Artificial Intelligence
In this paper, two datasets for text classification were primarily used in the experiments: AG News and IMDB. The AG News dataset is a widely used four-class news dataset, including four categories: World News, Sports News, Business News, and Technology News. The dataset contains a total of 120,000 samples, with 114,000 samples in the training set and the remaining 6,000 samples in the test set. The IMDB dataset is a movie review dataset used for sentiment analysis, primarily for binary classification tasks, i.e., positive and negative reviews.
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This graph illustrates the visualization trend of a subset of the dataset I have uploaded, which comprises 6500*9 data points. The dataset consists of nine columns representing underwater speed (UWS), underwater course (UWC), depth below the surface (DBS), rate of change in speed (RCS), rate of change in course (RCC), rate of change in depth (RCD), trend A and B of vibrational signals (TVS_A, TVS_B) and electromagnetic noise trend (TEN) recorded by the AUV.
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Acquiring imagery of extraterrestrial planetary surfaces has consistently posed a significant challenge. Moreover, the availability of publicly accessible, annotated lunar datasets remains exceedingly sparse. To address this gap in the field, we have developed the Real Chang'e Lunar Landscape Dataset. The images in this dataset were captured by the landing cameras of the Chang'e-3, Chang'e-4, and Chang'e-5 lunar mission probes, as well as the panoramic and terrain cameras carried by the Yutu-1 and Yutu-2 lunar rovers used during the missions.
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Acquiring imagery of extraterrestrial planetary surfaces has consistently posed a significant challenge. Moreover, the availability of publicly accessible, annotated lunar datasets remains exceedingly sparse. To address this gap in the field, we have developed the Real Chang'e Lunar Landscape Dataset. The images in this dataset were captured by the landing cameras of the Chang'e-3, Chang'e-4, and Chang'e-5 lunar mission probes, as well as the panoramic and terrain cameras carried by the Yutu-1 and Yutu-2 lunar rovers used during the missions.
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56 Views
Acquiring imagery of extraterrestrial planetary surfaces has consistently posed a significant challenge. Moreover, the availability of publicly accessible, annotated lunar datasets remains exceedingly sparse. To address this gap in the field, we have developed the Real Chang'e Lunar Landscape Dataset. The images in this dataset were captured by the landing cameras of the Chang'e-3, Chang'e-4, and Chang'e-5 lunar mission probes, as well as the panoramic and terrain cameras carried by the Yutu-1 and Yutu-2 lunar rovers used during the missions.
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167 Views
This is an optical flow dataset which covers multiple independent moving object samples under various adverse weather. This is an optical flow dataset which covers multiple independent moving object samples under various adverse weather. This is an optical flow dataset which covers multiple independent moving object samples under various adverse weather.
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In order to improve the efficiency and quality of salt-and-pepper denoising and realize the strategy of ‘denoising after judging’, the noise image classification network (CNN-J) is needed to judge whether the input image is a noisy image. For noisy images, the noise marking network (CNN-M) and noise denoising network (CNN-D) are combined for denoising processing, and the clean image will be directly output. In order to train the above three networks, three datasets are provided here, which are dataset_J, dataset_M and dataset_D, respectively.
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479 Views
In this paper, a modified zeroing neurodynamics (MZND) model with immunity to periodic noises is proposed from a control perspective to address time-varying nonlinear equations (TVNE), a common issue in engineering applications. Grounded in the Lyapunov stability theory, this paper provides a thorough assessment of the performance of the MZND model. Through comparative analyses and simulations, the superior performance of the MZND model is validated against existing neurodynamics models.
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eterogeneous graph representation learning is crit-
ical for analyzing complex data structures. Metapaths within this
field are vital as they elucidate high-order relationships across the
graph, significantly enhancing the model’s accuracy and depth of
understanding. However, metapaths tend to prioritize long-range
dependencies of the target node, which can lead to the oversight of
potentially crucial 1st-order heterogeneous neighbors or short-
range dependencies. To address this challenge and circumvent
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RLED contains 80,400 images and corresponding events, we utilized a photometer to continuously measure scene illumination and calculate the illumination value after attenuation at the event camera. The capture scenes included city (35.0%), suburbs (10.3%), town (14.5%), village (17.8%), and valley (22.4%). Half of the RLED frames are captured at a frame rate of 25 fps, and the other half at 10 fps. The exposure time is set to 1ms, 3ms, and 5ms based on the varying environmental illumination.
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171 Views