Artificial Intelligence
This dataset is associated with the paper entitled "DeepWiPHY: Deep Learning-based Receiver Design and Dataset for IEEE 802.11ax Systems", accepted by IEEE Transactions on Wireless Communications. It has synthetic and real-word IEEE 802.11ax OFDM symbols. The synthetic dataset has around 110 million OFDM symbols and the real-world dataset has more than 14 million OFDM symbols. Our comprehensive synthetic dataset has specifically considered typical indoor channel models and RF impairments. The real-world dataset was collected under a wide range of signal-to-noise ratio (SNR) levels and at va
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We test the consumed time of the three steps of the exchange model in order to show that our scheme is feasible.
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The training, validation, and test set used for Deep Xi (https://github.com/anicolson/DeepXi).
Training set:
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This is the noisy-speech test set used in the original Deep Xi paper: https://doi.org/10.1016/j.specom.2019.06.002. The clean speech and noise used to create the noisy-speech set are also available.
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Noisy-speech set used to test Deep Xi (https://github.com/anicolson/DeepXi). The clean speech and noise used to create the noisy-speech set are also available. The clean-speech recordings are from Librispeech test-clean (http://www.openslr.org/12/).
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The data files contains all the thermal images and error data of the spindle in the experiment.
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About
Dataset described in:
Daudt, R.C., Le Saux, B., Boulch, A. and Gousseau, Y., 2019. Multitask learning for large-scale semantic change detection. Computer Vision and Image Understanding, 187, p.102783.
This dataset contains 291 coregistered image pairs of RGB aerial images from IGS's BD ORTHO database. Pixel-level change and land cover annotations are provided, generated by rasterizing Urban Atlas 2006, Urban Atlas 2012, and Urban Atlas Change 2006-2012 maps.
The dataset is split into five parts:
- 2006 images
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Dataset for paper.
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Master data has played a significant role in improving operational efficiencies and has attracted the attention of many large businesses over the decade. Recent professional searches have also proved a significant growth in the practice and research of managing these master data assets.
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