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Found 5 papers, 0 papers with code
$\textit{A Contrario}$ Paradigm for YOLO-based Infrared Small Target Detection
Traditional object detection methods such as YOLO struggle to detect tiny objects compared to segmentation neural networks, resulting in weaker performance when detecting small targets.
Evaluating Crowd Density Estimators via Their Uncertainty Bounds
In this work, we use the Belief Function Theory which extends the probabilistic framework in order to provide uncertainty bounds to different categories of crowd density estimators.
Geometry-Based Multiple Camera Head Detection in Dense Crowds
This paper addresses the problem of head detection in crowded environments.
Efficient Evaluation of the Number of False Alarm Criterion
In this work, we introduce a strategy which relies on the use of a cumulative space of reduced dimensionality, derived from the coupling of a classic (Hough) cumulative space with an integral histogram trick.
2CoBel : An Efficient Belief Function Extension for Two-dimensional Continuous Spaces
This paper introduces an innovative approach for handling 2D compound hypotheses within the Belief Function Theory framework.
