Surveillance server technology was growth with new technology, effective, extra new features, human friendly, and human deals with big amount data, can't view and collect the data in the short time, and took time ...
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Surveillance server technology was growth with new technology, effective, extra new features, human friendly, and human deals with big amount data, can't view and collect the data in the short time, and took time to analyze, playback video/picture to determine machine, human, vehicle or environment issues or performance, Surveillance Server Systems now which has the ability to face recognition, face detection, human detection, motion detection, license plate recognition, The authors perform this study that still new this research has never been done before to determine the efficacy of the LSTM in predicting human behavior (Long Short Term Memory) Face Detection on Server surveillance system, by taking log view data with a total of 91501 Face detection data downloaded from 10/18/2022~11/9/2022, the data will be processed using Python programming and training so that it can be used to predict the future regarding human activities that vary utilizing time series prediction LSTM include the number of daily activities, the highest and lowest numbers of days, and the maximum and minimum numbers of days. from the results of this study it was found to help to find out the days with the lowest number of humans and the days with the highest number of human activities, so that the owner can predict with sequence of the data the service would be provided when human activity is high in certain area or certain day, it can also can find out the maximum or minimum amount human counting day by day, and compare able some different date and location, the author will continue to do more in-depth research the others data related with prediction with deep learning server surveillance machine system interaction with human, vehicle behavior in the future studies.
We present a deep-learning method based on Wiener filters and U-Nets that performs image reconstruction in systems with spatially-varying aberrations. We train on simulated microscopy measurements and test on experime...
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We present implantable silicon photonic probes for selective plane illumination imaging in vivo. The small form factor of the probes minimizes tissue displacement and heat dissipation while providing planar illuminati...
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DNA double-strand breaks (DSBs) occur frequently in eukaryotic cells, and the homologous recombination pathway (HR) is one of the major pathways required to repair these breaks. However, tumor cells that are able to r...
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We propose a biohybrid sensor based on optical measurements of transmembrane proteins using micro-ring resonators. The scalability and sensitivity of this geometry could enable optical recording of many individual cel...
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This paper is concerned with the problem of cooperative transportation of payloads by teams of unmanned aerial multirotor vehicles equipped with dexterous robotic arms. In order to increase the autonomy of such system...
This paper is concerned with the problem of cooperative transportation of payloads by teams of unmanned aerial multirotor vehicles equipped with dexterous robotic arms. In order to increase the autonomy of such systems, a leader-follower setting is implemented. The leader UAV dictates the motion and all other follower UAVs attempt to maintain their desired relative pose with respect to the leader. A fiducial marker structure is attached to the leader, which allows all followers to continuously visually track the leader. Each robotic arm is equipped with force-torque sensors at its end-effector for improving the UAVs’ flight stability. Specialized controllers are designed for the aerial manipulator systems, in order to ensure a compliant behavior against forces transmitted through the payload. Simulations are provided using the Gazebo environment in order to validate the proposed control methods.
This paper introduces an alternative technique for diagnosing Acute Ischemic Stroke within the IoMT environment. In the proposed approach, the collected data is transmitted to a cloud-based center where the technique ...
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ISBN:
(数字)9798350351408
ISBN:
(纸本)9798350351415
This paper introduces an alternative technique for diagnosing Acute Ischemic Stroke within the IoMT environment. In the proposed approach, the collected data is transmitted to a cloud-based center where the technique utilizes EfficientNet, a deep learning model, designed to extract features from MRI images thereby enhancing the detection of acute ischemic infarctions. The performance of EfficientNet is compared against two other models, CNN and MobileNet, demonstrating its superior efficacy through metrics such as accuracy, precision, recall, and F1-score, which stand at 92.31%, 92.28%, 92.33%, and 92.30%, respectively.
Photovoltaic (PV) generation systems that are partially shaded have a non-linear operating curve that is highly dependent on temperature and irradiance conditions. Shading from surrounding objects like clouds, trees, ...
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Nonnegative matrix factorization (NMF) was a classic model for dimensional reduction. Manhattan NMF is a variant version of NMF that uses a L 1 -norm cost function as the objective function instead of the L 2 -norm ...
Nonnegative matrix factorization (NMF) was a classic model for dimensional reduction. Manhattan NMF is a variant version of NMF that uses a L 1 -norm cost function as the objective function instead of the L 2 -norm cost function. Manhattan NMF can be formulated as a nonconvex nonsmooth optimization problem. An algorithm framework for solving the Manhattan NMF problem based on the alternating direction method of multiplication is presented to us. Compared with the existed algorithm, our proposed algorithm is more effective by experiments on synthetic and real data sets.
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