The experimental results in real videos from YouTube show that the proposed approach is very efficient in recognizing the Jordanian license plates and achieved 87% recognition accuracy, whereas the commercial systems have recognition accuracies that are less than 81%. Two well-known commercial software packages are used for comparisons. The dataset is available online and includes many real videos for moving vehicles in Jordan. To my knowledge, there is no dataset for Jordanian license plates, therefore this paper proposes a new dataset called JALPR dataset. To my knowledge, the proposed approach represents the first end-to-end Jordanian ALPR that processes video stream in real-time. last version turbobit Sighthound Video 10.11.5 limetorrents zipshare format mac stable bittorrent Sighthound Video torrentday 10.11.4. isoHunt PRO 2013 faster downloads & latest isoHunt torrents. A set of arrays data structure is used to track the vehicles’ LPs and eliminate incorrect ones. Latest Full Version Software with Crack, serial Keys, license Keys, Serial Number, Keygen, Activator Free Download Full Version PC Software. The proposed approach uses temporal information from different frames to remove false predictions. The sizes of LPs' characters are very small compared with the frame size, therefore the YOLO3 network architecture is modified to a shallow network to detect small objects. The download of Sighthound Video, version 3.0.2, is proceeding. Two-stage Convolutional Neural Networks (CNNs) are used in the proposed approach, the CNNs are based on the YOLO3 framework. Thank you so much for using our software portal. This paper aims to develop an accurate ALPR for Jordanian LPs. Countries have different specifications for License Plates (LPs), therefore developing one Automatic license plate recognition (ALPR) system that works well for all LPs types is a difficult task.
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