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Object-conditioned Bag of Instances for Few-Shot Personalized Instance Recognition
Nowadays, users demand for increased personalization of vision systems to localize and identify personal instances of objects (e. g., my dog rather than dog) from a few-shot dataset only.
FFT-based Selection and Optimization of Statistics for Robust Recognition of Severely Corrupted Images
Improving model robustness in case of corrupted images is among the key challenges to enable robust vision systems on smart devices, such as robotic agents.
NNStreamer: Efficient and Agile Development of On-Device AI Systems
NNStreamer efficiently handles neural networks with complex data stream pipelines on devices, significantly improving the overall performance with minimal efforts.
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