Machine Learning
42 stimulus pictures are presented separately on the screen in the same sequences for all participants, including landscapes, people, social scenes and composite pictures. The eye tracker records the participants' gaze data on the stimulus pictures. Based on the gaze fixation position and duration, the fixation map could be visualized. We applies a 2-d convolution with a gauss filter on the fixation maps to get the visual heatmaps. The participants consist of schizophrenic patients and healthy controls.
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9 Views
This dataset provides the high-resolution remote senisng data regarding various coastline scenes.
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295 Views
Recently, a limited number of datasets that exist are used to detect errors in the printing process of the 3D printer. Limited datasets lead most researchers to dive into sensor data fault classification.
The dataset is captured and labelled before being fed to the DL model. The image dataset is captured in a time-lapse video mode with a 15-second duration for each printing process. Next, the time-lapse is used to extract around 50 images per video. In total, 2297 images containing four classes are collected.
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1867 Views
Most machine learning (ML) proposals in the Internet of Things (IoT) space are designed and evaluated on pre-processed datasets, where the data acquisition and cleaning steps are often considered a black box. Therefore, the data acquisition stage requires additional data cleaning/anomaly techniques, which translate to additional resources, energy, and storage.
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1482 Views
Personal assistive devices for rehabilitation will be in increasing demand during the coming decades due to demographic change, i.e., an aging society. Among the elderly population, difficulty in walking is the most common problem. Even though there are commercially available lower limb exoskeleton systems, the coordination between user and device still needs to be improved to achieve versatile personalized gait. To tackle this issue, an advanced EXOskeleton framework for Versatile personalized gaIt generation with a Seamless user-exo interface (called "EXOVIS") is proposed in this study.
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405 Views
This is a data set for Radio Frequency fingerprinting, which is a kind of identification of wireless devices based on their intrinsic physical features. The data set is composed by GSM bursts collected from 12 GSM mobile phones while transmitting. The samples have been collected using a Software Defined Radio with a sample rate at 20 MS/s. The content information has been removed from the bursts to remove the risk of bias due to content. The data set is in MATLAB format.
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979 Views
A reliable and extensive set of public WiFi fingerprinting radio map databases for researchers to implement, evaluate and compare Wi-Fi RSSI indoor localization schemes, the radio map database contains RSSI information from more than 400 APs collected during the conducted experiment on different days with the support of lab mates and volunteers.
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1320 Views
This dataset containg 1900+ images divided into fresh oranges and rotten oranges. In an orange packing factory, a video was recorded, by placing the camera parallel and above the oranges conveyor. The video was captured for 10 minutes with a quality of Ultra High Definition (4K) with 60 frames per second and a High Dynamic Range feature. The video was changed from High Dynamic Range to Standard Dynamic Range by the use of Splice - Video Editor & Maker software. The video is inserted to developed algorithm operating video processing on it and creating the frames.
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84 Views
In this project, an LSTM-based Model Predictive Controller (LSTM-MPC), with 200 neurons of each layer, is designed to have a highly efficient control on the temperature. The resulted dataset is attached, for further considerations.
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647 Views
In emerging vehicular networks, delay-sensitive tasks can be processed in real time by offloading to
the edge computing servers. Unlike the legacy scenarios, in this paper a novel data offloading/delivery
decision making framework is proposed, where users have the option to divide their task into several
portions and partially offload their data to a complex multi-access edge computing (MEC) environment,
consisting of several MEC servers located on road side units (RSUs), base stations (BSs), and unused
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397 Views