Artificial Intelligence
This dataset has been meticulously curated to evaluate the efficiency of Retrieval-Augmented Generation (RAG) pipelines in both retrieval and generative accuracy, with a particular focus on scenarios involving overlapping contexts. The dataset comprises two primary components: Motor data and Employee data. The Motor dataset includes master data of various motor models along with their corresponding manuals, linked by the motor's model name. Similarly, the Employee dataset encompasses employee master data and associated policy documents, linked by department.
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345 Views
This dataset is designed for the reconstruction of images of underground potato tubers using received signal strength (RSS) measurements collected by a ZigBee wireless sensor network. It includes RSS data from sensing areas of various sizes, environments with different layouts, and soils with varying moisture levels. The measurements were obtained from 9 potato tubers of differing sizes and shapes, which were buried in two distinct positions within the sensing area.
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189 Views
We construct the triple-modality dataset, VGG-sound+, comprising image-text-audio data. Based on VGG-sound, VGG-sound+ consists of 200,000 audio-visual data entries categorized as video data, including metadata label- ing the category of each video clip. We define the image-text-audio triplet modalities of VGG-sound+ as the dataset Di = (Ii , Ti , Ai), where Ii represents an image snap- shot of the video, Ti denotes a textual description of the video, and Ai signifies the audio clip.
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676 Views
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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41 Views
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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88 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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96 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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38 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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86 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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359 Views
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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460 Views