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Begriffe
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Begriffe

Prediction heatmap

Two-dimensional heatmap generated by the network indicating the probabilities of object corner presence at each spatial position in the image.

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Corner pooling

Specialized pooling operation that explicitly encodes corner information by aggregating horizontal and vertical edge features toward a central point.

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Embedding vector

Feature vector associated with each predicted corner, used to match the top-left corner with its corresponding bottom-right corner of the same object instance.

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Offset prediction

Additional regression that predicts sub-pixel offsets between quantized corner positions and their actual locations to improve accuracy.

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Peak detection

Process of extracting candidate corner locations from heatmaps by identifying local maxima above a confidence threshold.

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Corner grouping

Mechanism that associates pairs of corners belonging to the same object using the similarity of their embedding vectors and detection scores.

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Feature pyramid pooling

Technique that combines features from different resolutions to improve multi-scale object detection in the CornerNet architecture.

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Corner refinement

Post-processing step that finely adjusts the locations of detected corners using local contextual information to improve accuracy.

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Top-left corner heatmap

Specific heatmap dedicated to detecting the top-left corners of objects, generated in parallel to that of bottom-right corners.

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Bottom-right corner heatmap

Specialized heatmap for predicting the bottom-right corners of objects, working in conjunction with the top-left corner heatmap.

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Corner confidence score

Probability value associated with each predicted corner, indicating the model's confidence in the actual presence of a corner at that position.

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