2019 IEEE Conference on Information and Communication Technology最新文献_第4页

Stacked Filter Bank based descriptor for Human Action Recognition from Depth Sequences 基于堆叠滤波器组描述符的深度序列人体动作识别

2019 IEEE Conference on Information and Communication Technology Pub Date : 2019-12-01 DOI: 10.1109/CICT48419.2019.9066216

P. Rathnakara Shetty, B. H. Shekar, L. Mestetsky, M. Manju Prasad

引用次数: 1

Malaria Parasite Recognition in Thin Blood Smear Images using Squeeze and Excitation Networks 利用挤压和激励网络在薄血涂片图像中识别疟疾寄生虫

2019 IEEE Conference on Information and Communication Technology Pub Date : 2019-12-01 DOI: 10.1109/CICT48419.2019.9066150

S. Singh, Prakhar Bansal, Somesh Kumar, P. Shrivastava

{"title":"Malaria Parasite Recognition in Thin Blood Smear Images using Squeeze and Excitation Networks","authors":"S. Singh, Prakhar Bansal, Somesh Kumar, P. Shrivastava","doi":"10.1109/CICT48419.2019.9066150","DOIUrl":"https://doi.org/10.1109/CICT48419.2019.9066150","url":null,"abstract":"Malaria is a blood disease that is caused by the Plasmodium parasites transmitted through the bite of female Anopheles mosquito. To detect the existence of this parasite, the experts usually examine the thin blood smears. However, this requires considerable expertise in order to precisely make a distinction between the two categories. The result is that methods fail when the task of classification is largely-scaled. In recent times, researchers have started using machine learning techniques which require careful analysis of morphological, textural, and positional variations of the region of interest (ROI) in order to extract hand-engineered features. In this study, we tend to present an advanced method to automate the above process based upon the pre-trained CNN based model, SeNet. This model acts as a feature extractor towards classifying parasitized and uninfected cells. To carry out the process, we have used the dataset of microscopic images of red blood cells provided by United States National Library of Medicine. Our results show that the model achieved an accuracy of 97.24 % in identifying the malarial parasite in red blood cells. The AUC/ROC score (Area under Curve) came out to be around 0.97. The training loss was calculated using Categorical Cross-Entropy which was around 0.075. Statistical validation of the outcomes reveals the use of pre-trained CNNs as a favorable tool for feature extraction for this purpose.","PeriodicalId":234540,"journal":{"name":"2019 IEEE Conference on Information and Communication Technology","volume":"94 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132686899","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

Cyber Risk Assessment of Networked Cyber Assets using Probabilistic Model Checking 基于概率模型检验的网络资产网络风险评估

2019 IEEE Conference on Information and Communication Technology Pub Date : 2019-12-01 DOI: 10.1109/CICT48419.2019.9066178

Anand Handa, Subhasis Mukhopadhyay, Shankhadip Mallick, Nitesh Kumar, S. Shukla, Remish L. Minz, Sanjana Pai Nagarmat, R. Rakesh

引用次数: 2

Developing a Bayesian Network Framework for Root Cause Analysis of Observable Problems in Cyber-Physical Systems 开发一个贝叶斯网络框架，用于网络物理系统中可观察问题的根源分析

2019 IEEE Conference on Information and Communication Technology Pub Date : 2019-12-01 DOI: 10.1109/CICT48419.2019.9066167

S. Chockalingam, Vikash Katta

{"title":"Developing a Bayesian Network Framework for Root Cause Analysis of Observable Problems in Cyber-Physical Systems","authors":"S. Chockalingam, Vikash Katta","doi":"10.1109/CICT48419.2019.9066167","DOIUrl":"https://doi.org/10.1109/CICT48419.2019.9066167","url":null,"abstract":"Because critical infrastructures rely on Cyber-Physical Systems (CPSs), appropriate response to problems in such infrastructures operated by CPSs is important. Firstly, it is essential for decision-makers to be able to determine whether the observed problem is due to an attack or technical failure. In previous work, we developed a framework for building Bayesian Network (BN) models to enable decision-makers to determine whether the observed problem is due to an attack or technical failure. However, this information alone is not adequate to choose effective response strategies for the observed problem. It is also essential for the decisionmakers to be able to determine the most likely attack vector used to cause the observed problem or failure mode caused the observed problem to choose effective response strategies. However, the decision support to determine the most likely root cause for an observed problem is missing. In this paper, we develop a framework for building BN models to enable decisionmakers to determine the most likely root cause of problems. We demonstrate the developed framework using an example problem in smart grids.","PeriodicalId":234540,"journal":{"name":"2019 IEEE Conference on Information and Communication Technology","volume":"39 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132532641","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

Stacking based approach for prediction of faulty modules 基于堆叠的故障模块预测方法

2019 IEEE Conference on Information and Communication Technology Pub Date : 2019-12-01 DOI: 10.1109/CICT48419.2019.9066206

Pradeep Singh

引用次数: 5

Three Phase Authentication Protocol for Smart Grid Communication 智能电网通信的三相认证协议

2019 IEEE Conference on Information and Communication Technology Pub Date : 2019-12-01 DOI: 10.1109/CICT48419.2019.9066209

Himank Goel, Ayush Gupta, Harshit Jain, Aashutosh Khandelwal, Harsh Jain, Ayush Sinha, Ranjana Vyas

引用次数: 1

Investigating the Challenges and Methodologies of Sentiment Analysis 调查情感分析的挑战和方法

2019 IEEE Conference on Information and Communication Technology Pub Date : 2019-12-01 DOI: 10.1109/CICT48419.2019.9066186

Mayank Shrivastava, Shishir Kumar

引用次数: 1

Glaucoma Detection using Fuzzy C-means Optic Cup Segmentation and Feature Classification 基于模糊c均值光学杯分割和特征分类的青光眼检测

2019 IEEE Conference on Information and Communication Technology Pub Date : 2019-12-01 DOI: 10.1109/CICT48419.2019.9066165

Rakshita Karmawat, Neha Gour, P. Khanna

引用次数: 5

Tuning of Passbands in Compact Substrate Integrated Waveguide Bandpass Filter using perturbation slot 基于微扰槽的紧凑基板集成波导带通滤波器通带调谐

2019 IEEE Conference on Information and Communication Technology Pub Date : 2019-12-01 DOI: 10.1109/CICT48419.2019.9066219

S. S. Chaudhury, S. Awasthi, R. Singh

引用次数: 2

Impact of Channel Doping Fluctuation and Metal Gate Work Function Variation in FD-SOI MOSFET for 5nm BOX Thickness 5nm BOX厚度下FD-SOI MOSFET沟道掺杂波动和金属栅功函数变化的影响

2019 IEEE Conference on Information and Communication Technology Pub Date : 2019-12-01 DOI: 10.1109/CICT48419.2019.9066255

Avaneesh K. Dubey, P. K. Pal, Vikrant Varshney, Ankur Kumar, R. Nagaria

引用次数: 2