In the field of radar data processing, track interruption seriously affects target tracking, track fusion, and other tasks. The existing track segment association algorithms have low correlation accuracy in dense dist...
In the field of radar data processing, track interruption seriously affects target tracking, track fusion, and other tasks. The existing track segment association algorithms have low correlation accuracy in dense distributed or long-time interruption situations. To this purpose, a dense multi-target track segment association (DMTTSA) algorithm is proposed. Firstly, two identical networks based on the multi-head probability sparse (ProbSparse) self-attention are used to capture the long-term dependencies of the tracks. Then, the bidirectional quadruplet hard sample loss (BiQuaHard loss) is constructed to make the tracks belonging to the same targets closer and the tracks belonging to the different targets farther. Finally, DMTTSA takes the closest track pairs in the feature space as the associated tracks and divides the unassociated tracks into the birth and dead tracks in chronological order. Some comparative experiments are carried out to show the anti-noise performance of the DMTTSA, as well as the effectiveness of solving the problem of dense multi-target track interruption.
To solve the problem of low performance of network intrusion detection,a deep learning intrusion detection model based on space-time fusion features and attention mechanism—CLT-net is *** this model,space-time fusion...
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ISBN:
(纸本)9781665431293
To solve the problem of low performance of network intrusion detection,a deep learning intrusion detection model based on space-time fusion features and attention mechanism—CLT-net is *** this model,space-time fusion features are obtained by integrating convolutional neural network and long short-time memory network,and attention module is added to calculate the importance of the input features,and softmax function is used for *** a large number of simulation experiments on NSL-KDD data sets,CLT-net has significantly improved the convergence of the training set and the accuracy of the test *** with the traditional CNN model with similar structure and the space-time fusion CLSTM the accuracy of the model increased by 11.8% and 10.9%*** shows that this model has great potential in the application field of network intrusion detection.
A wheel-legged robot is equipped with Stewart parallel mechanism, constituting a reconfigurable robot which can change its wheelbase, robot body height, and achieve omnidirectional steering. The legged character effec...
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ISBN:
(纸本)9798400712647
A wheel-legged robot is equipped with Stewart parallel mechanism, constituting a reconfigurable robot which can change its wheelbase, robot body height, and achieve omnidirectional steering. The legged character effectively improves the terrain adaptability, which concerns our planning concentration. We introduced an optimization-based whole-body trajectory planning algorithm to navigate robot in rugged terrain. The planner combines terrain data and stability, allowing lower-level motion generator and controller to operate more efficiently. The Model Predictive control(MPC)-based method updates the footholds and CoG trajectories, which builds upon the support polygon constraints on optimization. The simulations of methodology working in several structure-obstacle scene demonstrated and compared the availability of approach.
Neural Radiance Fields (NeRF) use multi-view images for 3D scene representation, demonstrating remarkable performance. As one of the primary sources of multi-view images, multi-camera systems encounter challenges such...
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Object detection and pose estimation are difficult tasks in robotics and autonomous driving. Existing object detection and pose estimation methods mostly adopt the same-dimensional data for training. For example, 2D o...
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Central pattern generator (CPG) model can form stable periodic signal through self-excited oscillation without high-level central control. Hopf oscillator is an implementation of CPG model, which has the characteristi...
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Fisheye cameras suffer from image distortion while having a large field of view(LFOV). And this fact leads to poor performance on some fisheye vision tasks. One of the solutions is to optimize the current vision algor...
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An inspection allocation algorithm based on different starting points and endurance capabilities of unmanned aerial vehicles (UAVs) is proposed for the multi-UAVs forest inspection process. Firstly, the area map to be...
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Modern object detectors take advantage of rectangular bounding boxes as a conventional way to represent objects. When it comes to fisheye images, rectangular boxes involve more background noise rather than semantic in...
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Because of their wide detection range and rich functions,autonomous underwater vehicles(AUVs)are widely used for observing the marine environment,for exploring natural resources,for security and defense purposes,and i...
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Because of their wide detection range and rich functions,autonomous underwater vehicles(AUVs)are widely used for observing the marine environment,for exploring natural resources,for security and defense purposes,and in many other fields of *** with a single AUV,a multi-AUV formation can better perform various tasks and adapt to complex underwater *** changes in the mission or environment,a change in the UAV formation may also be *** the last decade,much progress has been made in the transformation of multi-AUV *** this paper,we aim to analyze the core concepts of multi-AUV formation transformation;summarize the effects of the AUV model,underwater environment,and communication between AUVs within formations on formation transformation;and elaborate on basic theories and implementation approaches for multi-AUV formation ***,this overview includes a bibliometric analysis of the related literature from multiple ***,some challenging issues and future research directions for multi-AUV formation transformation are highlighted.
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