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10.1002/cpe.6331 http://scihub22266oqcxt.onion/10.1002/cpe.6331 34230817!8250277!34230817     free     free     free       Concurr+Comput 2021 ; ? (?): e6331 Nephropedia Template TP {{tp|p=34230817|t=2021. Multi-angle head pose classification with masks based on color texture analysis and stack generalization |pdf=|usr=}}{{34230817}} gab.com Text Multi-angle head pose classification with masks based on color texture analysis and stack generalization JO: Concurr Comput http://www.kidney.de/pget.php?&tw=1&pmid=34230817 #FOAvip Head pose classification is an important part of the preprocessing process of face recognition, which can independently solve application problems related to multi-angle. But, due to the impact of the COVID-19 coronavirus pandemic, more and more people wear masks to protect themselves, which covering most areas of the face. This greatly affects the performance of head pose classification. Therefore, this article proposes a method to classify the head pose with wearing a mask. This method focuses on the information that is helpful for head pose classification. First, the H-channel image of the HSV color space is extracted through the conversion of the color space. Then use the line portrait to extract the contour lines of the face, and train the convolutional neural networks to extract features in combination with the grayscale image. Finally, stacked generalization technology is used to fuse the output of the three classifiers to obtain the final classification result. The results on the MAFA dataset show that compared with the current advanced algorithm, the accuracy of our method is 94.14% on the front, 86.58% on the more side, and 90.93% on the side, which has better performance. Twit Text FOAVip Multi-angle head pose classification with masks based on color texture analysis and stack generalization ????Concurr Comput http://www.kidney.de/pget.php?&tw=1&pmid=34230817 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=34230817 #FOAvip English Wikipedia <ref>{{Cite pmid|34230817}}</ref> Multi-angle head pose classification with masks based on color texture analysis and stack generalization #MMPMID34230817 Li S; Dong X; Shi Y; Lu B; Sun L; Li W Concurr Comput 2021[Apr]; ? (?): e6331 PMID34230817show ga Head pose classification is an important part of the preprocessing process of face recognition, which can independently solve application problems related to multi-angle. But, due to the impact of the COVID-19 coronavirus pandemic, more and more people wear masks to protect themselves, which covering most areas of the face. This greatly affects the performance of head pose classification. Therefore, this article proposes a method to classify the head pose with wearing a mask. This method focuses on the information that is helpful for head pose classification. First, the H-channel image of the HSV color space is extracted through the conversion of the color space. Then use the line portrait to extract the contour lines of the face, and train the convolutional neural networks to extract features in combination with the grayscale image. Finally, stacked generalization technology is used to fuse the output of the three classifiers to obtain the final classification result. The results on the MAFA dataset show that compared with the current advanced algorithm, the accuracy of our method is 94.14% on the front, 86.58% on the more side, and 90.93% on the side, which has better performance. ?Multi-angle head pose classification with masks based on color texture(epmc).pdf DeepDyve Pubget Overpricing