检索结果-内蒙古大学图书馆

35th sibgrapi conference on graphics, patterns and images (sibgrapi)

作者： Pereira, Danilo C. Longo, Leonardo C. Tosta, thaina A. A. Martins, Alessandro S. Silva, Adriano B. de Faria, Paulo R. Neves, Leandro A. do Nascimento, Marcelo Z. Univ Fed Uberlandia Fac Comp Sci Uberlandia MG Brazil Sao Paulo State Univ UNESP Dept Comp Sci & Stat DCCE Sao Paulo Brazil Fed Univ Sao Paulo UNIFESP Sci & Technol Inst Sao Paulo Brazil Fed Inst Triangulo Mineiro IFTM Uberaba MG Brazil Fed Univ Uberlandia UFU Inst Biomed Sci Dept Histol & Morphol Uberlandia MG Brazil

ISBN: (数字)9781665453851

ISBN: (纸本)9781665453851

Histological image analysis through systems to aid diagnosis plays an important role in medicine with supplementary reading for the specialist's diagnosis. this work proposes a method based on the association of extracted features by fractal techniques, regularization and polynomial classifier. the feature vectors were classified by applying the cross-validation technique with 10 folds. the evaluation of the results occurred through metrics such as accuracy (ACC) and imbalance accuracy metric (IAM). the proposed approach achieved significant results for all metrics with non-Hodgkin lymphoma lesion sets. the proposed approach provided values around 0.97 of IAM and 99% of ACC for investigated groups. these results are considered relevant to studies in the literature and the association of Hermite polynomial and regularization can contribute to the detection of the lesions by supporting specialists in clinical practices.

关键词： CAD Histological Image Polynomial Classifier Regularization

来源：评论

学校读者我要写书评

暂无评论

STN PLAD: A Dataset for Multi-Size Power Line Assets Detection in High-Resolution UAV images 34

STN PLAD: A Dataset for Multi-Size Power Line Assets Detecti...

引用

34th sibgrapi conference on graphics, patterns and images (sibgrapi)

作者： Buarque Vieira-e-Silva, Andre Luiz Felix, Heitor de Castro Chaves, thiago de Menezes Magalhaes Simoes, Francisco Paulo Teichrieb, Veronica dos Santos, Michel Mozinho Santiago, Hemir da Cunha Cordeiro Sgotti, Virginia Adelia Teixeira Lott Neto, Henrique Baptista Duffles Univ Fed Pernambuco Ctr Informat Voxar Labs Recife PE Brazil Univ Fed Rural Pernambuco Dept Comp Recife PE Brazil In Forma Software Recife PE Brazil Sistema Transmissao Nordeste STN Recife PE Brazil

ISBN: (纸本)9781665423540

Many power line companies are using UAVs to perform their inspection processes instead of putting their workers at risk by making them climb high voltage power line towers, for instance. A crucial task for the inspection is to detect and classify assets in the power transmission lines. However, public data related to power line assets are scarce, preventing a faster evolution of this area. this work proposes the STN Power Line Assets Dataset, containing high-resolution and real-world images of multiple high-voltage power line components. It has 2,409 annotated objects divided into five classes: transmission tower, insulator, spacer, tower plate, and Stockbridge damper, which vary in size (resolution), orientation, illumination, angulation, and background. this work also presents an evaluation with popular deep object detection methods and MS-PAD, a new pipeline for detecting power line assets in hi-res UAV images. the latter outperforms the other methods achieving 89.2% mAP, showing considerable room for improvement.

关键词： Power transmission lines Image resolution Poles and towers Pipelines Lighting Object detection Inspection

来源：评论

学校读者我要写书评

暂无评论

Analysis of Frequency Range Effect on the Detection of Voice Disorder using Convolutional Neural Networks Trained on Spectogram images 37

Analysis of Frequency Range Effect on the Detection of Voice...

引用

37th sibgrapi conference on graphics, patterns and images (sibgrapi)

作者： Souza Paulino, Jose Alberto Gomes, Herman Martins Batista, Leonardo Vidal Lopes, Leonardo Wanderley Fed Univ Campina Grande UFCG Dept Comp Sci Campina Grande Paraiba Brazil Fed Univ Paraiba UFPB Dept Comp Joao Pessoa Paraiba Brazil Fed Univ Paraiba UFPB Integrated Voice Studies Lab Joao Pessoa Paraiba Brazil

ISBN: (纸本)9798350376043;9798350376036

Considering the current advancements in signal processing and machine learning (ML), non-invasive techniques for assessing vocal quality have become increasingly popular, especially with the use of spectrograms in acoustic analysis, which typically do not evaluate patterns in regions above 5kHz, either through visual inspection or using ML algorithms. this study aims to assess the relevance of different frequency ranges in classifying healthy and disordered voices using convolutional neural networks (CNN), as well as to investigate whether the combination of frequency ranges can improve classification results. To achieve this goal, spectrogram subsets were generated from 16 frequency ranges in two datasets, obtained through a bank of band-pass filters, and trained in CNN models with transfer learning. the study was conducted by first evaluating the relevance of each frequency range individually. then, the results of the 65,536 possible combinations obtained with the 16 frequency ranges were assessed. this analysis revealed that it is possible to characterize voice pathology patterns in frequency regions above 5kHz, but the interval between 1 to 1,462 Hz is substantially better in terms of descriptive capacity in spectrograms. Additionally, it was observed that high-frequency regions, when combined with other frequency ranges, produce better classification results, improving the test accuracy from 80.53% to 82.10% in the SVD dataset and from 78.11% to 82.12% in the AVFAD dataset.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Segmentation of Pigmented Melanocytic Skin Lesions Based on Learned Dictionaries and Normalized Graph Cuts 27

Segmentation of Pigmented Melanocytic Skin Lesions Based on ...

引用

27th sibgrapi conference on graphics, patterns and images (sibgrapi)

作者： Flores, Eliezer S. Scharcanski, Jacob Univ Fed Rio Grande do Sul Inst Informat Porto Alegre RS Brazil

ISBN: (纸本)9781479942602

Pigmented melanocytic skin lesion pre-screening relies on the proper segmentation of the image regions affected by the skin lesion. this paper proposes a new pigmented melanocytic skin lesion segmentation algorithm for standard camera images. It is assumed that only one skin lesion is in each input image, and also is assumed that the skin lesion is placed at (or close to) the image center. thus, the input is, at first, shading attenuated, and then converted to a three-channel color space that enhances the discrimination between healthy and unhealthy skin regions. Afterwards, a dictionary is generated for each image, which is compact and reconstructive, and represents the image patches. this dictionary is obtained in an unsupervised manner using a modified version of the Information-theoretic Dictionary Learning (ITDL) method, which was originally proposed as supervised dictionary learning method. Normalized Graph Cuts is used to partition the set of projected patches in two groups, resulting in a binary mask that labels the pixels as corresponding to healthy or unhealthy image regions. Our preliminary experimental results obtained on a publicly available dataset are encouraging, and suggest that the proposed pigmented melanocytic skin lesion segmentation method provides, in average, a lower segmentation error rate than comparable state-of-the-art methods proposed in the literature.

关键词： Melanomacytic skin lesions standard camera images segmentation dictionary learning normalized graph cuts

来源：评论

学校读者我要写书评

暂无评论

Non-Linear co-registration in UAVs' images using deep learning 35

Non-Linear co-registration in UAVs' images using deep learni...

引用

35th sibgrapi conference on graphics, patterns and images (sibgrapi)

作者： Furtado Pinto Silva, Leandro Henrique Dias Junior, Jocival Dantas Mari, Joao Fernando Escarpinati, Mauricio Cunha Backes, Andre Ricardo Univ Fed Uberlandia Sch Comp Sci Ave Joa Naves Avila 121 BR-38408100 Uberlandia MG Brazil Univ Fed Vicosa Campus Rio Paranaiba Vicosa MG Brazil

ISBN: (数字)9781665453851

ISBN: (纸本)9781665453851

Unmanned Aerial Vehicles (UAVs) has stood out for assisting, enhancing, and optimizing agricultural production. images captured by UAVs allow a detailed view of the analyzed region since the flight occurs at low and medium altitudes (50m to 400m). In addition, there is a wide variety of sensors (RGB cameras, heat capture sensors, multi and hyperspectral cameras, among others), each with its own characteristics and capable of producing different information. In multi-spectral images acquisition, we use a distinct sensor to capture each image band and at different time, leading to misalignments. To tackle this problem we propose to train a deep neural network to predict the vector deformation fields to perform the registration between bands of a multi-spectral image. the proposed approach has an accuracy ranging from 89.90% to 93.79% in the task of estimating the displacement field between bands. With this field estimated by the network, it is possible to register between the bands without the need for manual marking of points.

关键词： Training Deep learning Visualization Vegetation mapping Manuals Sensor phenomena and characterization Cameras

来源：评论

学校读者我要写书评

暂无评论

Automatic Segmentation of Specular Reflections for Endoscopic images Based on Sparse and Low-Rank Decomposition 27

Automatic Segmentation of Specular Reflections for Endoscopi...

引用

27th sibgrapi conference on graphics, patterns and images (sibgrapi)

作者： Queiroz, Fabiane Ren, Tsang Ing Fed Univ Pernambuco UFPE Ctr Informt Recife PE Brazil

ISBN: (纸本)9781479942602

Endoscopy is a minimally invasive medical diagnostic procedure that is used to provide a realistic view of the surfaces of organs inside human body. images taken during such procedures largely show tissues of human organs. Due to the presence of mucosa of the gastrointestinal tract or other characteristics of the human body, these surfaces usually have a glossy appearance showing specular reflections. For many image analysis algorithms, these distinct and bright visual mark can be a significant source of error. On other hand, these features can also be useful for image restoration and for the construction of 3D model of the organs. In this article, we propose a segmentation method of the specular regions based on sparse and low-rank decomposition using a robust PCA via accelerated proximal gradient algorithm. In contrast to the existing approaches, the proposed segmentation works without using colour image thresholds. Moreover, the proposed method presents more precise segmentation results represented by grayscale masks instead of binary masks.

关键词： Matrix Decomposition robust PCA specular reflections segmentation medical imaging image pocessing

来源：评论

学校读者我要写书评

暂无评论

Humans are easily fooled by digital images

引用

COMPUTERS & graphics-UK 2017年第Nov.期68卷 142-151页

作者： Schetinger, Victor Oliveira, Manuel M. da Silva, Roberto Carvalho, Tiago J. Univ Fed Rio Grande do Sul Inst Informat Porto Alegre RS Brazil Univ Fed Rio Grande do Sul Inst Fis Porto Alegre RS Brazil IFSP Inst Fed Educ Ciencia & Tecnol Sao Paulo Campinas SP Brazil

Digital images are everywhere, from social media to news and scientific papers. this paper describes an extensive user study to evaluate the ability of an average individual to spot edited images. By design, our study avoids lucky guesses. After observing an image, subjects were asked if it is authentic or not. Whenever a subject indicated that an image has been altered, (s)he had to provide evidence to support the answer by pointing at the suspected region in the image. We collected 17,208 individual answers from 393 volunteers, using 177 images selected from public forensic databases. Our results indicate that the average individual is not good at distinguishing original from edited images, answering correctly on 58% of all images, and only identifying the modified ones 46.5% of the time. this performance is superior to random guessing, but poor compared to results achieved by computational techniques. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Digital image forensics Behavior forensics

来源：评论

学校读者我要写书评

暂无评论

A Deep Learning Approach for Classification of Reaching Targets from EEG images 30

A Deep Learning Approach for Classification of Reaching Targ...

引用

30th sibgrapi conference on graphics, patterns and images Tutorials (sibgrapi-T)

作者： Carvalho, Schubert R. Filho, Iraquitan C. Resende, Damares O. Siravenha, Ana C. de Souza, Cleidson R. B. Debarba, Henrique Gomes, Bruno D. Boulic, Ronan ITV Lab Comp Aplicada Belem Para Brazil Univ Fed Para UFPA Inst Ciencias Biol Belem Para Brazil Artanim Fdn Geneva Switzerland Ecole Polytech Fed Lausanne Immers Interact Grp Lausanne Switzerland

ISBN: (纸本)9781538622193

In this paper, we propose a new approach for the classification of reaching targets before movement onset, during visually-guided reaching in 3D space. Our approach combines the discriminant power of two-dimensional Electroencephalography (EEG) signals (i.e., EEG images) built from short epochs, with the feature extraction and classification capabilities of deep learning (DL) techniques, such as the Convolutional Neural Networks (CNN). In this work, reaching motions are performed into four directions: left, right, up and down. To allow more natural reaching movements, we explore the use of Virtual Reality (VR) to build an experimental setup that allows the subject to perform self-paced reaching in 3D space while standing. Our results reported an increase both in classification performance and early detection in the majority of our experiments. To our knowledge this is the first time that EEG images and CNN are combined for the classification of reaching targets before movement onset.

关键词： Brain-Computer Interface Deep Learning EEG Imagens

来源：评论

学校读者我要写书评

暂无评论

Real-time object tracking in high-definition video using frame segmentation and background integral images

Real-time object tracking in high-definition video using fra...

引用

2013 26th conference on graphics, patterns and images, sibgrapi 2013

作者： Moreira, Gustavo Feijo, Bruno Lopes, Helio Feitosa, Raul Queiroz Departamento de Informatica Pontificia Universidade Catolica Do Rio de Janeiro Rio de Janeiro RJ Brazil Departamento de Engenharia Eletrica Pontificia Universidade Catolica Do Rio de Janeiro Rio de Janeiro RJ Brazil

ISBN: (纸本)9780769550992

Object tracking in video sequences is still a challenging issue in real-time video processing. In this paper we propose an integrated detection and tracking method suitable for high-definition videos at real-time frame rates. In this method we implement a frame segmentation procedure using integral images of the background, which permits to discard the analysis of several image parts of each frame and achieve high frame rates. Also we extend the proposed algorithm to detect multiple objects in parallel. © 2013 IEEE.

关键词： Tracking (position)

来源：评论

学校读者我要写书评

暂无评论

Ensemble of Semantic Segmentation Models for Oral Epithelial Dysplasia images 37

Ensemble of Semantic Segmentation Models for Oral Epithelial...

引用

37th sibgrapi conference on graphics, patterns and images (sibgrapi)

作者： Silva, Adriano B. Tosta, thalna A. A. Neves, Leandro A. Martins, Alessandro S. de Faria, Paulo R. do Nascimento, Marcelo Z. Univ Fed Uberlandia Fac Comp Sci Uberlandia MG Brazil Univ Fed Sao Paulo Sci & Technol Inst Sao Paulo Brazil Sao Paulo State Univ Dept Comp Sci & Stat DCCE Sao Paulo Brazil Fed Inst Triangulo Mineiro Uberaba Brazil Univ Fed Uberlandia Inst Biomed Sci Dept Histol & Morphol Uberlandia MG Brazil

ISBN: (纸本)9798350376043;9798350376036

Early detection of potentially malignant disorders such as oral epithelial dysplasia (OED) is important for preventing oral cancer. Semantic segmentation of nuclei in histopathological images provides relevant insights for pathologists. CNN-based methods have shown promise in improving histological lesion detection and segmentation processes, but achieving results with significant values in terms accuracy metrics remains a challenging task. this paper presents an ensemble approach to enhance the performance of semantic segmentation for nuclei in OED histopathology images. Six CNN models were employed, and their outputs were associated using three ensemble strategies: simple averaging, weighted averaging, and majority voting. To further enhance model robustness, a data augmentation stage was assessed. the proposed ensemble, combined with an image augmentation strategy, achieved accuracy and Dice coefficient values of 93.41% and 0.88, respectively, on OED images. Analysis of the OED grades showed values ranging from 91.14% to 95.24% and 0.87 to 0.90 for accuracy and Dice coefficient, respectively. these values show an improvement over the CNN segmentation models. the analysis of segmentation performance with the OED grade images is another significant contribution of this study that addresses a gap in the literature. A validation stage on three publicly available datasets demonstrated that our approach is on par with state-of-the-art methods.

关键词： Semantic Segmentation

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：