NAN-SPOT detects unknown objects better than retraining-heavy methods by using Negative-Aware Norm from off-the-shelf detectors and introduces the expanded COCO-Open dataset.
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N-BEATS outperformed other models including LSTM and TFT in forecasting time to stability on sparse KATRIN tritium monitoring data.
Synthetic flight data generated by TVAE and Gaussian Copula models supports flight delay prediction models with accuracy comparable to real data.
citing papers explorer
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Beyond Known Objects: A Novel Framework for Open-Set Object Detection using Negative-Aware Norm
NAN-SPOT detects unknown objects better than retraining-heavy methods by using Negative-Aware Norm from off-the-shelf detectors and introduces the expanded COCO-Open dataset.
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Forecasting Source Stability in Scientific Experiments using Temporal Learning Models: A Case Study from Tritium Monitoring
N-BEATS outperformed other models including LSTM and TFT in forecasting time to stability on sparse KATRIN tritium monitoring data.
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Synthetic Flight Data Generation Using Generative Models
Synthetic flight data generated by TVAE and Gaussian Copula models supports flight delay prediction models with accuracy comparable to real data.