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Found 4 papers, 2 papers with code
Know Yourself Better: Diverse Discriminative Feature Learning Improves Open Set Recognition
In this paper, we conduct an analysis of open set recognition methods, focusing on the aspect of feature diversity.
OpenIncrement: A Unified Framework for Open Set Recognition and Deep Class-Incremental Learning
In most works on deep incremental learning research, it is assumed that novel samples are pre-identified for neural network retraining.
Automated Antenna Testing Using Encoder-Decoder-based Anomaly Detection
A contour-based anomaly detector can then map the reconstruction error matrix to an anomaly score to identify faulty antenna arrays and increase the classification F-measure (F-M) by up to 46%.
PF-Net: Point Fractal Network for 3D Point Cloud Completion
Unlike existing point cloud completion networks, which generate the overall shape of the point cloud from the incomplete point cloud and always change existing points and encounter noise and geometrical loss, PF-Net preserves the spatial arrangements of the incomplete point cloud and can figure out the detailed geometrical structure of the missing region(s) in the prediction.
