Sensors
A 5.76-second piano rendition of the Inspector Gadget Theme with a sampling rate of 44.1 kHz, played 2 mm from the multi-mode fiber. High-speed infrared camera data, derived from sound sampled at 1.93 kHz, consists of 10,000 frames capturing vibrations on a multi-mode fiber. It includes 128*8 pixel data and can be monitored, played, and processed through MATLAB.
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Real-time monitoring of heat flux changes in hot-end components in harsh environments is of great significance for safe operation and thermal protection design. Although many high-performance heat flux sensors have been developed on planar by technologies such as MEMS, their inherent planar properties make it difficult to satisfy the characteristics of curved surfaces on real objects.
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The dataset is the image data obtained after data conversion of the phases of six Chinese sign languages collected using RFID, the dataset includes the data of five people in environment 1, and also includes the data of user 1 in the previous environment, the dataset is converted into 1000×1000 pixel images to be saved in it, which is a total of 3,000 images.
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The dataset consists of measurements of different stages of degradation in low-voltage contactors used for industrial purposes. The measurements were obtained with fiber Bragg grating (FBG) sensors that detect the dynamic deformation generated in switching under different load conditions and internal components. The posted dataset was preprocessed and separated into two different events. The signal is segmented and reduced from the original measurement (separated into opening and closing). Furthermore, two sets of measurements were obtained.
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Our dataset has a total of 8 actions, 7 people(P1-P7), and 3 experimental environments(Room-A,Room-B,Room-C). There are a total of 3 directions in each environment, with 5 samples of each action taken for each person in each direction, so the number of samples is 360(samples/person)*7 = 2520.
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This data set contains two kinds of road perception information: image and acoustics. It covers four kinds of pavement: asphalt pavement, water pavement, gravel pavement and snow pavement. The image and audio files of the whole data set are too large, and this data set is part of it for researchers' reference. Please contact wangzhangu1@163.com if you need the whole data.
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SWAN is a large-scale outdoor point cloud semantic segmentation, instance segmentation and object detection dataset. The dataset is targeted explicitly at the challenging urban environment, which aligns well with the needs of the intelligent transportation systems. The data is collected in the Central Business District (CBD) of Perth city in Australia, covering nearly 150km. It additionally used specialized equipment (portable trolley) to capture scenes of no-through roads and narrow streets.
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SWAN is a Large-Scale Outdoor Point Cloud semantic segmentation dataset . The dataset is targeted explicitly at the challenging urban environment, which aligns well with the needs of the intelligent transportation systems. The data is collected in the Central Business District (CBD) of Perth city in Australia, covering nearly 150km. It additionally used specialized equipment (portable trolley) to capture scenes of no-through roads and narrow streets.
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