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Anais do XVII Workshop de Visão Computacional (WVC 2021)最新文献

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Measuring the Root Length of Peanuts Grown in Rhizotrons Using Computer Vision 用计算机视觉测量花生根管生长的根长
Anais do XVII Workshop de Visão Computacional (WVC 2021) Pub Date : 2021-11-22 DOI: 10.5753/wvc.2021.18901
Leonardo Michalski Stefanello, Leonardo Paillo da Silva, Luís Henrique Soares Dayrell, J. Ferrari Neto, H. Pistori, Higor Henrique Picoli Nucci
{"title":"Measuring the Root Length of Peanuts Grown in Rhizotrons Using Computer Vision","authors":"Leonardo Michalski Stefanello, Leonardo Paillo da Silva, Luís Henrique Soares Dayrell, J. Ferrari Neto, H. Pistori, Higor Henrique Picoli Nucci","doi":"10.5753/wvc.2021.18901","DOIUrl":"https://doi.org/10.5753/wvc.2021.18901","url":null,"abstract":"Peanut is one of the most grown leguminous crops in the world, but it can suffer during water deficit periods. In this paper, a new method to help monitoring root growth for laboratory experiments with this plant is proposed. By using a new combination of smoothing, thresholding, morphological filtering and skeletonization, our method has achieved a correlation of 0.968 with the Tennant's standard approach.","PeriodicalId":311431,"journal":{"name":"Anais do XVII Workshop de Visão Computacional (WVC 2021)","volume":"135 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129477639","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
A Methodology for Tumor Detection in MRI using a New q-Gabor Function as a Convolutional Filter 一种使用新的q-Gabor函数作为卷积滤波器的MRI肿瘤检测方法
Anais do XVII Workshop de Visão Computacional (WVC 2021) Pub Date : 2021-11-22 DOI: 10.5753/wvc.2021.18908
Vinicius de A. Silva, Lucas P. Laheras, Éverton C. Acchetta, P. S. Rodrigues
{"title":"A Methodology for Tumor Detection in MRI using a New q-Gabor Function as a Convolutional Filter","authors":"Vinicius de A. Silva, Lucas P. Laheras, Éverton C. Acchetta, P. S. Rodrigues","doi":"10.5753/wvc.2021.18908","DOIUrl":"https://doi.org/10.5753/wvc.2021.18908","url":null,"abstract":"Convolutional Neural Networks (CNN) can achieve excellent computer-assisted diagnosis with a good amount of data. However, there is still a growing demand for specific data and information for training Machine Learning models, either for classification or other tasks such as segmentation. Towards this, the Data Augmentation (DA) technique can handle the small medical imaging dataset problem by generating artificial training data. In this context, Generative Adversarial Networks (GANs) can synthesize realistic images to increase the number of images in a dataset. Therefore, to maximize the DA efficiency in a CNNbased tumor classification task, we propose using non-extensive Gabor filters as a convolutional layer kernel initializer. Our proposal has been tested in the BraTS15 dataset and results show that CNN with an additional q-Gabor layer can achieve an average accuracy 3.65% better than CNN with Gabor and 5.03% better than the default model when trained with artificial images (data augmentation).","PeriodicalId":311431,"journal":{"name":"Anais do XVII Workshop de Visão Computacional (WVC 2021)","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122430195","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
Single Image 3D Building Reconstruction Using Rectangles Parallel to an Axis 使用平行于轴的矩形进行单图像3D建筑重建
Anais do XVII Workshop de Visão Computacional (WVC 2021) Pub Date : 2021-11-22 DOI: 10.5753/wvc.2021.18906
Tomás Ferranti, Asla Medeiros e Sá, P. Carvalho
{"title":"Single Image 3D Building Reconstruction Using Rectangles Parallel to an Axis","authors":"Tomás Ferranti, Asla Medeiros e Sá, P. Carvalho","doi":"10.5753/wvc.2021.18906","DOIUrl":"https://doi.org/10.5753/wvc.2021.18906","url":null,"abstract":"Historic photographic collections are valuable documents of urban evolution through time. Many historic buildings documented in such collections may have been demolished or changed over time. Digital modeling such buildings may be challenging due to the reduced amount of information available that may be limited to a few images and/or schematic drawings. This paper presents a method to create a 3D set of rectangles that approximates elements of a scene (such as walls, floors, and roofs) from a single image. Using a pinhole camera model, the extraction of geometry and texture of planes parallel to an axis can be obtained after a camera calibration step that recovers intrinsic parameters of the model. Results show that a good visualization of the scene can be created, using the proposed technique, from a single image.","PeriodicalId":311431,"journal":{"name":"Anais do XVII Workshop de Visão Computacional (WVC 2021)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125597305","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
Automatic counting of cattle with Faster R-CNN on UAV images 在无人机图像上使用更快的R-CNN自动计数牛
Anais do XVII Workshop de Visão Computacional (WVC 2021) Pub Date : 2021-11-22 DOI: 10.5753/wvc.2021.18880
João Vitor de Andrade Porto, Fábio Prestes Cesar Rezende, Gilberto Astolfi, V. Weber, M. Pache, H. Pistori
{"title":"Automatic counting of cattle with Faster R-CNN on UAV images","authors":"João Vitor de Andrade Porto, Fábio Prestes Cesar Rezende, Gilberto Astolfi, V. Weber, M. Pache, H. Pistori","doi":"10.5753/wvc.2021.18880","DOIUrl":"https://doi.org/10.5753/wvc.2021.18880","url":null,"abstract":"It is remarkable the growth of the bovine herd in the last four decades however, the availability of areas for pasture did not follow the same trend and thus caused direct interference in the binomial quality and price of the final product. One of the ways to get around this interference is by the use of technologies to help minimize the handling costs, from the breeding in a controlled environment with the need of trained manpower in the confinement process. Thus, as opposed to the current format done manually and in restricted space, computer vision technology can mitigate the identification and counting of cattle problems using unmanned aerial vehicle (UAV). Attending to the objective outlined in this article demonstrates the use of the Faster R-CNN for counting cattle in feedlots employing aerial images, obtaining an average precision of 89.7% for the set of hyperparameters that differed most positively from the others in this experiment.","PeriodicalId":311431,"journal":{"name":"Anais do XVII Workshop de Visão Computacional (WVC 2021)","volume":"139 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127330363","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
Self-portrait to ID Document face matching: CNN-Based face verification in cross-domain scenario 自画像到证件的人脸匹配:跨域场景下基于cnn的人脸验证
Anais do XVII Workshop de Visão Computacional (WVC 2021) Pub Date : 2021-11-22 DOI: 10.5753/wvc.2021.18885
Filipe Costa, Marcos Vinícius L. Melo, Igor Gadelha, G. Folego, Larissa Gambaro, André Rodrigues
{"title":"Self-portrait to ID Document face matching: CNN-Based face verification in cross-domain scenario","authors":"Filipe Costa, Marcos Vinícius L. Melo, Igor Gadelha, G. Folego, Larissa Gambaro, André Rodrigues","doi":"10.5753/wvc.2021.18885","DOIUrl":"https://doi.org/10.5753/wvc.2021.18885","url":null,"abstract":"Face verification approaches determine whether two given faces are from the same person. Recently, a new demand for face verification application which has become popular in commercial applications is the self-portrait and ID face matching, in which we compare the faces of a selfie shot by a subject and the face in a picture of her identification document. In this work, we proposed a novel approach for face verification in a cross-domain scenario, assuming we have only two images for each subject in the dataset. The method is based on siamese architecture with triplet-loss function. Experiments show the proposed model reaches good effectiveness for cross-domain face verification with low error rates, in comparison to other works of the literature.","PeriodicalId":311431,"journal":{"name":"Anais do XVII Workshop de Visão Computacional (WVC 2021)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126052217","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
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