Quantum dot–based time-bin QKD achieves stable, long-distance secure communication with practical performance.
Modality-agnostic decoders leverage modality-invariant representations in human subjects' brain activity to predict stimuli irrespective of their modality (image, text, mental imagery).
Abstract: Change detection plays a vital role in numerous real-world domains, aiming to accurately identify regions that have changed between two temporally distinct images. Capturing the complex ...
Abstract: Automatic modulation classification (AMC) is one of the fundamental technologies in adaptive communication systems, supporting various tasks such as spectrum surveillance and cognitive radio ...
The implementation is intentionally explicit and educational, avoiding high-level abstractions where possible. . ├── config.py # Central configuration file defining model hyperparameters, training ...
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 ...
NVIDIA introduces Riva TTS models enhancing multilingual speech synthesis and voice cloning, with applications in AI agents, digital humans, and more, featuring advanced architecture and preference ...
I want to train pretrain a sentence transformer using TSDAE. We have previously used all-MiniLM-L6-v2 as a checkpoint where we finetuned with MultipleNegativeRankingLoss with the main downstream task ...
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