Resultados da pesquisa

Resultados da pesquisa - Todos

Filtros
  1. 9741
    Icone de Cobertura

    Systems coupled to multiple baths via noncommuting coupling operators

    Publicação
    dissertação de mestrado Portugal Acesso Aberto
  2. 9742
  3. 9743
  4. 9744
    Icone de Cobertura

    Clustering of rare events and other limiting properties of chaotic dynamics

    Publicação
    dissertação de mestrado Portugal Acesso Aberto
  5. 9745
  6. 9746
    Icone de Cobertura

    Detecting garment and its landmarks

    Publicação
    Garment folding is a task happening daily at our homes, retail and industry. When put into numbers, over a lifetime people spend on average 375 days performing this chore, while employees at a store may fold the same shirt 119 times per day. Despite the associated repetitive characteristics of this task, its automation is still far from being achieved mainly due to the large number of possible configurations that a crumpled piece of clothing may assume. In general, highly deformable objects still present large challenges for both fields of Robotics and Computer Vision. We attempt to offer a contribution to the garment folding automation by addressing the recognition of clothing pieces without much constraints on their pose or wrinkling, mimicking a most realistic scenario as possible. Such capability would enable a folding robot to choose and adapt its execution plan to the current clothing category. Because the considered problem revolves around clothe recognition, this work may also be of the interest of many other clothe related software applications such as recommendation systems existing on e.g., online e-commerce platforms, or intelligent surveillance setups that require tracking of people by their clothing description. Some work has been produced using Machine Learning techniques that, in general, consist on extracting a set of engineered features from the source image and then applying classification algorithms (e.g., Support Vector Machines) to find the associated clothing category and or pose. With the recent success of Convolutional Neural Networks, where features extraction is incorporated in the learning process, on the object classification problem, these have been preferred in favor of the previous pipelines. We apply Deep Learning techniques on images containing a single piece of clothing in a flat, wrinkled and semi-folded pose, existing on a clean background with the goal of classify and localize each piece. Furthermore, its relevant landmarks (shoulders, legs, crotch, etc) are equally treated. We train and evaluate our solution using the datasets produced by CTU at the CloPeMa project.
    dissertação de mestrado Portugal Acesso Aberto
  7. 9747
  8. 9748
    Icone de Cobertura

    Relação entre a doença periodontal e doenças sistémicas

    Publicação
    dissertação de mestrado Portugal Acesso Aberto
  9. 9749
  10. 9750
  11. 9751
  12. 9752
  13. 9753
    Icone de Cobertura

    Formulation/development of a food product with an agri-food by-product

    Publicação
    dissertação de mestrado Portugal Acesso Aberto
  14. 9754
  15. 9755
  16. 9756
    Icone de Cobertura

    Stencilarte

    Publicação
    dissertação de mestrado Portugal Acesso Aberto
  17. 9757
  18. 9758
  19. 9759
    Icone de Cobertura

    Distância de Visibilidade de Ultrapassagem em Estradas de Duas Vias

    Publicação
    dissertação de mestrado Portugal Acesso Aberto
  20. 9760