2021 International Conference on Information Technology and Biomedical Engineering (ICITBE)最新文献_第4页

Lane Departure Warning Model Based on Slope 基于坡度的车道偏离预警模型

2021 International Conference on Information Technology and Biomedical Engineering (ICITBE) Pub Date : 2021-12-01 DOI: 10.1109/ICITBE54178.2021.00033

Xueting Zheng, Zhengyou Wang, Yanan Zhang, Shanna Zhuang

引用次数: 0

Application of SVD EMD SG Combination Algorithm in TDLAS Rice Seed Respiration Detection SVD - EMD - SG组合算法在TDLAS水稻种子呼吸检测中的应用

2021 International Conference on Information Technology and Biomedical Engineering (ICITBE) Pub Date : 2021-12-01 DOI: 10.1109/ICITBE54178.2021.00065

Jun Yuan, Liangquan Jia, Lu Gao, Hengnian Qi, Xu Huang

{"title":"Application of SVD EMD SG Combination Algorithm in TDLAS Rice Seed Respiration Detection","authors":"Jun Yuan, Liangquan Jia, Lu Gao, Hengnian Qi, Xu Huang","doi":"10.1109/ICITBE54178.2021.00065","DOIUrl":"https://doi.org/10.1109/ICITBE54178.2021.00065","url":null,"abstract":"A SVD, EMD, SG combined algorithm was proposed to denoise the signal of TDLAS rice seed respiration detection, for seed respiration was a nonstationary procedure and sensitive to environmental changes. Firstly, the amplitude signal of the second harmonic was denoised by singular value decomposition (SVD) adaptively. Subsequently, the denoising signal was decomposed by Empirical mode decomposition (EMD). The dispersion entropy (DE) of each IMF and the correlation coefficients between each IMF and the denoising signal were calculated as the common coefficient, which was used to determine the effective component. Finally, Savitzky- Golay (SG) filter was used to smooth the signal, the polynomial order and window size of SG filters were obtained by improving particle swarm optimization (PSO) algorithm. A simulated signal and experiment data acquired from the TDLAS system were processed, the denoising results were compared with those from the traditional algorithms, this method showed better performance with the higher signal-to- noise ratio and correlation coefficient. The SVD, EMD, SG combination algorithm was suitable for TDLAS rice seed respiration detection","PeriodicalId":207276,"journal":{"name":"2021 International Conference on Information Technology and Biomedical Engineering (ICITBE)","volume":"93 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114131166","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

Research on Light Field Correction Based on LinkNet in HER2 Pathological Image 基于LinkNet的HER2病理图像光场校正研究

2021 International Conference on Information Technology and Biomedical Engineering (ICITBE) Pub Date : 2021-12-01 DOI: 10.1109/ICITBE54178.2021.00087

Zhenrong Lin, Lijun Song, Luyang Wang, Weili Wang, Cong Ji

{"title":"Research on Light Field Correction Based on LinkNet in HER2 Pathological Image","authors":"Zhenrong Lin, Lijun Song, Luyang Wang, Weili Wang, Cong Ji","doi":"10.1109/ICITBE54178.2021.00087","DOIUrl":"https://doi.org/10.1109/ICITBE54178.2021.00087","url":null,"abstract":"The assessment of pathological Images plays a crucial role in cancer cure and research. The automatic evaluation method based on artificial intelligence can provide assistance for doctors and effectively improve the efficiency and accuracy of doctors’ diagnosis. However, the current methods based on artificial intelligence have the problem of low quality of collected pathological images, which has a negative impact on the prediction of intelligent algorithms. Due to the influence of the illumination deviation, the brightness distribution of the collected pathological images is uneven, and the noise generated by the uneven illumination will be mixed with the useful signal in the image, and some details are partially blurred or completely obscured. To tackle these problems, this paper proposes a LinkNet-based light field correction method for polarization correction of pathological images. This method takes advantage of Gaussian image characteristics to generate a large number of images with different center points and different brightness diffusion speeds to simulate the light field distribution map, and uses WSI (Whole-slides Image) as a standard unbiased pathological image to train a polarization correction model. Compared with traditional image enhancement methods, the method proposed in this paper is not only the best in terms of visual effect contrast, but also has very desirable effects in image light field correction and detail enhancement. The experimental results show that the method proposed in this article and other evaluation methods we use are the best in optional various index evaluations.","PeriodicalId":207276,"journal":{"name":"2021 International Conference on Information Technology and Biomedical Engineering (ICITBE)","volume":"155 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114413581","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

Pedestrian Attribute Recognition Based On Deep Learning : A Survey 基于深度学习的行人属性识别研究进展

2021 International Conference on Information Technology and Biomedical Engineering (ICITBE) Pub Date : 2021-12-01 DOI: 10.1109/ICITBE54178.2021.00039

X. Chen, Shanna Zhuang, Xueting Zheng, Zhengyou Wang

引用次数: 0

The compact genetic algorithm based method for disease associated study 基于紧凑遗传算法的疾病相关性研究方法

2021 International Conference on Information Technology and Biomedical Engineering (ICITBE) Pub Date : 2021-12-01 DOI: 10.1109/ICITBE54178.2021.00093

Jing Zhao, Bin Wei, Xuan She

引用次数: 0

A guided test case generation algorithm based on the method of collision domain detection 一种基于碰撞域检测方法的导向测试用例生成算法

2021 International Conference on Information Technology and Biomedical Engineering (ICITBE) Pub Date : 2021-12-01 DOI: 10.1109/ICITBE54178.2021.00011

F. Yang, Yongjian Fan, Zheng Fang

引用次数: 0

Learning Channel Attention in Frequency Domain for Visual Tracking 基于频域的信道注意学习视觉跟踪

2021 International Conference on Information Technology and Biomedical Engineering (ICITBE) Pub Date : 2021-12-01 DOI: 10.1109/ICITBE54178.2021.00034

Jun Wang, Pei Zhang, Chenchen Meng, Limin Zhang, Yuanyun Wang

{"title":"Learning Channel Attention in Frequency Domain for Visual Tracking","authors":"Jun Wang, Pei Zhang, Chenchen Meng, Limin Zhang, Yuanyun Wang","doi":"10.1109/ICITBE54178.2021.00034","DOIUrl":"https://doi.org/10.1109/ICITBE54178.2021.00034","url":null,"abstract":"Visual tracking based on attention mechanism, especially channel attention, has achieved great success. However, they do not make full use of the correlation between the feature map channels and use the feature information to model the target appearance. In this paper, under the Siamese network framework, we propose a simple and effective tracking algorithm based on channel attention mechanism in the frequency domain, referred to as SiamFCA. The frequency channel attention preprocesses the feature map obtained through the fully convolutional network (FCN). It divides and weights the feature maps in the frequency domain, and recalibrates the channel feature response by modeling the correlation between the feature channels. The proposed model further enhances the feature information of the extracted target image, reduces the model complexity and computational burden. The results of the experiment on the two benchmark datasets of OTB2015 and VOT2016 show that the proposed tracker based on the frequency channel attention mechanism is better than many state-of-the-art trackers.","PeriodicalId":207276,"journal":{"name":"2021 International Conference on Information Technology and Biomedical Engineering (ICITBE)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131371627","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

Key frame extraction for falling detection 关键帧提取的下落检测

2021 International Conference on Information Technology and Biomedical Engineering (ICITBE) Pub Date : 2021-12-01 DOI: 10.1109/ICITBE54178.2021.00032

Jing Du, Yale Zhao, Shanna Zhuang, Zhengyou Wang

{"title":"Key frame extraction for falling detection","authors":"Jing Du, Yale Zhao, Shanna Zhuang, Zhengyou Wang","doi":"10.1109/ICITBE54178.2021.00032","DOIUrl":"https://doi.org/10.1109/ICITBE54178.2021.00032","url":null,"abstract":"The continuous advancement of computer vision and deep learning technology provides powerful technical support for supervising the occurrence of falling behaviors. Considering that some frames in the video contribute little to the recognition of falling behaviors, in order to eliminate the video frames irrelevant to falling behaviors, this paper proposes an algorithm to extract key frames in a video by combining LUV local maximum and Mask-RCNN. Firstly, candidate key frames are extracted based on the local maximum of LUV. Video frames containing motion changes can be obtained. Afterwards, in order to further eliminate the video frames that are less relevant to the fall action, Mask-RCNN is used for human body detection. According to the aspect ratio of the bounding box and the motion speed of the human body, the video frames that are more relevant to the fall action are selected as key frames. Experiments and results analysis are carried out on the UR fall detection dataset, Multiple cameras fall dataset, Le2i Fall detection dataset and falling video dataset of real scenes. The effectiveness and accuracy of the proposed method are verified.","PeriodicalId":207276,"journal":{"name":"2021 International Conference on Information Technology and Biomedical Engineering (ICITBE)","volume":"15 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120991189","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

Analysis and prediction of COVID-19 based on the SIR-B model 基于SIR-B模型的COVID-19分析与预测

2021 International Conference on Information Technology and Biomedical Engineering (ICITBE) Pub Date : 2021-12-01 DOI: 10.1109/ICITBE54178.2021.00063

Yijun Shen, Xin-wei Guo

引用次数: 0

Copper loaded ureteral stent reduces encrustation 输尿管载铜支架可减少结痂

2021 International Conference on Information Technology and Biomedical Engineering (ICITBE) Pub Date : 2021-12-01 DOI: 10.1109/ICITBE54178.2021.00070

Jianzhong Li, Jing Zhao

引用次数: 0