Proceedings of the 5th International Conference on Computer Science and Software Engineering最新文献_第7页

UAV signal recognition technology 无人机信号识别技术

Proceedings of the 5th International Conference on Computer Science and Software Engineering Pub Date : 2022-10-21 DOI: 10.1145/3569966.3571186

Yin Xue, Yuan-Lung Chang, Yu Zhang, Jiajun Ma, Guangjie Li, Q. Zhan, Dandan Wu, Jiancun Zuo

引用次数: 2

3D Model Retrieval Algorithm Based on Attention and Multi-view Fusion 基于注意力和多视角融合的三维模型检索算法

Proceedings of the 5th International Conference on Computer Science and Software Engineering Pub Date : 2022-10-21 DOI: 10.1145/3569966.3570092

Ziqi Shi, Ziyang Quan, Jingshan Shi, Zhuyan Guo, Mandun Zhang, Zhidong Xiao

{"title":"3D Model Retrieval Algorithm Based on Attention and Multi-view Fusion","authors":"Ziqi Shi, Ziyang Quan, Jingshan Shi, Zhuyan Guo, Mandun Zhang, Zhidong Xiao","doi":"10.1145/3569966.3570092","DOIUrl":"https://doi.org/10.1145/3569966.3570092","url":null,"abstract":"With the rapid development of computer vision, 3D data is increasing rapidly. How to retrieve similar model from a large number of models has become a hot research topic. However, in order to meet people's demand, the retrieval accuracy need to be further improved. In terms of multi-view 3D model retrieval, how to effectively learn the information between views is the key to improving performance. In this paper, we propose a novel 3D model retrieval algorithm based on attention and multi-view fusion. Specifically, we mainly constructed two modules. First, dynamic attentive graph learning module is used to learn the intrinsic relationship between view blocks; Then we propose the Attention-NetVlad algorithm, which combines the channel attention algorithm and the NetVlad algorithm. It learns the information between feature channels to enhance the feature expression ability firstly, then uses the NetVlad algorithm to fuse multiple view features into a global feature according to the clustering information. Finally the global feature is used as the only feature of the model to retrieve according to Euclidean distance. In comparison with other state-of-the-art methods by utilizing ModelNet10 and ModelNet40 the proposed method has demonstrated significant improvement for retrieval mAP. Our experiments also demonstrate the effectiveness of the modules in the algorithm.","PeriodicalId":145580,"journal":{"name":"Proceedings of the 5th International Conference on Computer Science and Software Engineering","volume":"17 17","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132644882","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

A task allocation algorithm for Coverage-Aware Crowdsensing with Data timeliness 具有数据时效性的覆盖感知众测任务分配算法

Proceedings of the 5th International Conference on Computer Science and Software Engineering Pub Date : 2022-10-21 DOI: 10.1145/3569966.3570083

Chenxi Pan, Shuyu Li

引用次数: 0

A Comprehensive Study to Analyze Trends in Web Search Interests Related to Fall Detection Before and After COVID-19 新型冠状病毒肺炎前后跌倒检测相关网络搜索兴趣趋势综合分析

Proceedings of the 5th International Conference on Computer Science and Software Engineering Pub Date : 2022-10-21 DOI: 10.1145/3569966.3571193

Nirmalya Thakur, Isabella Hall, Chia Y. Han

{"title":"A Comprehensive Study to Analyze Trends in Web Search Interests Related to Fall Detection Before and After COVID-19","authors":"Nirmalya Thakur, Isabella Hall, Chia Y. Han","doi":"10.1145/3569966.3571193","DOIUrl":"https://doi.org/10.1145/3569966.3571193","url":null,"abstract":"Falls, considered a serious health-related concern for the elderly people, are associated with multiple diverse and dynamic needs for the elderly people themselves, their caregivers, their family members, and healthcare professionals. The modern-day Internet of Everything lifestyle is characterized by people using the internet for a multitude of reasons which also includes seeking and sharing information related to such needs. Such activity on the internet results in the generation of tremendous amounts of web behavior-based Big Data which can be studied and analyzed to investigate the trends in the underlining needs and the associated web search interests. The COVID-19 pandemic that the world is facing right now has impacted the elderly population to a significant extent. In fact, the elderly population is considered a demographic group that is most likely to get infected by this virus and develop serious symptoms, which could lead to hospitalizations and death. There hasn't been any study conducted in the field of aging research thus far that investigates how the COVID-19 pandemic may or may not have impacted the needs related to fall detection in the elderly. This work aims to address this research challenge. A dedicated methodology based on Google Trends is proposed in this paper that studies the web behavior-based Big Data related to fall detection from different countries both before and after the pandemic. The preliminary results presented from the analysis of the web behavior-based Big Data from 14 countries - USA, India, Germany, United Kingdom, Spain, Australia, Indonesia, Malaysia, Thailand, South Africa, Canada, Philippines, Sweden, and Ireland, which are amongst the countries worst hit by COVID-19, shows evidence that the pandemic had an impact towards increasing the web search interests related to fall detection in multiple countries.","PeriodicalId":145580,"journal":{"name":"Proceedings of the 5th International Conference on Computer Science and Software Engineering","volume":"190 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115010326","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

Underwater Acoustic Point-cloud Filtering via Adaptive Unsharp Masking 基于自适应非锐化掩蔽的水声点云滤波

Proceedings of the 5th International Conference on Computer Science and Software Engineering Pub Date : 2022-10-21 DOI: 10.1145/3569966.3570052

Jisong Wang, Xuewu Zhang, Xiaolong Xu, Ke-Pu Song

{"title":"Underwater Acoustic Point-cloud Filtering via Adaptive Unsharp Masking","authors":"Jisong Wang, Xuewu Zhang, Xiaolong Xu, Ke-Pu Song","doi":"10.1145/3569966.3570052","DOIUrl":"https://doi.org/10.1145/3569966.3570052","url":null,"abstract":"Owing to the complex water environment, the acoustic point-cloud model formed by the detection method based on acoustic reflection mechanism is inevitably disturbed by the noise, which seriously affects the reconstruction effect of the underwater targets. Distinguishing between geometric features and noise is of paramount importance for the underwater point-cloud model filtering. Inspired by the classic image detail enhancement method of unsharp masking, we take the geometric coordinate information of the point as the research object and design a geometric feature-preserving adaptive unsharp masking filtering for the underwater point-cloud model. First, the proposed method directly performed a low-pass filtering using the neighborhood information to obtain the main structure of the input point-cloud model. Second, the detail layer was yielded by the difference between the input point-cloud model and the base layer. Third, the different scaling factors measuring the importance of the points with respect to the whole base layer were used to adaptively enhance the detail layer. Experimental results show that the proposed algorithm can effectively remove noise while maintaining the geometric characteristics of the model, which is obviously better than other comparison methods.","PeriodicalId":145580,"journal":{"name":"Proceedings of the 5th International Conference on Computer Science and Software Engineering","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114932974","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

Skin melanoma segmentation algorithm using dual-channel efficient CNN network 基于双通道高效CNN网络的皮肤黑色素瘤分割算法

Proceedings of the 5th International Conference on Computer Science and Software Engineering Pub Date : 2022-10-21 DOI: 10.1145/3569966.3570104

Yadi Zhen, Jianbing Yi, Feng Cao, Jun Li, Jun Wu

引用次数: 0

A Novel Image perceptual hashing algorithm based on frequency decomposition and LoG 一种基于频率分解和LoG的图像感知哈希算法

Proceedings of the 5th International Conference on Computer Science and Software Engineering Pub Date : 2022-10-21 DOI: 10.1145/3569966.3570057

Zihao Yang, Guosheng Hao, Xiaoyun Zhou, Wang Ruan

引用次数: 0

A new method for detecting binary random sequences in cryptography: First interval test for non-overlapping templates 一种检测密码学中二进制随机序列的新方法:非重叠模板的第一间隔检验

Proceedings of the 5th International Conference on Computer Science and Software Engineering Pub Date : 2022-10-21 DOI: 10.1145/3569966.3569968

Xia Wu, Sheng Lin

{"title":"A new method for detecting binary random sequences in cryptography: First interval test for non-overlapping templates","authors":"Xia Wu, Sheng Lin","doi":"10.1145/3569966.3569968","DOIUrl":"https://doi.org/10.1145/3569966.3569968","url":null,"abstract":"ABSTRACT: In the application of various fields of cryptography, the generation of the key should be random, because it directly determines the security of the system, so the detection of the random generation of the key is a crucial work in cryptography. Different detection methods detect different properties of sequences. The first interval test of non-overlapping templates introduced in this paper is mainly aimed at testing the frequency of the first interval of the specified template in the sequence. When the frequency of the first interval of the specified template conforms to the ideal distribution, the randomness hypothesis is accepted. On the contrary, the specific frequency the template, random hypothesis is rejected. This method focuses more on specifying the interval frequency of the occurrence of the template than some methods of checking the frequency of the occurrence of the template in the whole sequence. In addition, the sequence length examined by this detection method can be short or long. Compared with the random number detection method, the method introduced in this paper is more inclusive.","PeriodicalId":145580,"journal":{"name":"Proceedings of the 5th International Conference on Computer Science and Software Engineering","volume":"734 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116109801","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 Short-term Load Forecasting of Power System Based on Wavelet Denoising and Artificial Neural Network 基于小波去噪和人工神经网络的电力系统短期负荷预测研究

Proceedings of the 5th International Conference on Computer Science and Software Engineering Pub Date : 2022-10-21 DOI: 10.1145/3569966.3569982

Zihan Liu

引用次数: 0

Fusion of multispectral and panchromatic images via convolutional sparse representation and morphological filter 基于卷积稀疏表示和形态滤波的多光谱与全色图像融合

Proceedings of the 5th International Conference on Computer Science and Software Engineering Pub Date : 2022-10-21 DOI: 10.1145/3569966.3570103

Jiao Jiao, Depeng Chen, Shaobo Yu, Xin Guo

引用次数: 0