作者:
Sun FengjieWang XianchangZhang RuiJilin University
Key Laboratory of Symbolic Computing and Knowledge Engineering Ministry of Education China Jilin University
Key Laboratory of Symbolic Computing and Knowledge Engineering Ministry of Education Chengdu Kestrel Artificial Intelligence Institute China
Unmanned Aerial Vehicle (UAV) can greatly reduce manpower in agricultural plant protection such as watering, sowing, pesticide spraying. It helps in creating an autonomous manufacturing sys- tem by executing tasks wit...
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ISBN:
(纸本)9781450365130
Unmanned Aerial Vehicle (UAV) can greatly reduce manpower in agricultural plant protection such as watering, sowing, pesticide spraying. It helps in creating an autonomous manufacturing sys- tem by executing tasks with less human intervention in time-efficient manner. Consequently, a scheduler is one essential component to be focused on; yet to the best of our knowledge, there are few re- search on practical UAV scheduling. This work proposes an algorithm to schedule the UAV actions in practice such as pesticide spraying, flying and charging. During the execution of the algorithm, the tasks are put into a queue then each task is assigned to the UAV that can complete it in the shortest amount of time, and then the UAVs perform tasks in the order in which they are as- signed. This proposed method is implemented into a scheduler and tested on datasets generated based on a real flight demonstration. Performance evaluation of the scheduler is discussed in details.
Nowadays, data parallelism has been widely applied to train large datasets on distributed deep learning clusters, but it has suffered from costly global parameter updates at batch barriers. Performance imbalance among...
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This paper proposes a unified model - D9-intersection model to represent topological relations between regions with holes. D9-intersection model can describe simple regional relations as accurately as 9-intersection m...
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An efficient methodology for recognizing features is presented. The part information is taken from the B-rep solid date library then broken down into sub-graph. Once the sub-graphs are generated, they are first checke...
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An efficient methodology for recognizing features is presented. The part information is taken from the B-rep solid date library then broken down into sub-graph. Once the sub-graphs are generated, they are first checked to see whether they match with the predefined feature library. If so, a feature vector is assigned to them. Otherwise, base faces are obtained as heuristic information and used to restore missing faces, meanwhile, update the sub-graphs. The sub-graphs are transformed into vectors, and these vectors are presented to the neural network which classifies them into feature classes.
Unmanned aerial vehicles (UAVs) are widely used in aerial photography nowadays for their strong maneuverability, good image quality and high cost performance, while they have limited battery capacity and difficulty in...
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In this paper, we investigate belief revision in possibilistic logic, which is a weighted logic proposed to deal with incomplete and uncertain information. Existing revision operators in possibilistic logic are restri...
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In this paper, an adaptive image thresholding algorithm is proposed for thresholding images with uneven illumination. Firstly, a Gaussian scale space, which is produced from the convolution of a two-dimensional Gaussi...
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ISBN:
(纸本)9781629932101
In this paper, an adaptive image thresholding algorithm is proposed for thresholding images with uneven illumination. Firstly, a Gaussian scale space, which is produced from the convolution of a two-dimensional Gaussian function with an input image, is used to estimate the background image. Followed by background subtraction, the objective image can be easily obtained to eliminate interference of uneven illumination. Thirdly, to highlight those darker objects, gamma correction is employed to enhance the objective image. Finally, the thresholding result is extracted easily using the global valley-emphasis Otsu method. The experimental results show that the introduced method yields satisfactory visual quality.
This paper addresses distributed computation Sylvester equations of the form AX+XB=C with fractional order *** partitioning parameter matrices A,B and C,we transfer the problem of distributed solving Sylvester equatio...
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This paper addresses distributed computation Sylvester equations of the form AX+XB=C with fractional order *** partitioning parameter matrices A,B and C,we transfer the problem of distributed solving Sylvester equations as two distributed optimization models and design two fractional order continuous-time algorithms,which have more design freedom and have potential to obtain better convergence performance than that of existing first order ***,rewriting distributed algorithms as corresponding frequency distributed models,we design Lyapunov functions and prove that proposed algorithms asymptotically converge to an exact or least squares ***,we validate the effectiveness of proposed algorithms by providing a numerical example.
User-specified trust relations are often very sparse and dynamic, making them difficult to accurately predict from online social media. In addition, trust relations are usually unavailable for most social media *** is...
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User-specified trust relations are often very sparse and dynamic, making them difficult to accurately predict from online social media. In addition, trust relations are usually unavailable for most social media *** issues pose a great challenge for predicting trust relations and further building trust networks. In this study,we investigate whether we can predict trust relations via a sparse learning model, and propose to build a trust network without trust relations using only pervasively available interaction data and homophily effect in an online world. In particular, we analyze the reliability of predicting trust relations by interaction behaviors, and provide a principled way to mathematically incorporate interaction behaviors and homophily effect in a novel framework,b Trust. Results of experiments on real-world datasets from Epinions and Ciao demonstrated the effectiveness of the proposed framework. Further experiments were conducted to understand the importance of interaction behaviors and homophily effect in building trust networks.
Multimodal Relation Extraction (MRE) has achieved great improvements. However, modern MRE models are easily affected by irrelevant objects during multimodal alignment which are called error sensitivity issues. The mai...
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