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Found 5 papers, 4 papers with code
Detecting Out-of-distribution Objects Using Neuron Activation Patterns
Object detection is essential to many perception algorithms used in modern robotics applications.
Detection of out-of-distribution samples using binary neuron activation patterns
Existing approaches to detect OOD samples treat a DNN as a black box and evaluate the confidence score of the output predictions.
Combating noisy labels in object detection datasets
This approach shows promising potential in rectifying state-of-the-art object detection datasets.
Deep Learning based Switching Filter for Impulsive Noise Removal in Color Images
Noise reduction is one the most important and still active research topic in low-level image processing due to its high impact on object detection and scene understanding for computer vision systems.
Organization of machine learning based product development as per ISO 26262 and ISO/PAS 21448
Machine learning (ML) algorithms generate a continuous stream of success stories from various domains and enable many novel applications in safety-critical systems.
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