Image 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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The dataset of satellite images we use comes from Satellite Tool Kit (STK), which is the world's top satellite simulation software produced by AGI Company of the United States. We mainly use STK to provide a high-precision visual simulation module, which can provide users with high-fidelity visual support in space. We collected 18 video sequences as our training set and 6 video sequences as our verification set. A video sequence contains a satellite, and each video sequence contains 40 to 60 satellite images.
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Video is a sequence of pictures, which are taken by camera at a short interval of time. A picture in video is called as frame, and the number of frames per second is defined as the frame rate, which denotes the temporal resolution of video. With the higher frame rate, the video contains the more details, such as to the improvement of visual quality for human interpretation or the fine representation for automatic machine perception. A high frame rate relies on the hardware configuration of camera, the higher the frame rate, the more expensive hardware devices.
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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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Drone based wildfire detection and modeling methods enable high-precision, real-time fire monitoring that is not provided by traditional remote fire monitoring systems, such as satellite imaging. Precise, real-time information enables rapid, effective wildfire intervention and management strategies. Drone systems’ ease of deployment, omnidirectional maneuverability, and robust sensing capabilities make them effective tools for early wildfire detection and evaluation, particularly so in environments that are inconvenient for humans and/or terrestrial vehicles.
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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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We propose a real world data set comprising light field images of 19 objects captured with the Lytro Illum camera in outdoor scenes and their corresponding 3D point clouds, as ground truth, captured with the 3dMD scanner. This data set allows more precise 3D pointcloud level comparison of algorithms for the task of depth estimation or 3D point cloud reconstruction from light field images.
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