Signal Processing
Abstract
PassengerEEG is a brain-signal dataset designed to study how human passengers perceive and cognitively respond to potential traffic hazards in highly automated vehicles (AVs). As AVs increasingly replace human drivers, understanding passenger cognition becomes essential for improving vehicle safety and adaptive decision-making.
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In order to accelerate the CU partitioning in VVC-SCC, we have established a specialized dataset for screen content. Firstly, we collect a wide variety of screen content videos and images in YUV format. Secondly, we encode these sequences under four different Quantization Parameters (QPs) to obtain comprehensive information about CU partitioning in VVC-SCC. This includes the length, width, position, mode labels, and RDcost values corresponding to each mode. This dataset will provide valuable data support for optimizing the CU partitioning process in screen content coding.
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This data set is a test result of a split antenna with a center frequency of 400MHz on a campus road. The test object is the road asphalt layer, and the data formats are. Pdd and. Pdh. Before using, please convert the format according to your requirements. It is worth noting that the author 's consent should be obtained before using the data.
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The LibriSpeech corpus, a publicly available English speech dataset derived from audiobook recordings. The corpus contains approximately 1,000 hours of 16 kHz read speech from over 2,400 speakers, encompassing diverse speaking styles, rates, and regional accents. For the purpose of contrastive learning, a subset of 100 speakers was sampled, with 20 utterances per speaker ranging from 3 to 10 seconds. The dataset provides clean, labeled speech suitable for tasks involving speaker representation, acoustic modeling, and multi-style synthesis.
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The sampling rate of laser Doppler vibration measurement data is 250MHZ, and the number of sampling points is 20M.A total of 12 frequency bands of 0.5kHZ, 1kHZ, 2kHZ, 3kHZ, 4kHZ, 5kHZ, 6kHZ, 7kHZ, 8kHZ, 9kHZ, 10kHZ, 11kHZ were collected, which ensured that there were at least 5 vibration samples in each frequency band, and 20 samples were collected in some frequency bands.
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This radar signal dataset comprises 10,000 simulated signals, providing a comprehensive resource for radar signal processing research and experiments. The dataset is designed to facilitate the study of various radar phenomena, including signal deinterleaving and modulation recognition analysis. The number of overlapping signals is uniformly distributed between 1 and 5, ensuring a wide range of complexity for testing algorithms under different interference conditions. Each signal file contains detailed pulse information, which supports robust analysis of radar performance. Researchers can le
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Attached Image data set from combined OCT-SLO is used to train AI models and identify features to maximize quality of data set to adjust MZI reference arm, PMT Voltage of Liquid Lens and location of object. Why adjustment is needed is explained below:
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Data associated with the article: "PM2.5 Retrieval with Sentinel-5P Data over Europe Exploiting Deep Learning"
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This dataset includes a database of 15 feature parameters such as image texture features, pixel statistical features, and geometric features extracted from scans of fixed and living cell samples of two types of cells, HeLa and SiHa, using an adaptive harmonic atomic force microscopy probe and a commercial atomic force microscope. The total number of data contained in the database is 2400.
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The data are the original data of UAV sound source localization by ODAS system consisting of 12-channel spherical microphone array and circular MEMS microphone array of dual system. The data contains four different types of UAV sound sources, and the UAV sound sources in different frequency bands are used to locate the sound sources of multiple UAVs.
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393 Views