Artificial Intelligence
Alan's GYA experimental data
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Each dataset is splitted by trainset, devset and testset.
Please read them with pytorch.
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The design and implementation of an anthropomorphic robotic hand control system for the Bioengineering and Neuroimaging Laboratory LNB of the ESPOL were elaborated. The myoelectric signals were obtained using a bioelectric data acquisition board (CYTON BOARD) using six channels out of 8 available, which had an amplitude of 200 [uV] at a sampling frequency of 250 [Hz].
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Brainwave entrainment beats detection has become an important topic due to the ability of these beats to change human brain waves to decrease anxiety, help focus attention, improve memory, improve mood, enhance creativity, reduce pain, help with meditation, enhance mental flexibility, and enhance sleep quality. However, listening to it can cause unwanted side effects as it can increase feelings of depression, anxiety, anger, and confusion in some people.
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We carried out swine lamina milling experiment and collect force signal during milling process, to establish data set for model training. A total of 36 segments of thoracic and lumbar spine, which included 36 vertebral plates, of fresh adult swine purchased from the market were selected. We tested 12 milling conditions with 6 times repeated experiments for each condition. In terms of ultrasonic scalpel, we designed 3 kinds of milling power: 100 $\%$, 80 $\%$, 60 $\%$, while for grinding drill, 3 grinding speeds including 10000r/s, 15000r/s, 20000r/s were chosen.
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ViFoDAC is a collection of Authentic videos and Forged videos. The dataset has a total of 16 Authentic videos and 16 Forged videos. The Authentic videos are camera recorded whereas the Forged videos are edited using Adobe Premiere Pro and Wondershare Filmora software. The dataset can be used to train and optimise video identification models. This dataset can be used for the Research and Development of fake video classification.
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None
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The Active-Passive SimStereo dataset is a simulated dataset created with Blender containing high quality both realistic and abstract looking images. Each image pair is rendered in classic RGB domain, as well as Near-Infrared with an active pattern. It is meant to be used as a dataset to study domain transfert between active and passive stereo vision, as well as providing a high quality active stereo dataset, which are far less common than passive stereo datasets.
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The dataset contains an example of energy consumption, Functioning hours and Production KPI of different stages of the experimental open pit mine, mainly the destoning, the screening, and the train loading station. The Code is an example of the prediction algorithm, and the API can be used to apply the same algorithm used in this article.
In the proposed Dataset the energy consumption data for each station are collected from power meters and stored into a database that contains functioning hours and production.
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