Infrared images have properties that are unaffected by illumination compared to visible images, object can be clearly recognized at day or night. Therefore, it is a better choice to use infrared images when training d...
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Much of the recent efforts on salient object detection (SOD) have been devoted to producing accurate saliency maps without being aware of their instance labels. To this end, we propose a new pipeline for end-to-end sa...
Human beings perceive the world through the senses of sight,hearing,smell,taste,touch,space,and *** first five senses are prerequisites for people to *** sensing organs upload information to the nervous systems,includ...
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Human beings perceive the world through the senses of sight,hearing,smell,taste,touch,space,and *** first five senses are prerequisites for people to *** sensing organs upload information to the nervous systems,including the brain,for interpreting the surrounding ***,the brain sends commands to muscles reflexively to react to stimuli,including light,gas,chemicals,sound,and ***,as an emerging two-dimensional material,has been intensively adopted in the applications of various sensors and *** this review,we update the sensors to mimic five primary senses and actuators for stimulating muscles,which employ MXene-based film,membrane,and composite with other functional ***,a brief introduction is delivered for the structure,properties,and synthesis methods of ***,we feed the readers the recent reports on the MXene-derived image sensors as artificial retinas,gas sensors,chemical biosensors,acoustic devices,and tactile sensors for electronic ***,the actuators of MXene-based composite are ***,future opportunities are given to MXene research based on the requirements of artificial intelligence and humanoid robot,which may induce prospects in accompanying healthcare and biomedical engineering applications.
Regional geomagnetic maps are widely used in geomagnetic navigation and magnetic anomaly detection. However,the complexity of geomagnetic spatial trend changes and the spatial sparseness of the geomagnetic data affect...
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Regional geomagnetic maps are widely used in geomagnetic navigation and magnetic anomaly detection. However,the complexity of geomagnetic spatial trend changes and the spatial sparseness of the geomagnetic data affect the accuracy of regional geomagnetic map construction. In order to improve the accuracy of regional geomagnetic maps, this paper proposes the Support Vector Machine Residual Kriging method（SVMRKriging）. First, Support Vector Machine（SVM） is used to fit the geomagnetic trend changes, then the residual component is interpolated by ordinary Kriging, and finally these two parts are added to construct a regional geomagnetic map. Experiments were performed using geomagnetic grid data and aeromagnetic data. The experiment results show that SVMRKriging method can improve the accuracy of regional geomagnetic maps with geomagnetic trend changes.
Dear editor,Swarm intelligence optimization algorithms are inspired by the behaviour of biological groups in nature. Such algorithms have the advantages of a clear structure, simple operation, comprehensible principle...
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Dear editor,Swarm intelligence optimization algorithms are inspired by the behaviour of biological groups in nature. Such algorithms have the advantages of a clear structure, simple operation, comprehensible principles, strong parallelism, effective search abilities, and strong robustness. They can effectively solve difficult problems that traditional methods cannot. Pigeon-inspired optimization (PIO), a novel biomimetic swarm intelligence optimization algorithm, was proposed by Duan and Qiao in
Recent object detection models have achieved satisfactory performance by deep learning with large-scale annotated datasets. However, these models often perform poorly when the training examples are not sufficient enou...
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Brain-computer interface (BCI) provides a new way to express our minds without peripheral nerves and muscles. In this work, a process control recognition method based on continuous flickering is proposed to output con...
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In this paper, with considerations of low efficiency of missile path planning (MPP) by traditional aggregation technology, it uses affinity propagation based multi-objective evolutionary algorithm with hypervolume env...
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With the enhancement of the anti-jamming ability of the target, it is difficult to track and strike the target stably and accurately by single guidance. It is necessary to use a variety of detectors as sensors to prov...
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With the enhancement of the anti-jamming ability of the target, it is difficult to track and strike the target stably and accurately by single guidance. It is necessary to use a variety of detectors as sensors to provide a variety of observation data to track the target stably and achieve accurate strike. In this paper, we mainly research the distributed multi-sensor estimation problem. First, the target motion model and observation model are established. Secondly, the central differential Kalman filter(CDKF) transformation is applied to address the non-linear filtering problem without the need for computation of Jacobian matrix. Then, a FCI fusion algorithm for the multi-sensor target tracking problem is proposed. Compared to the traditional covariance intersection fusion method, FCI is more efficient in computation without the need for complex optimization process. Finally, simulations are designed and implemented and the joint CDKF-FCI fusion estimation algorithm is validated.
Simulation test evaluation of the unmanned aerial vehicle (UAV) cluster operational effectiveness requires the support of simulation models with different granularity levels such as precise, medium, and coarse levels....
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Simulation test evaluation of the unmanned aerial vehicle (UAV) cluster operational effectiveness requires the support of simulation models with different granularity levels such as precise, medium, and coarse levels. In order to ensure the confidence of the evaluation, difficulties in evaluating the effectiveness of different granularity simulation models of the UAV cluster need to be solved. Aiming at the problem that the existing evaluation methods are not fully applicable due to the constraints of a large number of actual flight data, this paper proposes the evaluation method of different granularity simulation models, completes the rationality analysis of the granularity partitioning of UAV cluster at three levels: precise, medium and coarse, and the rationality analysis of the support relationship between different granularity models. Based on the special input method, capability meta-models of the UAV cluster with different granularity are evaluated. The evaluation method of different granularity simulation models of the UAV cluster based on sensitivity analysis is proposed. The sensitivity factor extraction and simulation analysis of precise granularity in the motion layer, medium granularity in the perception layer, and coarse granularity in the decision layer are completed. The validity evaluation of the different granularity simulation models has laid a solid foundation for the simulation test evaluation of the UAV cluster operational effectiveness.
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