2019 9th International Conference on Computer and Knowledge Engineering (ICCKE)最新文献_第4页

Toward real-time object detection on heterogeneous embedded systems 异构嵌入式系统实时目标检测研究

2019 9th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2019-10-01 DOI: 10.1109/ICCKE48569.2019.8964764

Milad Niazi-Razavi, Abdorreza Savadi, Hamid Noori

{"title":"Toward real-time object detection on heterogeneous embedded systems","authors":"Milad Niazi-Razavi, Abdorreza Savadi, Hamid Noori","doi":"10.1109/ICCKE48569.2019.8964764","DOIUrl":"https://doi.org/10.1109/ICCKE48569.2019.8964764","url":null,"abstract":"low power consumption and high efficiency of heterogeneous systems improves processing power and enables the implementation of real-time applications. Deep learning, as one of the hottest topics of today, plays an important role in solving difficult problems such as machine vision. The use of traditional methods for solving visual machine problems requires the engineering of features by humans, which makes it difficult to create a comprehensive model for a problem. The use of revolutionary deep learning in the machine vision, which along with the embedded systems can be useful in many today's issues. Convolutional neural networks have shown a high degree of efficiency in the task of categorizing images and detecting objects. An important feature in neural networks is the intrinsic parallelism of its structure, which results in the use of embedded heterogeneous systems that can provide excellent performance in the implementation of neural networks. Implementing real-time objects detection systems in enclosed environments with limited computing resources and memory is challenging. This paper presents a method for implementing the MobileNet-SSD object detection system on the Jetson TK1, which attempts to improve performance by changing the network's convoys and dividing tasks between the central and the graphics processor.","PeriodicalId":6685,"journal":{"name":"2019 9th International Conference on Computer and Knowledge Engineering (ICCKE)","volume":"21 1","pages":"450-454"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81508227","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: 3

Glioma Brain Tumors Diagnosis and Classification in MR Images based on Convolutional Neural Networks 基于卷积神经网络的脑胶质瘤MR图像诊断与分类

2019 9th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2019-10-01 DOI: 10.1109/ICCKE48569.2019.8965143

Fatemeh Bashir Gonbadi, Hassan Khotanlou

引用次数: 5

A Fast Hybrid Feature Selection Method 一种快速混合特征选择方法

2019 9th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2019-10-01 DOI: 10.1109/ICCKE48569.2019.8964884

Mohammad Ahmadi Ganjei, R. Boostani

{"title":"A Fast Hybrid Feature Selection Method","authors":"Mohammad Ahmadi Ganjei, R. Boostani","doi":"10.1109/ICCKE48569.2019.8964884","DOIUrl":"https://doi.org/10.1109/ICCKE48569.2019.8964884","url":null,"abstract":"To confront with high dimensional datasets, several feature selection schemes have been suggested in three types of wrapper, filter, and hybrid. Hybrid feature selection methods adopt both filter and wrapper approaches by compromising between the computational complexity and efficiency. In this paper, we proposed a new hybrid feature selection method, in which in the filter stage the features are ranked according to their relevance. Instead of running the wrapper on all the features, we use a split-to-blocks technique and show that block size has a considerable impact on performance. A sequential forward selection (SFS) method was applied to the ranked blocks of features in order to find the most relevant features. The proposed method rapidly eliminates a large number of irrelevant features in its ranking stage, and then different block sizes were evaluated in the wrapper phase by choosing a proper block size using SFS. It causes this method to have a low time complexity, despite the good results. Hybrid methods consist of components that have different criteria for them. we compare and analyze different criteria. To show the effectiveness of the proposed method, state-of-the-art hybrid feature selection methods like re-Ranking, IGIS, and IGIS+ were implemented and their classification accuracies, over the known benchmarks, were computed using the K-nearest neighbor (KNN) and decision tree classifiers. Applying statistical tests to the compared results supports the superiority of the proposed method to the counterparts.","PeriodicalId":6685,"journal":{"name":"2019 9th International Conference on Computer and Knowledge Engineering (ICCKE)","volume":"1 1","pages":"6-11"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89820358","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

A Genetic Asexual Reproduction Optimization Algorithm for Imputing Missing Values 缺失值输入的遗传无性繁殖优化算法

2019 9th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2019-10-01 DOI: 10.1109/ICCKE48569.2019.8964808

M. Noei, M. S. Abadeh

{"title":"A Genetic Asexual Reproduction Optimization Algorithm for Imputing Missing Values","authors":"M. Noei, M. S. Abadeh","doi":"10.1109/ICCKE48569.2019.8964808","DOIUrl":"https://doi.org/10.1109/ICCKE48569.2019.8964808","url":null,"abstract":"In this paper, we suggest a new technique that significantly improve the computational time of the genetic algorithm for imputing missing values. Data contain noise and missing values, which made them unreliable for scientific purposes. Due to this, we are required to preprocess these data before using them. Researchers either avoid or impute missing data. It is necessary to choose an appropriate imputation method, and it is based on several factors such as datatypes and numbers of missing data. For a higher missing value rate, missing value imputation (MVI) can be suitable way for imputing missing data in incomplete dataset. One of the MVI methods is the genetic algorithm; although genetic algorithm may produce good results, the computational time is very high. The proposed algorithm is a combination of the genetic and Asexual Reproduction Optimization (ARO) algorithm. We present an experimental evaluation of Pima and mammographic mass dataset that collected from UCI repository. In the small percentage of missing values, those instances can be imputed by the ARO algorithm, but in the case of large amounts, our approach illustrates much better results. This proposed technique works even better when the rate of missing values is higher. The accuracy and computational time of our proposed algorithm are compared with another techniques like Mean, K-Nearest Neighbor, and SVM. On average our approach 8% improved the accuracy and 4% improved the ROC, and it requires less computational time than a basic genetic algorithm.","PeriodicalId":6685,"journal":{"name":"2019 9th International Conference on Computer and Knowledge Engineering (ICCKE)","volume":"9 1","pages":"214-218"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75055910","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: 11

An Automatic Method for Morphological Abnormality Detection in Metaphase II Human Oocyte Images 人卵母细胞中期形态异常自动检测方法研究

2019 9th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2019-10-01 DOI: 10.1109/ICCKE48569.2019.8964838

Sedighe Firuzinia, S. Mirroshandel, F. Ghasemian, Seyed Mahmoodreza Afzali

{"title":"An Automatic Method for Morphological Abnormality Detection in Metaphase II Human Oocyte Images","authors":"Sedighe Firuzinia, S. Mirroshandel, F. Ghasemian, Seyed Mahmoodreza Afzali","doi":"10.1109/ICCKE48569.2019.8964838","DOIUrl":"https://doi.org/10.1109/ICCKE48569.2019.8964838","url":null,"abstract":"The morphological evaluation of metaphase II (MII) oocytes before Intra-Cytoplasmic Sperm Injection (ICSI) can help to know and predict their developmental potential, the ICSI outcomes, and transfer the best embryo. The main morphometric features of MII oocytes are the thickness of zona pellucida, the width of perivitelline space, and the area of ooplasm and oocyte. Manual characterization of the MII oocytes can be prone to high inter-observer and intra-observer variability. In this study, we propose a fully automatic algorithm to identify malformations in images of human oocytes. 1500 images of MII oocytes were taken using inverted microscope before the ICSI process to build a dataset, namely the Human MII Oocyte Morphology Analysis Dataset (HMOMA-DS). The three main components of these prepared oocytes are analyzed. As the first step, we eliminated the noise and enhanced the quality of our input image. Further the regions were detected and segmented. Finally, the quality of the oocyte was assessed in terms of measuring the size and area of its main components. We have applied our method to the prepared dataset. It has been able to achieve an accuracy of 98.51% for the thickness of zona pellucida and area of oocyte. The accuracy values for measuring the area of ooplasm and the width of perivitelline space were 99.25% and 91.08%, respectively. The proposed fully automatic method performs effectively before ICSI due to its high accuracy and low computation time. It can help embryologists to select the best-qualified embryo based on the available analyzed parameters from injected oocytes in real-time.","PeriodicalId":6685,"journal":{"name":"2019 9th International Conference on Computer and Knowledge Engineering (ICCKE)","volume":"2 3 1","pages":"91-97"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79893418","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

An Automated Method for Selecting GoF Design Patterns GoF设计模式的自动选择方法

2019 9th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2019-10-01 DOI: 10.1109/ICCKE48569.2019.8965221

Raheleh Rahmati, A. Rasoolzadegan, Diyana Tehrany Dehkordy

引用次数: 5

Improved Answer Selection For Factoid Questions 改进了虚假问题的答案选择

2019 9th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2019-10-01 DOI: 10.1109/ICCKE48569.2019.8965131

Jamshid Mozafari, M. Nematbakhsh, A. Fatemi

{"title":"Improved Answer Selection For Factoid Questions","authors":"Jamshid Mozafari, M. Nematbakhsh, A. Fatemi","doi":"10.1109/ICCKE48569.2019.8965131","DOIUrl":"https://doi.org/10.1109/ICCKE48569.2019.8965131","url":null,"abstract":"In recent years, question and answer systems and information retrieval have been widely used by web users. The purpose of these systems is to find answers to users' questions. These systems consist of several components that the most essential of which is the Answer Selection, which finds the most relevant answer. In related works, the proposed models used lexical features to measure the similarity of sentences, but in recent works, the line of research has changed. They used deep neural networks. In the deep neural networks, early, recurrent neural networks were used due to the sequencing structure of the text, but in state of the art works, convolutional neural networks are used. We represent a new method based on deep neural network algorithms in this research. This method attempts to find the correct answer to a given question from the pool of responses. Our proposed method uses wide convolution instead of narrow convolution, concatenates sparse features vector into feature vector and uses dropout in order to rank candidate answers of the user’s question semantically. The results show a 1.01% improvement at the MAP and a 0.2% improvement at the MRR metrics than the best previous model. The experiments show using context-sensitive interactions between input sentences is useful for finding the best answer.","PeriodicalId":6685,"journal":{"name":"2019 9th International Conference on Computer and Knowledge Engineering (ICCKE)","volume":"39 1","pages":"143-148"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91209956","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

MC-RPL: A New Routing Approach based on Multi-Criteria RPL for the Internet of Things MC-RPL:一种基于多准则RPL的物联网路由新方法

2019 9th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2019-10-01 DOI: 10.1109/ICCKE48569.2019.8964675

Behnam Farzaneh, A. Ahmed, Emad Alizadeh

引用次数: 9

Behavioral Entropy Towards Detection of Metamorphic Malwares 面向变形恶意软件检测的行为熵

2019 9th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2019-10-01 DOI: 10.1109/ICCKE48569.2019.8964967

Kambiz Vahedi, M. Abbaspour, Khadijeh Afhamisisi, Mohammad Rashidnejad

{"title":"Behavioral Entropy Towards Detection of Metamorphic Malwares","authors":"Kambiz Vahedi, M. Abbaspour, Khadijeh Afhamisisi, Mohammad Rashidnejad","doi":"10.1109/ICCKE48569.2019.8964967","DOIUrl":"https://doi.org/10.1109/ICCKE48569.2019.8964967","url":null,"abstract":"Recent metamorphic malware detection methods based on statistical analysis of malware code and measuring similarity between codes are by far more superior compared with signature-based detection methods; yet, lacking against code obfuscation methods including insertion of garbage codes similar to benign files and replacing instructions with equivalent instructions. This paper proposes a method on improved detection of metamorphic malwares based on activity and behavior analysis of executable files. The process involves two stages: initially, behavior of the file is analyzed during runtime and the behavioral pattern is obtained; then, in the second stage, behavioral patterns of the malware files are compared with the sample file in order to determine the level of similarity. The stage on analyzing behavior of the file is accomplished in a monitored environment and then malicious behavioral features of the file are extracted. The second stage involves determining level of similarity between malwares registered into the database in the first stage and the sample files. The obtained experimental results show that the proposed method, by determining the similarity level of behavioral patterns, significantly improves detection of metamorphic malwares and along with no false positives.","PeriodicalId":6685,"journal":{"name":"2019 9th International Conference on Computer and Knowledge Engineering (ICCKE)","volume":"22 1","pages":"78-84"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90834439","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: 3

Toward a Distinguishing Approach for Improving the Apriori Algorithm 一种改进Apriori算法的判别方法

2019 9th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2019-10-01 DOI: 10.1109/ICCKE48569.2019.8965206

Mahdieh Dehghani, A. Kamandi, M. Shabankhah, A. Moeini

{"title":"Toward a Distinguishing Approach for Improving the Apriori Algorithm","authors":"Mahdieh Dehghani, A. Kamandi, M. Shabankhah, A. Moeini","doi":"10.1109/ICCKE48569.2019.8965206","DOIUrl":"https://doi.org/10.1109/ICCKE48569.2019.8965206","url":null,"abstract":"Association rule mining, one of the most important branches of data mining, which focused on detecting frequent patterns of itemsets. Apriori is the first algorithm proposed for association rule mining. This algorithm has the best response and can detect all frequent itemsets from transaction databases. Apriori is of time complexity order two to the power n at worst case, n is the number of items in the database. At each step, the database is scanned to detect frequent itemsets. As a result, this algorithm has a very large response time for large databases. There are two ways to reduce the response time of this algorithm. First, prune the itemsets which candidate for checking. Second, reduce the dimension of the database. We used the second solution and reduce the dimension of the database considering that if a set is frequent, all of its subsets are frequent with more frequencies in the database. In the proposed algorithm, database scanned one time, and then frequent itemsets are detected by the reduced database. Our algorithm improved an apriori response time. To evaluate the algorithm, precision and recall measures have been used. According to the experimental in most cases, the algorithm can provide precision and recall above ninety percent.","PeriodicalId":6685,"journal":{"name":"2019 9th International Conference on Computer and Knowledge Engineering (ICCKE)","volume":"48 1","pages":"309-314"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90394534","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