Abstract: Conventional semantic communication systems require training task-specific semantic encoders on each user device and corresponding decoders on the server for every client, resulting in ...
I noticed an inaccuracy in the model description between the README and the Technical Report. README: mentions "...unified encoder-decoder architecture..." Technical Report: states "...adopts a ...
Medical image segmentation is a fundamental component of many clinical applications such as computer-aided diagnosis, radiotherapy planning, and preoperative planning. Its accuracy and stability ...
Abstract: Reliable and timely data collection poses a significant challenge for underwater wireless sensor networks (UWSNs), primarily due to the extremely low data rate of underwater communication ...
Most learning-based speech enhancement pipelines depend on paired clean–noisy recordings, which are expensive or impossible to collect at scale in real-world conditions. Unsupervised routes like ...
ABSTRACT: This work presents an innovative Intrusion Detection System (IDS) for Edge-IoT environments, based on an unsupervised architecture combining LSTM networks and Autoencoders. Deployed on ...
First of all, I'd like to commend the authors on the excellent work presented in SSS! I have a quick question regarding the model architecture, specifically related to the frozen image encoder and ...
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