2021 IEEE 13th International Conference on Computer Research and Development (ICCRD)最新文献

A Noise-Assisted Polar Code Attempt Decoding Algorithm 一种噪声辅助极化码尝试译码算法

2021 IEEE 13th International Conference on Computer Research and Development (ICCRD) Pub Date : 2021-01-05 DOI: 10.1109/ICCRD51685.2021.9386557

He Zhanquan, L. Xiaoqing, W. Shusheng, Qian YueZhen

{"title":"A Noise-Assisted Polar Code Attempt Decoding Algorithm","authors":"He Zhanquan, L. Xiaoqing, W. Shusheng, Qian YueZhen","doi":"10.1109/ICCRD51685.2021.9386557","DOIUrl":"https://doi.org/10.1109/ICCRD51685.2021.9386557","url":null,"abstract":"Aiming at the characteristics of Polar codes, this paper proposes a noise-assisted Polar code attempt decoding algorithm based on the analysis of frame error rate and bit error rate to improve Polar code decoding performance. The basic principle of the algorithm is that when the encoded data frame is transmitted through the channel, the signal-to-noise ratio is decreased. When the received signal exceeds the decoding capability and cannot be decoded normally, the auxiliary man-made noise is added to make the received signal to have a lower decision probability. The addition of low-power man-made noise will result in further randomization of the region with poor reliability of the original sampled data signal (close to zeros for BPSK modulation), and the bit rollover probability of the higher reliability of the sampled data is smaller. Under this condition, attempt to decode, if check data correct, decode finished, otherwise regenerate man-made noise for the next attempt until the decoding passes or reaches the maximum. This algorithm is a post-compensation processing method for existing algorithms, which play an incremental role.","PeriodicalId":294200,"journal":{"name":"2021 IEEE 13th International Conference on Computer Research and Development (ICCRD)","volume":"45 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120922551","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

Surgical Action and Instrument Detection Based on Multiscale Information Fusion 基于多尺度信息融合的手术动作与器械检测

2021 IEEE 13th International Conference on Computer Research and Development (ICCRD) Pub Date : 2021-01-05 DOI: 10.1109/ICCRD51685.2021.9386349

Wenting Xu, Ruiguo Liu, Weifeng Zhang, Z. Chao, F. Jia

{"title":"Surgical Action and Instrument Detection Based on Multiscale Information Fusion","authors":"Wenting Xu, Ruiguo Liu, Weifeng Zhang, Z. Chao, F. Jia","doi":"10.1109/ICCRD51685.2021.9386349","DOIUrl":"https://doi.org/10.1109/ICCRD51685.2021.9386349","url":null,"abstract":"The detection of surgical actions and instruments plays a very important role in computer-assisted endoscopic surgery. However, organ deformation and narrow surgical field increase the task difficulty. Accordingly, the problems of the detection of surgical actions and instruments have not been solved yet. In this paper, we proposed a multiscale fusion feature pyramid network (MSF-FPN) to merge low-level semantic information and high-level semantic information. Firstly, the feature map effectively aggregates the information by the initial layer of the pyramid network, and then diverges after the cross-transmission of the feature information in the middle layer. Finally, a strong semantic feature map was obtained in the output layer. Experiments verified that the average precision of the proposed MSF-FPN on the public endoscopic surgeon action detection (ESAD) dataset is increased by 2.9% and 1.5% compared with the general FPN and path aggregation network (PANet), and the average precision on the proposed cataract-based object detection (COD) dataset is increased by 4.3% and 2.6%, respectively.","PeriodicalId":294200,"journal":{"name":"2021 IEEE 13th International Conference on Computer Research and Development (ICCRD)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132215043","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 Design of Volunteer Computing System Based on Blockchain 基于区块链的志愿者计算系统设计

2021 IEEE 13th International Conference on Computer Research and Development (ICCRD) Pub Date : 2021-01-05 DOI: 10.1109/ICCRD51685.2021.9386703

Boxuan Shan

{"title":"A Design of Volunteer Computing System Based on Blockchain","authors":"Boxuan Shan","doi":"10.1109/ICCRD51685.2021.9386703","DOIUrl":"https://doi.org/10.1109/ICCRD51685.2021.9386703","url":null,"abstract":"In recent years, the application range of blockchain has become more and more extensive. This paper proposed a volunteer computing system design based on the blockchain. This system takes advantage of the decentralized, persistent and auditable characteristics of the blockchain to solve the scalability and single point of failure problem under the traditional centralized C/S framework and provides a certain traceability for volunteer calculations. Increased scalability implies that the system can accommodate more computing jobs and participants. Solving the single-point failure problem implies that the volunteer computing system can provide researchers with longer-term and more stable computing resources. The traceability implies that anyone can view the blockchain to understand which volunteers have participated in every computing work in history and the adoption of the results provided by each volunteer. At the same time, with the help of the persistence and auditability of the blockchain, the authenticity of history can be ensured. This paper studies the C/S framework volunteer computing as well as blockchain, and proposes a framework for volunteer computing based on the blockchain. Then discussed its pros and cons in terms of feasibility, scalability, security, authenticity, traceability etc.","PeriodicalId":294200,"journal":{"name":"2021 IEEE 13th International Conference on Computer Research and Development (ICCRD)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131199398","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

SRWGANTV: Image Super-Resolution Through Wasserstein Generative Adversarial Networks with Total Variational Regularization SRWGANTV:基于全变分正则化的Wasserstein生成对抗网络的图像超分辨率

2021 IEEE 13th International Conference on Computer Research and Development (ICCRD) Pub Date : 2021-01-05 DOI: 10.1109/ICCRD51685.2021.9386518

Jun Shao, Liang Chen, Yi Wu

{"title":"SRWGANTV: Image Super-Resolution Through Wasserstein Generative Adversarial Networks with Total Variational Regularization","authors":"Jun Shao, Liang Chen, Yi Wu","doi":"10.1109/ICCRD51685.2021.9386518","DOIUrl":"https://doi.org/10.1109/ICCRD51685.2021.9386518","url":null,"abstract":"The study of generative adversarial networks (GAN) has enormously promoted the research work on single image super-resolution (SISR) problem. SRGAN firstly apply GAN to SISR reconstruction, which has achieved good results. However, SRGAN sacrifices the fidelity. At the same time, it is well known that the GANs are difficult to train and the improper training fails the SISR results easily. Recently, Wasserstein Generative Adversarial Network with gradient penalty (WGAN-GP) has been proposed to alleviate these issues at the expense of performance of the model with a relatively simple training process. However, we find that applying WGAN-GP to SISR still suffers from training instability, leading to failure to obtain a good SR result. To address this problem, we present an image super resolution framework base on enhanced WGAN (SRWGAN-TV). We introduce the total variational (TV) regularization term into the loss function of WGAN. The total variational (TV) regularization term can stabilize the network training and improve the quality of generated images. Experimental results on public datasets show that the proposed method achieves superior performance in both quantitative and qualitative measurements.","PeriodicalId":294200,"journal":{"name":"2021 IEEE 13th International Conference on Computer Research and Development (ICCRD)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133493683","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

A Convolutional Neural Network with Background Exclusion for Crowd Counting in Non-uniform Population Distribution Scenes 基于背景排除的卷积神经网络在非均匀人口分布场景下的人群计数

2021 IEEE 13th International Conference on Computer Research and Development (ICCRD) Pub Date : 2021-01-05 DOI: 10.1109/ICCRD51685.2021.9386369

Xinfeng Zhang, Lisha Zuo, Baoqing Yang, Shuhan Chen, Bin Li

{"title":"A Convolutional Neural Network with Background Exclusion for Crowd Counting in Non-uniform Population Distribution Scenes","authors":"Xinfeng Zhang, Lisha Zuo, Baoqing Yang, Shuhan Chen, Bin Li","doi":"10.1109/ICCRD51685.2021.9386369","DOIUrl":"https://doi.org/10.1109/ICCRD51685.2021.9386369","url":null,"abstract":"The crowd counting in public places is a wildly concerned issue in the fields of public safety, activity planning, and space design. The current crowd counting methods are mainly aimed at the situation that the crowd is full of the whole scene, which cannot be applied to practical applications due to the actual crowd is non-uniform distributed in the scene. The complex background caused by non-uniform population distribution affects the accuracy of crowd counting. Therefore, we propose a convolutional neural network with background exclusion for crowd counting. Firstly, we divide the image into blocks and then use the residual network to determine whether each block contains crowd, to eliminate the clutter background area and avoid the background interference to crowd counting. Secondly, we use the dilated convolution and asymmetric convolution to estimate the crowd density map of image blocks containing crowd. Finally, the crowd density map of all crowd areas is integrated to obtain the crowd counting results of the whole scene. We collect some images of more general scenes, such as the crowd is only a part of the whole image, and construct Non-uniformly Distributed Crowd (NDC 2020) dataset. We conduct experiments on ShanghaiTech datasets and NDC 2020 dataset. Experiment results show that our method is superior to the existing crowd counting methods in the scene of non-uniform population distribution.","PeriodicalId":294200,"journal":{"name":"2021 IEEE 13th International Conference on Computer Research and Development (ICCRD)","volume":"9 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123782000","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

Application of Yolo on Mask Detection Task Yolo在掩码检测任务中的应用

2021 IEEE 13th International Conference on Computer Research and Development (ICCRD) Pub Date : 2021-01-05 DOI: 10.1109/ICCRD51685.2021.9386366

Ren Liu, Ziang Ren

{"title":"Application of Yolo on Mask Detection Task","authors":"Ren Liu, Ziang Ren","doi":"10.1109/ICCRD51685.2021.9386366","DOIUrl":"https://doi.org/10.1109/ICCRD51685.2021.9386366","url":null,"abstract":"2020 has been a year marked by the COVID-19 pandemic. This event has caused disruptions to many aspects of normal life. An important aspect in reducing the impact of the pandemic is to control its spread. Studies have shown that one effective method in reducing the transmission of COVID-19 is to wear masks. Strict mask-wearing policies have been met with not only public sensation but also practical difficulty. We cannot hope to manually check if everyone on a street is wearing a mask properly. Existing technology to help automate mask checking uses deep learning models on real-time surveillance camera footages. The current dominant method to perform real-time mask detection uses Mask-R-CNN with ResNet as backbone. While giving good detection results, this method is computationally intensive and its efficiency in real-time face mask detection is not ideal. Our research proposes a new approach to the mask detection by replacing Mask-R-CNN with a more efficient model \"YOLO\" to increase the processing speed of real-time mask detection and not compromise on accuracy. Besides, given the small volume as well as extreme imbalance of the mask detection datasets, we adopt a latest progress made in few-shot visual classification, simple CNAPs, to improve the classification performance.","PeriodicalId":294200,"journal":{"name":"2021 IEEE 13th International Conference on Computer Research and Development (ICCRD)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133842497","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: 27

Video Quality Assessment by Sparse Representation and Dynamic Atom Classification 基于稀疏表示和动态原子分类的视频质量评估

2021 IEEE 13th International Conference on Computer Research and Development (ICCRD) Pub Date : 2021-01-05 DOI: 10.1109/ICCRD51685.2021.9386597

Zihui Zhang, Zongyao Hu

引用次数: 0

Research on RFID Virtual Tag Location Algorithm Based on Monte Carlo 基于蒙特卡罗的RFID虚拟标签定位算法研究

2021 IEEE 13th International Conference on Computer Research and Development (ICCRD) Pub Date : 2021-01-05 DOI: 10.1109/ICCRD51685.2021.9386426

Tingliang Guan, Ding Wang, Yixin Su

引用次数: 2

A Synchronization Optimization Technique for OpenMP OpenMP的同步优化技术

2021 IEEE 13th International Conference on Computer Research and Development (ICCRD) Pub Date : 2021-01-05 DOI: 10.1109/ICCRD51685.2021.9386475

Zhaochu Deng, Jianjiang Li, Jie Lin

{"title":"A Synchronization Optimization Technique for OpenMP","authors":"Zhaochu Deng, Jianjiang Li, Jie Lin","doi":"10.1109/ICCRD51685.2021.9386475","DOIUrl":"https://doi.org/10.1109/ICCRD51685.2021.9386475","url":null,"abstract":"In recent years, even though the chip density can still increase, it is difficult to increase the main frequency. Performance improvements for single processors may be close to their limits. So multi-core processors are coming on the scene. In order to make full use of multi-core platforms, we must find the inherent parallelism of programs and write programs that can execute in parallel. OpenMP standard is widely used in parallel programming because of its good portability and ease of use. For OpenMP programs generated by parallel compilers and OpenMP programs which only have simple parallelism, they belong to programs with insufficient optimization. In OpenMP parallel execution, synchronization control is one of the main overheads. Its unnecessary barrier synchronization reduces the performance of parallel program. This paper discusses an optimization technology of OpenMP program. Firstly, the parallel area of OpenMP program is merged and expanded to reduce the overhead of parallel and serial switching in execution, and at the same time, it is convenient for next steps to optimize the program. Then explicit the implicit synchronization in OpenMP program. Finally, data dependency analysis is carried out for the context of each synchronization, and unnecessary synchronizations are deleted. The program is tested with the program running time as an index to evaluate the performance of the test program. The experimental results show that the optimization strategy proposed in this paper correctly reconstructs the parallel regions and reduces its execution overhead; it reduces the number of redundant synchronizations and effectively improve the performance of OpenMP program.","PeriodicalId":294200,"journal":{"name":"2021 IEEE 13th International Conference on Computer Research and Development (ICCRD)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128248366","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

Two Stage Operation Optimization of Active Distribution Network Based on IMOHS Algorithm 基于IMOHS算法的有源配电网两阶段运行优化

2021 IEEE 13th International Conference on Computer Research and Development (ICCRD) Pub Date : 2021-01-05 DOI: 10.1109/ICCRD51685.2021.9386491

Xueshun Ye, Kaiyuan He, Tianyuan Kang, Muke Bai

引用次数: 2