14 Matching Annotations
  1. Dec 2019
    1. In this thesis, I propose three possible strategies, incre-mental relabeling, importance-weighted label prediction and active Bayesian Networks.

      Więcej ciekawych podejść do tematu.

    1. Use your “gold standard” data to measure the performance ofeach contributor so you know when to retrain workers. Whena contributor’s score falls below 70% accuracy, exclude hiswork and retrain.
    2. “Gold Standard” Data: A Best Practice Methodfor Assessing Labels

      instrukcja adnotacji

    1. A box is considered too loose when there is too much distance between the object and the edges of the bounding box, which leads to unnecessary parts of the image background showing through within the box.

      loose bbox

  2. arxiv.org arxiv.org
    1. The left-hand side is rejected due to too loose bounding box

      wielkość bounding boxa

  3. Nov 2019
    1. We construct a graph from the unlabeled data to representthe underlying structure, such that each node represents adata point, and edges represent the inter-relationships be-tween them. Thereafter, considering the flow of beliefs in thisgraph, we choose those samples for labeling which minimizethe joint entropy of the nodes of the graph.

      ciekawe podejście

    1. Traditional Optical Character Recognition (OCR) systems

      orc w faster rcnn