Machine Learning
BCI-Double-ErrP-Dataset is an EEG dataset recorded while participants used a P300-based BCI speller. This speller uses a P300 post-detection based on Error-related potentials (ErrPs) to detect and correct errors (i.e. when the detected symbol does not match the user’s intention). After the P300 detection, an automatic correction is made when an ErrP is detected (this is called a “Primary ErrP”). The correction proposed by the system is also evaluated, eventually eliciting a “Secondary ErrP” if the correction is wrong.
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Pressing demand of workload along with social media interaction leads to diminished alertness during work hours. Researchers attempted to measure alertness level from various cues like EEG, EOG, Video-based eye movement analysis, etc. Among these, video-based eyelid and iris motion tracking gained much attention in recent years. However, most of these implementations are tested on video data of subjects without spectacles. These videos do not pose a challenge for eye detection and tracking.
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Four fully annotated marine image datasets. The annotations are given as train and test splits that can be used to evaluate machine learning methods.
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Development of Industrial IoT System for Anomaly Detection in Smart Factory
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GPS spoofing and jamming are common attacks against the UAV, however, conducting these experiments for research can be difficult in many areas. This dataset consists of a logs from simulation and live fights. Logs include data from a benign flight as well as one where the UAV experiences an attack.
Simulated Attacks
Note: This is not the most accurate of the data. We recommend using the live GPS Spoofing and Jamming data if possible.
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Along with the increasing use of unmanned aerial vehicles (UAVs), large volumes of aerial videos have been produced. It is unrealistic for humans to screen such big data and understand their contents. Hence methodological research on the automatic understanding of UAV videos is of paramount importance.
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This is a dataset having paired thermal-visual images collected over 1.5 years from different locations in Chitrakoot, India and Prayagraj, India. The images can be broadly classified into greenery, urban, historical buildings and crowd data.
The crowd data was collected from the Maha Kumbh Mela 2019, Prayagraj, which is the largest religious fair in the world and is held every 6 years.
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A Traffic Light Controller PETRI_NET (Finite State Machine) Implementation.
An implementation of FSM approach can be followed in systems whose tasks constitute a well-structured list so all states can be easily enumerated. A Traffic light controller represents a relatively complex control function
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