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kategorie
2 032
podkategorie
23 060
pojęcia
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pojęcia

Cascade regression

Iterative process where each detector in the cascade refines the predictions of the previous detector, using progressively higher IoU thresholds to improve accuracy.

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R-CNN (Region-based CNN)

Family of object detection architectures based on regions of interest extracted from images, combining region proposals with convolutional neural networks for classification and localization.

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Adaptive IoU thresholds

Set of increasing IoU thresholds (typically 0.5, 0.6, 0.7) used in Cascade R-CNN to train specialized detectors with different levels of detection quality.

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Detector head

Classification and regression module placed after the backbone, responsible for predicting object classes and refining bounding box coordinates for each ROI.

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Multi-stage training

Training strategy where cascade stages are trained sequentially, each stage using outputs from the previous stage as inputs for progressive refinement.

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IoU-aware loss

Specialized loss function directly integrating the IoU metric into optimization, encouraging the model to produce bounding boxes with more precise localizations.

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Progressive IoU thresholds

Increasing sequence of IoU thresholds used in Cascade R-CNN where each successive stage only trains on samples with IoU higher than the previous stage's threshold.

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Contextual reasoning

Model's ability to consider spatial and contextual relationships between objects to improve detection accuracy, particularly important in complex scenes.

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