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2020 24th International Conference on Information Technology (IT)最新文献

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Video protection by color watermark using a modified cyclic insertion scheme 基于改进循环插入方案的彩色水印视频保护
2020 24th International Conference on Information Technology (IT) Pub Date : 2020-02-01 DOI: 10.1109/IT48810.2020.9070430
Z. Velickovic, Z. Milivojevic
{"title":"Video protection by color watermark using a modified cyclic insertion scheme","authors":"Z. Velickovic, Z. Milivojevic","doi":"10.1109/IT48810.2020.9070430","DOIUrl":"https://doi.org/10.1109/IT48810.2020.9070430","url":null,"abstract":"This paper presents an original algorithm for copyrighting video content by inserting a color watermark. The optimal parameters of the algorithm allow lossless watermark extraction from H.264 encoded video are determined. The proposed algorithm is based on YCbCr transformation, block SVD decomposition, bitplane decomposition and modified reduced cyclic insertion scheme. The results obtained confirm the effectiveness of the proposed algorithm and it can be successfully applied in the protection of video content by color watermark without visible degradation of video content.","PeriodicalId":220339,"journal":{"name":"2020 24th International Conference on Information Technology (IT)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129110418","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
Distributed Control Strategy for Multi-Agent Systems Using Consensus Among Followers 基于一致性的多智能体系统分布式控制策略
2020 24th International Conference on Information Technology (IT) Pub Date : 2020-02-01 DOI: 10.1109/IT48810.2020.9070617
Luka Martinović, Ž. Zečević, B. Krstajić
{"title":"Distributed Control Strategy for Multi-Agent Systems Using Consensus Among Followers","authors":"Luka Martinović, Ž. Zečević, B. Krstajić","doi":"10.1109/IT48810.2020.9070617","DOIUrl":"https://doi.org/10.1109/IT48810.2020.9070617","url":null,"abstract":"In this paper we introduce a novel distributed control strategy for coordinating the cooperative dynamic behavior in networked systems. The proposed control strategy is based on the leader-follower methodology with no communication between the leaders. Contrary to other solutions, the followers implement a dynamic consensus algorithm in such a way that each follower has full knowledge of the state of network of the followers. By using connection among leaders and followers each leader utilizes the information and implements a predefined control law. Simulation results show that this leads to the smaller mean square error in tracking the reference trajectory.","PeriodicalId":220339,"journal":{"name":"2020 24th International Conference on Information Technology (IT)","volume":"144 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126870130","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
Image-Based Plant Disease Detection: A Comparison of Deep Learning and Classical Machine Learning Algorithms 基于图像的植物病害检测:深度学习与经典机器学习算法的比较
2020 24th International Conference on Information Technology (IT) Pub Date : 2020-02-01 DOI: 10.1109/IT48810.2020.9070664
Draško Radovanović, Slobodan Đukanović
{"title":"Image-Based Plant Disease Detection: A Comparison of Deep Learning and Classical Machine Learning Algorithms","authors":"Draško Radovanović, Slobodan Đukanović","doi":"10.1109/IT48810.2020.9070664","DOIUrl":"https://doi.org/10.1109/IT48810.2020.9070664","url":null,"abstract":"Rapid human population growth requires corresponding increase in food production. Easily spreadable diseases can have a strong negative impact on plant yields and even destroy whole crops. That is why early disease diagnosis and prevention are of very high importance. Traditional methods rely on lab analysis and human expertise which are usually expensive and unavailable in a large part of the undeveloped world. Since smartphones are becoming increasingly present even in the most rural areas, in recent years scientists have turned to automated image analysis as a way of identifying crop diseases. This paper presents the most recent results in this field, and a comparison of deep learning approach with the classical machine learning algorithms.","PeriodicalId":220339,"journal":{"name":"2020 24th International Conference on Information Technology (IT)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129569542","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: 24
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