的有限时间容错控制

2018 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC) Pub Date : 2018-12-01 DOI: 10.1109/SPAC46244.2018.8965550

Shuai Sui, C. L. Chen

引用次数: 1

Image Recognition of Tea Leaf Diseases Based on Convolutional Neural Network 基于卷积神经网络的茶叶病害图像识别

2018 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC) Pub Date : 2018-12-01 DOI: 10.1109/SPAC46244.2018.8965555

Xiaoxiao Sun, Shaomin Mu, Yongyu Xu, Zhihao Cao, Tingting Su

引用次数: 35

Bag-of-visual-words Model for Image Classification Based on Spatial Semantic Distribution 基于空间语义分布的图像分类视觉词袋模型

2018 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC) Pub Date : 2018-12-01 DOI: 10.1109/SPAC46244.2018.8965481

Yong-Qin Li, Bu-Dong Xu, Hai-Di Sheng

{"title":"Bag-of-visual-words Model for Image Classification Based on Spatial Semantic Distribution","authors":"Yong-Qin Li, Bu-Dong Xu, Hai-Di Sheng","doi":"10.1109/SPAC46244.2018.8965481","DOIUrl":"https://doi.org/10.1109/SPAC46244.2018.8965481","url":null,"abstract":"To satisfy the requirement of image classification in the application of image retrieval, a novel method of image representation based on bag-of-visual-words model is proposed in the paper to describe the spatial semantic distribution of associated features. Firstly, the extracted SIFT features are mapped into visual words including certain semantic information. According to spatial pyramid hierarchy, the specific region is divided with local features, and the spatial distribution of associated features is analyzed from different aspects and in various regions. In this way, the semantic phrases are established with local features. Next, the spatial semantic lexicon is constructed with sparse encoding of spatial semantic phrases, and the images are described with the form of sparse statistical histogram vectors. Finally, the vectors of images are classified with the classifier embedded with the improved bag-of-visual-words model. The experimental results show that the accuracy of image classification is significantly enhanced which is benefited from the Bag-of-visual-words model with spatial semantic distribution.","PeriodicalId":360369,"journal":{"name":"2018 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)","volume":"294 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132896370","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

Research on the Influencing Factors of Regional Financial Risk under Internet Financial Innovation 互联网金融创新下的区域金融风险影响因素研究

2018 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC) Pub Date : 2018-12-01 DOI: 10.1109/SPAC46244.2018.8965529

Chunran Wen, Xuan Shen, Zhiping Zhou

引用次数: 0

Hand-dorsa Vein Recognition based on Deep Learning 基于深度学习的手背静脉识别

2018 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC) Pub Date : 2018-12-01 DOI: 10.1109/SPAC46244.2018.8965546

Kefeng Li, Guangyuan Zhang, Peng Wang

引用次数: 0

Medical entity recognition of Esophageal Carcinoma based on word clustering 基于词聚类的食管癌医学实体识别

2018 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC) Pub Date : 2018-12-01 DOI: 10.1109/SPAC46244.2018.8965515

Rui Wang, Jinfeng Zhao, Lizhi Peng, Bo Yang, Lin Wang, Baosheng Li

{"title":"Medical entity recognition of Esophageal Carcinoma based on word clustering","authors":"Rui Wang, Jinfeng Zhao, Lizhi Peng, Bo Yang, Lin Wang, Baosheng Li","doi":"10.1109/SPAC46244.2018.8965515","DOIUrl":"https://doi.org/10.1109/SPAC46244.2018.8965515","url":null,"abstract":"Electronic Medical Records (EMRs) is the core of medical information system in hospital. EMRs arises from the medical institution, and large amount of clinical data generated every day. Due to the EMRs contains many medical entities and clinical information of the patient, by analyzing and mining the texts data, medical knowledge which closely related to patients or certain diseases can be obtained. In this paper, we ues the EMRs of patients with Esophageal Carcinoma(EC), which include the clinical symptoms of the patients, tests they have undergone, results of the examinations, and the diagnosis and treatment plan. In this paper, word vector training is carried out for large-scale electronic medical record corpus by means of the skip model of word2vec deep learning tool. Then applying the features data to the k-means clustering algorithm to identifying medical entities about EC by word clustering. As the first step of medical knowledge mining, medical entity recognition is the premise of extracting the semantic relationship implied in medical text and structuring EMRs.","PeriodicalId":360369,"journal":{"name":"2018 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123756032","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: 4

Smoking Behavior Detection Based on Hand Trajectory Tracking and Mouth Saturation Changes 基于手部轨迹跟踪和口腔饱和度变化的吸烟行为检测

2018 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC) Pub Date : 2018-12-01 DOI: 10.1109/SPAC46244.2018.8965455

Zhenkai Lin, Changfeng Lv, Yimin Dou, Jinping Li

{"title":"Smoking Behavior Detection Based on Hand Trajectory Tracking and Mouth Saturation Changes","authors":"Zhenkai Lin, Changfeng Lv, Yimin Dou, Jinping Li","doi":"10.1109/SPAC46244.2018.8965455","DOIUrl":"https://doi.org/10.1109/SPAC46244.2018.8965455","url":null,"abstract":"Smoking seriously endanger people's physical and mental health. In some special places, e.g., gas stations and forest areas, smoking may cause serious accidents. In order to detect smoking behavior timely and accurately, we propose an effective and practical detection method by means of video analysis. Two basic approaches are involved in the proposed method: one is smoke detection; the other is smoking action detection. In the first approach, we detect human face by using a special open source of face detection system called SeetaFace, then segment the mouth area and calculate the corresponding grayscale and saturation, finally we can determine if sudden a change occurs around the mouth. In the second approach, there are two basic steps: firstly, we detect the skin color area based on the skin color ellipse model in YCrCb color space, then determine the initial position of the hand by using the location of the skin color area that relative to the face; secondly, track the trajectory of hand movement by using optical flow and then detect whether the hand overlap the mouth in real time. Finally, we combine the results of the preceding two steps in the second approach with the result in the first approach together and then we can determine smoking or non-smoking person. The experimental results show that the proposed method can effectively detect smoking behavior with a small training sample in real time and achieve the detection rate of 95%.","PeriodicalId":360369,"journal":{"name":"2018 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115383208","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

Evaluation and Prediction of Entrepreneurial Intention Based on Entrepreneurial Psychological Capital and Work Value of University Students: Using BP Neural Network Method 基于创业心理资本和工作价值的大学生创业意向评价与预测——基于BP神经网络方法

2018 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC) Pub Date : 2018-12-01 DOI: 10.1109/SPAC46244.2018.8965499

Yinghong Sun, Peng Wu, Jin Zhou, Dong Wang

引用次数: 0