Signal Processing
Due to the smaller size, low cost, and easy operational features, small unmanned aerial vehicles (SUAVs) have become more popular for various defense as well as civil applications. They can also give threat to national security if intentionally operated by any hostile actor(s). Since all the SUAV targets have a high degree of resemblances in their micro-Doppler (m-D) space, their accurate detection/classification can be highly guaranteed by the appropriate deep convolutional neural network (DCNN) architecture.
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In the view of national security, radar micro-Doppler (m-D) signatures-based recognition of suspicious human activities becomes significant. In connection to this, early detection and warning of terrorist activities at the country borders, protected/secured/guarded places and civilian violent protests is mandatory.
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Electroretinography is a non-invasive electrophysiological method standardized by the International Society for Clinical Electrophysiology of Vision (ISCEV). Electroretinography has been used for the clinical application and standardization of electrophysiological protocols for diagnosing the retina since 1989. Electroretinography become fundamental ophthalmological research method that may assesses the state of the retina. To transfer clinical practice to patients the establishment of standardized protocols is an important step.
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For the data acquisition we used JINS MEME smart glasses -- a device furnished with three-point EOG and six-axis inertial measurement unit (IMU) with an accelerometer and a gyroscope. The sampling frequency of the acquired signals is 100 Hz. The data are transmitted to a computer via Bluetooth or USB and can be exported to CSV file.
Data were acquired under real road conditions from 30 healthy subjects, including twenty experienced drivers and ten students attending a driving school. 16 males and 14 females with average age = 38 +-17 participated in the study.
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Dataset for Radar^2
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GAN-generated faces look challenging to distinguish from genuine human faces. As a result, because synthetic images are presently being used as profile photos for fake identities on social media, they may have serious social consequences. Iris pattern anomalies might expose GAN-generated facial photos. When photographs are printed and scanned, it becomes more difficult to distinguish between genuine and counterfeit since fraudulent images lose some of their qualities.
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A Chinese character gesture dataset for 8 Chinese characters ( “国”,“图”,“木”,“工”,“口”,“中”,“国”,“人” ) .Datasets were collected in three different environments.
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