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Automatic detection of sow estrus using a lightweight real-time detector and thermal images

International Journal of Agricultural and Biological Engineering 2023年第3期16卷 194-207页

作者： Haibo Zheng Hang Zhang Shuang Song Yue Wang Tonghai Liu College of Computer and Information Engineering Tianjin Agricultural UniversityTianjin 300392China

Determination of ovulation time is one of the most important tasks in sow reproduction *** variation in the vulva of the sows can be used as a predictor of ovulation ***,the skin temperatures of sows in existing studies are obtained manually from infrared thermal images,posing an obstacle to the automatic prediction of ovulation *** this study,an improved YOLO-V5s detector based on feature fusion and dilated convolution(FDYOLOV5s)was proposed for the automatic extraction of the vulva temperature of sows based on infrared thermal *** the purpose of reducing the model complexity,the depthwise separable convolution and the modified lightweight ShuffleNet-V2 module were introduced in the ***,the feature fusion network structure of the model was simplified for efficiency,and a mixed dilated convolutional module was designed to obtain global *** experimental results show that FD-YOLOV5s outperformed the other nine methods,with a mean average precision(mAP)of 99.1%,an average frame rate of 156.25 fps,and a model size of only 3.86 MB,indicating that the method effectively simplifies the model while ensuring detection *** a linear regression between manual extraction and the results extracted using this method in randomly selected thermal images,the coefficients of determination for maximum and average vulvar temperatures reached 99.5%and 99.3%,*** continuous vulva temperature of sows was obtained by the target detection algorithm,and the sow estrus detection was performed by the temperature trend and compared with the manually detected estrus *** results showed that the sensitivity,specificity,and error rate of the estrus detection algorithm were 89.3%,94.5%,and 5.8%,*** method achieves real-time and accurate extraction of sow vulva temperature and can be used for the automatic detection of sow estrus,which could be helpful for the automatic prediction of ovulation ti

关键词： automatic estrus detection thermal images real-time detector vulva temperature mixed dilated convolutional

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Unsupervised time Series Anomaly Detection using Moving Memorial Dynamic Filter

Unsupervised Time Series Anomaly Detection using Moving Memo...

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第40届中国控制会议

作者： Jufang Duan Xiangyang Xu Yi Wang School of Automation Beijing Institute of Technology AI Lab Lenovo Research

Anomaly detection on time series data is something of great importance *** the unsupervised machine learning method like K-Means to newly developed artificial neural networks,people try very hard to give a precise detection of where the anomalies *** this paper,a new method,the moving memorial dynamic filter,which combines Fourier seasonality decomposition,distance transformation and anomaly determination is ***,the seasonal component is split off based on Fourier *** the time series data is mapped to a center-to-center distance subsequence using a dynamic circumscribed circle filter,which could use a low dimensional series to represent high dimensional *** last,moving memorial value at risk is introduced and serves as a threshold to determine whether a certain data point should be labeled as an *** method is tested and evaluated using the Numenta Anomaly Benchmark,an open-sourced dataset for time series anomaly *** result shows that our method outperforms the competing algorithms in terms of accuracy on most profiles of the NAB with a shorter latency in time consumption.

关键词： anomaly detection time series data dynamic filter real-time detector

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