Almeida, R.; Jr. , Z. K. G. P. & Guimarães, S. J. F. :2018:
Exploring Feature Distribution to Create Mid-level Representations: A Case Study in Human Action Recognition
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The search expression was <conferencen sibgrapi 31>.
131 references found. Search local date and time: 11/07/2025 07:15. |
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AlmeidaJrGuim:2018:CaStHu Almeida, R.; Jr. , Z. K. G. P. & Guimarães, S. J. F. :2018: Exploring Feature Distribution to Create Mid-level Representations: A Case Study in Human Action Recognition
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AlvesFerrLima:2018:MéHíFu Alves, E. P.; Ferreira, F. A. B. S. & Lima, M. J. C. :2018: Um método híbrido fuzzy-swarm-clustering para segmentação de MRI
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AndradeFariCapp:2018:RiDeLe Andrade, N.; Faria, F. A. & Cappabianco, F. A. M. :2018: A Practical Review on Medical Image Registration: from Rigid to Deep Learning based Approaches
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AndrezzaPrBoSiBaGo:2018:NoFiQu Andrezza, I. L. P., et al. :2018: A Novel Fingerprint Quality Assessment Based on Gabor Filters
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AriasFeli:2018:ViDeQu Arias, R. L. B. & Felinto, A. S. :2018: Video Denoising Quality Assessment for Different Noise Distributions
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AvasFern:2018:PhTrAp Avas, I. & Fernández, E. :2018: A Photon Tracing Approach to Solve Inverse Rendering Problems
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BaffaLatt:2018:CoNeNe Baffa, M. F. O. & Lattari, L. G. :2018: Convolutional Neural Networks for Static and Dynamic Breast Infrared Imaging Classification
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BatistaBellSilv:2018:ReM´Re Batista, J. C.; Bellon, O. R. P. & Silva, L. :2018: Regress˜ao m´ultipla com redes neurais convolucionais para estimativa conjunta da intensidade de Action Units
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BeltrãoNazaSchw:2018:AuGyWo Beltrão, D. F. A.; Nazare, A. C. & Schwartz, W. R. :2018: Automatic Gym Workout Recognition using Wearable Devices
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BenatoTeleFalc:2018:SeLeIn Benato, B. C.; Telea, A. C. & Falcão, A. X. :2018: Semi-Supervised Learning with Interactive Label Propagation guided by Feature Space Projections
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BentoSouzFray:2018:AuApEv Bento, M.; Souza, R. & Frayne, R. :2018: Multicenter Imaging Studies: Automated Approach to Evaluating Data Variability and the Role of Outliers
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Bergamasco:2018:3DMeOb Bergamasco, L. C. C. :2018: 3D medical objects retrieval approach using SPHARMs descriptor and network flow as similarity measure
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BezerraGome:2018:ReOcLa Bezerra, G. A. & Gomes, R. B. :2018: Recognition of occluded and lateral faces using MTCNN, Dlib and homographies
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BoehsVierPere:2018:DeExBo Boehs, G. E.; Viera, M. L. H. & Pereira, C. G. :2018: Decoupling Expressiveness and Body-Mechanics in Human Motion
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BorgesGonz:2018:LoTeDe Borges, T. T. N. & Gonzaga, A. :2018: Local Texture Descriptors for Color Texture Classification Under Varying Illumination
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BorgesViei:2018:DoSaDi Borges, L. R. & Vieira, M. A. C. :2018: Dose Savings in Digital Breast Tomosynthesis through Image Processing
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CabreraAvilaOrtiGonç:2018:ToMeCo Cabrera Avila, E. V.; Ortiz Fernández, L. E. & Gonçalves Garcia, L. M. :2018: Towards a metric for computing similarity ofrestricted non-rigid objects in real time
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CabreraOrtiGonç:2018:ToMeCo Cabrera, E. V.; Ortiz, L. E. & Gonçalves, L. M. :2018: Towards a metric for computing similarity ofrestricted non-rigid objects in real time
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Cardenas:2018:MuHuAc Cardenas, E. J. E. :2018: Multimodal Human Action Recognition Based on a Fusion of Dynamic Images using CNN descriptors
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CavallariRibePont:2018:DoCrFe Cavallari, G. B.; Ribeiro, L. S. F. & Ponti, M. A. :2018: Unsupervised representation learning using convolutional and stacked auto-encoders: a domain and cross-domain feature space analysis
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CordeiroPedr:2018:ArCoRi Cordeiro, N. H. & Pedrino, E. C. :2018: An Architecture for Collision Risk Prediction for Visually Impaired People
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Costa:2018:FeAuDe Costa, D. F. :2018: ADVIR: Ferramenta para Auxilio de Deficientes
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CunhaMLTQSSP:2018:LaRePa Cunha, K. B., et al. :2018: Patch PlaNet: Landmark Recognition with Patch Classification Using Convolutional Neural Networks
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DallaquaFariFaze:2018:AcLeAp Dallaqua, F. B. J. R.; Faria, F. A. & Fazenda, A. L. :2018: Active Learning Approaches for Deforested Area Classification
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DiasMing:2018:EXHiPo Dias, F. F. & Minghim, R. :2018: xHiPP: eXtended Hierarchical Point Placement Strategy
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DinizMenoSchw:2018:ReInGP Diniz, M. A.; Menotti, D. & Schwartz, W. R. :2018: Face Detection at 15,000 FPS: Real-Time Inference on GPU and CPU
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DuartePenaAlme:2018:BaAtVi Duarte, L. A.; Penatti, O. A. B. & Almeida, J. :2018: Bag of attributes for video event retrieval
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FaccinVernierCombTele:2018:StGrIn Faccin Vernier, E.; Comba, J. & Telea, A. C. :2018: A Stable Greedy Insertion Treemap Algorithm for Software Evolution Visualization
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FerrazBorCavGonSai:2018:EvCoNe Ferraz, C. T., et al. :2018: Evaluation of convolutional neural networks for raw food texture classification under variations of lighting conditions
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FigueiredoCele:2018:DiFiGe de Figueiredo, A. H. & Celes, W. :2018: Directionality fields in the generation and evaluation of quadrilateral meshes
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FigueiredoIvsoCele:2018:HiSuRe Figueiredo, L. C.; Ivson, P. & Celes Filho, W. :2018: Hidden Surface Removal for Accurate Painting-Area Calculation on CAD Models
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FreitasFari:2018:UsTeMe Freitas, P. G. & Farias, M. C. Q. :2018: Using Texture Measures for Visual Quality Assessment
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FreitasMira:2018:NeShDe Freitas, A. M. & Miranda, P. A. V. :2018: New Shape Descriptors based on Tensor Scale with Global Features
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GaioJúniorSant:2018:MeOpCl Gaio Júnior, A. & Santos, E. M. :2018: A method for opinion classification in video combining facial expressions and gestures
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GalvãoFalcChow:2018:ReItSp Galvão, F. L.; Falcão, A. X. & Chowdhury, A. S. :2018: RISF: Recursive Iterative Spanning Forest for superpixel segmentation
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Gobber:2018:ÚlLeBa Gobber, C. F. :2018: Últimos levelings com base em funções de energia aplicados a detecção de objetos
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GobberAlve:2018:ÚlLeBa Gobber, C. F. & Alves, W. A. L. :2018: Últimos levelings com base em funções de energia aplicados a detecção de objetos
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GomesReseSchi:2018:DeExPr Gomes, A. L. N.; Resende, F. R. & Schiavoni, F. L. :2018: Desenvolvimento de extensões de processamento e síntese de imagens para a ferramenta Mosaicode
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Jung:2018:ReGeDe zeni, & Jung, C. R. :2018: Real-Time Gender Detection in the Wild Using Deep Neural Networks
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OrtizCabrGonç:2018:MéGeEs Ortiz, L. E.; Cabrera, E. V. & Gonçalves, L. M. G. :2018: Método Genérico para Estimação e Modelagem do Erro RMS em Dados de Profundidade de Sensores para Visão 3D
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RibeiroLope:2018:InPrVe Ribeiro, P. C. & Lopes, H. :2018: Inverse Projection of Vector Fields
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RibeiroPapa:2018:UnDiAc Ribeiro, L. C. F. & Papa, J. P. :2018: Unsupervised Dialogue Act Classification with Optimum-Path Forest
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RodriguesConc:2018:MaMoMa Rodrigues, E. O. & Conci, A. :2018: Mathematical Morphology in Machine Learning
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SantosMasc:2018:StDiPa Santos, C. A. N. & Mascarenhas, N. D. D. :2018: Stochastic distances for patch-based ultrasound image despeckling
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SantosPont:2018:RoFeSp Santos, F. P. & Ponti, M. A. :2018: Robust feature spaces from pre-trained deep network layers for skin lesion classification
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SantosRodr:2018:NePaRe Santos, R. M. & Rodrigues, P. S. :2018: New Pattern Recognition of Brain Mapping Based on Non-Extensive Statistical Systems
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