yoloYou only look once v3 (YOLOv3)YouTubeYOLOv5YOLOv8YOLOYOLO-RYolov5YOLOXYOLOv7-tinyYou only look once (YOLO)
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Z numberZERNIKEZEISSZero Parallax SettingZoom FatigueZ-type SchlierenZero-Shot ClassificationZebra EmbryoZernike polynomialZERNIKE MOMENTS
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0.8um pixel
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1-bit matrix completion180 degree images108 Megapixel1/f noise100 Hue test1st and 2nd FM generation 3D halftoning133-MEGAPIXEL1 MICRON PIXELS
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2D AND 3D CONVERTIBLE DISPLAY2.5D printing2.5D PRINTING2D/3D imaging, high performance computing, imaging systems, efficient computations and storage2.5 D printing2D printing2D-TO-3D CONVERSION ARTIFACTS2-D barcodes2AFC2D2.5D2D DCT2D VIEWS2.5D reconstruction2D-plus-depth video2D and 3D video2D metrics2-d scale2D to Hologram conversion
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3D Image Processing3D RANGE IMAGING3-D RECONSTRUCTION3D MODELLING3d localization360-deg quality assessment360-DEGREE IMAGE3D shape analysis3D Quality3D Video Conferencing3D Models3D Computer Graphics3D Compression3D object shape3D Video3-T pixel3D recursive search3D-human body detection3D halftoning3D print3D Meshes3D SALIENCY3D SHAPE INDEXING AND RETRIEVAL3D and 2D3D SCENE RECONSTRUCTION AND MODELING3D Scene Reconstruction3D Lidar3D-CNN3D MESH3D Iterative Halftoning360° STEREO PANORAMAS3D reconstruction3DMM3D VISUALIZATION3D Compression and Encryption3D Gaussian splatting3D Display3D MESHES360-degree3D communications360-degree video3D displays3DSR3d3D Range Data Encoding3D-printing3D Reconstruction3D Color Printing360-degree imaging3D encoding3D3D vision3D surface structure based halftoning3D COMPRESSION AND ENCRYPTION3D glasses3D STIMULI3d video3D IMAGE3D visual representation3D-high efficiency video coding3D DISPLAY3d mapping3-D SHAPE RECOVERY360x3D scene capture3A ALGORITHMS360 Video3D TV3D cinema and TV360-Degree Video Technology3D PROFILE3D USER INTERFACES3D range geometry3D Print Appearance3D colour Digital Image Correlation3D digitization and dissemination3D localization and mapping3D imaging3D audio3D ACQUISITION ARCHITECTURE360° VIDEO3D INTERACTION3D printer3D RECOVERY35MM FILM DIGITIZATION3D mesh simplification3D projector3D-Anisotropic smoothing3DCNN3D Scene Reconstruction and Modeling3D human-centered technologies3D point cloud3D-assisted features3D/4D SCANNING3D localization3D RECONSTRUCTION3D rigid transformations3D Immersion3D Vision3D digital halftoning3D/2D Visuals3D modeling360° video3ARRI footage3D Curvelet3D range scanning3D depth sensing3D HALFTONING360 IMAGING3D PRINTER3D shape3D printing360-degree content3D Communications3D Printing3D recovery3D affine transformation3D Point Cloud3D Range Data Compression360 degree images3D modelling3D capture3D scanning3D Mapping3D EDUCATIONAL MATERIAL3D Tracking3D connected tube model3D scene flow estimation360-degree videos3D/4D DATA PROCESSING AND FILTERING3D Shape Indexing and Retrieval3D Video Communications3D camera3D Data Sources3D Halftoning3D adaptive halftoning3D-HEVC3D image compression3D Digital Image Correlation360-degree Image3D TRANSFORMATION3D Imaging3D compression3D model3D STACK3D Modeling3D Range Data3D surface reproduction3D optical scans3D data processing3D surface3D Saliency3D objects3D warping3D video processing3D scene classification360VR3D/4D Data Processing and Filtering3D mapping and localization360-video3D depth-map360-degree video streaming3D MODEL3D face alignment3D PRINTING3D Morphable Model360-degree images3D Object Detection360-degree image projection360 degrees video360-degree art exhibition3D CAMERAS3D perception360 panorama3D stereo vision3D/4D Scanning3D-LUT3D video3D display3D-color perception3D refinement3D shape indexing and retrieval3D mesh3D-shooting3D position measurement of people3D DIGITIZATION METHOD FOR OIL PAINTINGS3D Telepresence3D Data Processing3D theater program listing3D Measurement
Video compression in automated vehicles and advanced driving assistance systems is of utmost importance to deal with the challenge of transmitting and processing the vast amount of video data generated per second by the sensor suite which is needed to support robust situational awareness.
The objective of this paper is to demonstrate that video compression can be optimised based on the perception system that will utilise the data. We have considered the deployment of deep neural networks to implement object (i.e. vehicle) detection based on compressed video camera data extracted
from the KITTI MoSeg dataset. Preliminary results indicate that re-training the neural network with M-JPEG compressed videos can improve the detection performance with compressed and uncompressed transmitted data, improving recalls and precision by up to 4% with respect to re-training with
uncompressed data.