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IEEE/ICACT20230149 Slide.09        [Big Slide]	Oral Presentation
	In this study, we proposed a ResNet-based autoencoder framework for Novelty detection, known signal classification, and Novelty clustering. Here we showed the workflow. After receiving a signal from an SDR, we utilize our YOLO framework for detecting the presence of RF signals. Afterward, we utilize our autoencoder framework. If the signal is known, the framework provides its class label. If unknown, we push it for clustering. After clustering, an expert can provide the class label and the model can relearn the novel signals.

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