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Matches in SemOpenAlex for { <https://semopenalex.org/work/W2056518953> ?p ?o ?g. }

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• W2056518953 abstract "Evaluation of object detection algorithms is a non-trivial task: a detection result is usually evaluated by comparing the bounding box of the detected object with the bounding box of the ground truth object. The commonly used precision and recall measures are computed from the overlap area of these two rectangles. However, these measures have several drawbacks: they don't give intuitive information about the proportion of the correctly detected objects and the number of false alarms, and they cannot be accumulated across multiple images without creating ambiguity in their interpretation. Furthermore, quantitative and qualitative evaluation is often mixed resulting in ambiguous measures. In this paper we propose a new approach which tackles these problems. The performance of a detection algorithm is illustrated intuitively by performance graphs which present object level precision and recall depending on constraints on detection quality. In order to compare different detection algorithms, a representative single performance value is computed from the graphs. The influence of the test database on the detection performance is illustrated by performance/generality graphs. The evaluation method can be applied to different types of object detection algorithms. It has been tested on different text detection algorithms, among which are the participants of the ICDAR 2003 text detection competition." @default.
• W2056518953 created "2016-06-24" @default.
• W2056518953 creator A5031669039 @default.
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• W2056518953 date "2006-04-11" @default.
• W2056518953 modified "2023-10-09" @default.
• W2056518953 title "Object count/area graphs for the evaluation of object detection and segmentation algorithms" @default.
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• W2056518953 doi "https://doi.org/10.1007/s10032-006-0014-0" @default.
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