It is difficult to perform real time object detection in Uncrewed Aerial Vehicle(UAV) based video surveillance because of the dynamic movement of camera, scale, occlusion, variation of illumination and limited power availability on-board of the computer. Purpose: In this paper of researches, the author suggests the proposed UAV Spatial-Temporal Network(UAV-STNet), which is a hybrid model of spatio-temporal deep learning model that is expected to improve the accuracy of the detection, balance of time, and real-time performance. Approaches: techniques: The proposed framework incorporates U-Net representing the system of total encoder involving extraction of multiscale space features mode, Transformer attention module which will involve global contextual modeling and Long Short-Term Memory(LSTM) network which will involve learning the short-term dependency in sequential frames. The model has been lives with and examined against a personalised UAV video dataset using a trade mark assortment of generally utilised measures of detection, including precision, recollection, mAPat 0.5 and inference velocity (FPS). Findings: UAV-STNet gave 94.5% precision, 93.1% recall and 93.2% mAP @0.5 and also 45 FPS. Better accuracy-tolerance efficient state is observed in comparative comparison with SSD, YOLOv3 and faster R-CNN which are evidently small object in motion affected scenes. Conclusions: The spatial, contextual and temporal modelling applied as a single-stop end-to-end architecture shows a powerful and computationally efficient solution of the topic of detecting real-time UAV video items, that brings benefits in the stability and reliability of intelligent surveillance systems using aerial vehicles.
Theoretical trends have appeared Which posed the concept of biological structures in contemporary architecture concept, Spread through the emergence of architectural production that reflect and indicate the nature of the construction structures based on the ideas and principles of biological structures in biological science: Despite the emergence of many architectural proposals that tried to explain the concept in the field of architecture, but it is not dealt with in depth and not given a comprehensive definition: So there was need to search for the concept and its beginning in the biological field as a general framework down to the field of architecture for the purpose of reducing the limits of their search framework T
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The development of microcontroller is used in monitoring and data acquisition recently. This development has born various architectures for spreading and interfacing the microcontroller in network environment. Some of existing architecture suffers from redundant in resources, extra processing, high cost and delay in response. This paper presents flexible concise architecture for building distributed microcontroller networked system. The system consists of only one server, works through the internet, and a set of microcontrollers distributed in different sites. Each microcontroller is connected through the Ethernet to the internet. In this system the client requesting data from certain side is accomplished through just one server that is in
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Deep learning techniques are applied in many different industries for a variety of purposes. Deep learning-based item detection from aerial or terrestrial photographs has become a significant research area in recent years. The goal of object detection in computer vision is to anticipate the presence of one or more objects, along with their classes and bounding boxes. The YOLO (You Only Look Once) modern object detector can detect things in real-time with accuracy and speed. A neural network from the YOLO family of computer vision models makes one-time predictions about the locations of bounding rectangles and classification probabilities for an image. In layman's terms, it is a technique for instantly identifying and recognizing
... Show MoreDeep learning techniques are used across a wide range of fields for several applications. In recent years, deep learning-based object detection from aerial or terrestrial photos has gained popularity as a study topic. The goal of object detection in computer vision is to anticipate the presence of one or more objects, along with their classes and bounding boxes. The YOLO (You Only Look Once) modern object detector can detect things in real-time with accuracy and speed. A neural network from the YOLO family of computer vision models makes one-time predictions about the locations of bounding rectangles andclassification probabilities for an image. In layman's terms, it is a technique for instantly identifying and rec
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Illegal distribution of digital data is a common danger in the film industry, especially with the rapid spread of the Internet, where it is now possible to easily distribute pirated copies of digital video on a global scale. The Watermarking system inserts invisible signs to the video content without changing the content itself. The aim of this paper is to build an invisible video watermarking system with high imperceptibility. Firstly, the watermark is confused by using the Arnold transform and then dividing into equal, non-overlapping blocks. Each block is then embedded in a specific frame using the Discrete Wavelet Transform (DWT), where the HL band is used for this purpose. Regarding the method of selecting the host frames, the
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The poet (Ahmed Safi Najafi), who came to the poet was a fabric alone, and gathered all the writers and critics who wrote in his poetry as a phenomenon worthy of research, study and meditation as he turned to poetic topics, some strange did not pay attention to poets who preceded him and went to poetic horizons not worn by other poets Those who lived in his time, he refused to gain poetry and attacked hypocrisy and his poets and critics, and rejected the festivals of poetry (festivals on the sidewalk is held) and called for renewal and renunciation of tradition, and ushered in a new world predominant humanism, and gave money to his companions, and played for women and the world, and married Alaqqam and pain, and sincerest For his hair, T
... Show MoreIn this paper, membrane-based computing image segmentation, both region-based and edge-based, is proposed for medical images that involve two types of neighborhood relations between pixels. These neighborhood relations—namely, 4-adjacency and 8-adjacency of a membrane computing approach—construct a family of tissue-like P systems for segmenting actual 2D medical images in a constant number of steps; the two types of adjacency were compared using different hardware platforms. The process involves the generation of membrane-based segmentation rules for 2D medical images. The rules are written in the P-Lingua format and appended to the input image for visualization. The findings show that the neighborhood relations between pixels o
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