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.
The city has normal natural state, and the man has a usual movement, change and search for the new .Also, the city has a usual change and transform in its time, place and quality (sizes)structures. The city has a solid memory diving into the past and the future and reflects The real present, and this memory has a timing layers change into real materialistic place making the city has accumulated overlapping circles which is hard to break u , and it broadcasts the lockup timing density ,in which there is no visual record precisely, it is just like((the social record)) that evaluates the un visual relationships between the components and parts of the city (community and form) in a visual quiet exhibition and transform change inside.
... Show MoreThe purpose of the study is the city of Baghdad, the capital of Iraq, was chosen to study the spectral reflection of the land cover and to determine the changes taking place in the areas of the main features of the city using the temporal resolution of multispectral bands of the satellite Landsat 5 and 8 for MSS and OLI sensors respectively belonging to NASA and for the period 1999-2021, and calculating the increase and decrease in the basic features of Baghdad. The main conclusions of the study were, This study from 1999 to 2021 and in two different seasons: the Spring of the growing season and Summer the dry season. When using the supervised classification method to determine the differences, the results showed remarkable changes. Where h
... Show MoreMammals are under threat worldwide due to deforestation, hunting, and other human activities. In Iraq, a total of 93 species of wild mammals have been recorded including species with global conservation concern. Bamo Mountain is situated within the Zagros Mountains in northern Iraq which is a suitable habitat for wild mammals. Due to scarcity of the field survey efforts and cryptic behavior, monitoring of the wild mammals fauna in Zagros Mountain seems challenging. Therefore, we used a camera trap which seems to be an ideal way to determine species diversity of wild mammals in Bamo Mountain. Moreover, interviews with local villagers were performed. The mammalian diversity of Bamo Mountain is not fully explored but seemed threatened by lo
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At different stages of the evolution of the modern Iraqi state ears last century did not receive the industrial sectors importance in great domestic production (GDP) and that the limited resources available in the initial stage and the dominance of public sector industry in the late stage , so the continued decline in the contribution of the private industrial sector in GDP , and this is why imbalance in the labor market and reduced demand for manpower in this sector despite the high rates of labor supply and the various skills and levels of investments, their human and the different geographical distribution , and direction of labor to other economic sectors most requested of the l
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Abstract: Two different shapes of offset optical fiber was studied based on coreless fiber for refractive index (RI)/concentration (con.) measurement, and compare them. These shapes are U and S-shapes, both shapes structures were formed by one segment of coreless fiber (CF) was joined between two single mode (SMF) lead in /lead out with the same displacement (12.268µm) at both sides, the results shows the high sensitive was achieved in a novel S-shape equal 98.768nm/RIU, to our knowledge, no one has ever mentioned or experienced it, it’s the best shape rather than the U-shape which equal 85.628nm/RIU. In this research, it was proved that the offset form has a significant effect on the sensitivity of the sensor. Addi
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The Islamic architectural heritage constitutes a civilized fortune that has to be preserved and protected and work should be done to maintain its development to be more convenient for the circumstances of the age and the civilization transformations. Due to the fact that architecture represents the civilization pot and cultural identity, its originality has to be preserved and work has to be done to prevent the strange architectural invasion that changes its character and make it lose the identity and the character and detached from its roots and environment.
Decoration, in the interior design, as a concept is connected to ornamentation process of interior spaces, which is a process of adding certain items
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During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve
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