Litchi,a succulent and perishable fruit,presents a narrow annual harvest window of under two *** advent of smart agriculture has driven the adoption of visually-guided,automated litchi harvesting ***,conventional appr...
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Litchi,a succulent and perishable fruit,presents a narrow annual harvest window of under two *** advent of smart agriculture has driven the adoption of visually-guided,automated litchi harvesting ***,conventional approaches typically rely on laboratory-based,high-performance computing equipment,which presents challenges in terms of size,energy consumption,and practical application within litchi *** address these limitations,we propose a real-time litchi detection methodology for complex environments,utilizing portable,low-energy edge computing ***,the litchi orchard imagery is collected to enhance data ***,a convolutional neural network(CNN)-based single-stage detector,YOLOx,is constructed to accurately pinpoint litchi fruit locations within the *** facilitate deployment on portable,low-energy edge devices,we employed channel pruning and layer pruning algorithms to compress the trained model,reducing its size and ***,the knowledge distillation technique is harnessed to fine-tune the *** findings demonstrated that our proposed method achieved a 97.1%compression rate,yielding a compact litchi detection model of a mere 6.9 MB,while maintaining 94.9%average precision and 97.2%average *** 99 frames per second(FPS),the method exhibited a 1.8-fold increase in speed compared to the unprocessed ***,our approach can be readily integrated into portable,low-computational automatic harvesting equipment,ensuring real-time,precise litchi detection within orchard settings.
Through the 2030 Agenda, countries are committed to reducing pollutant emissions. In this context, the transport sector plays a relevant role and road transport accounts for a very large proportion of Greenhouse gas e...
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The accuracy of the dynamic model of a robot plays an important role for robots performing highly dynamic tasks. Quadruped robots are often performing highly dynamic tasks and in order to be able to do that, fine and ...
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Problem of adaptive state observer synthesis for linear time-varying (LTV) system with unknown time-varying parameter and delayed output measurements is considered. State observation problem has attracted the attentio...
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In urban environments, complex transportation demands, including land, air, and maritime transport, are increasingly growing. While significant advancements have been made in land transportation and autonomous driving...
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This paper addresses the key question that when faults occur either the aircraft system dynamics changes due to the fault or these dynamics are unknown (precisely). This question is addressed for the important case of...
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This paper addresses the key question that when faults occur either the aircraft system dynamics changes due to the fault or these dynamics are unknown (precisely). This question is addressed for the important case of Air Data Sensor failures, due to e.g. icing, for fixed wing aircraft operating in a nominal fight condition. The solution to this question uses basic ideas from subspace Identification to cast this problem in linear least squares problem with convex constraints (nuclear norm and 1-norm constraints). The latter are relaxations of a rank and cardinality constraint. The presented solution is validated using real-life fight test data.
Intelligent vehicles and autonomous driving systems rely on scenario engineering for intelligence and index (I&I), calibration and certification (C&C), and verification and validation (V&V). To extract and...
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Intelligent vehicles and autonomous driving systems rely on scenario engineering for intelligence and index (I&I), calibration and certification (C&C), and verification and validation (V&V). To extract and index scenarios, various vehicle interactions are worthy of much attention, and deserve refined descriptions and labels. However, existing methods cannot cope well with the problem of scenario classification and labeling with vehicle interactions as the core. In this paper, we propose VistaScenario framework to conduct interaction scenario engineering for vehicles with intelligent systems for transport automation. Based on the summarized basic types of vehicle interactions, we slice scenario data stream into a series of segments via spatiotemporal scenario evolution tree. We also propose the scenario metric Graph-DTW based on Graph Computation Tree and Dynamic Time Warping to conduct refined scenario comparison and labeling. The extreme interaction scenarios and corner cases can be efficiently filtered and extracted. Moreover, with naturalistic scenario datasets, testing examples on trajectory prediction model demonstrate the effectiveness and advantages of our framework. VistaScenario can provide solid support for the usage and indexing of scenario data, further promote the development of intelligent vehicles and transport automation. IEEE
This paper analyses the HBEFA-based instantaneous vehicle emissions model implemented in the SUMO microscopic traffic simulation. We identify significant discrepancies between real vehicle emissions measured with port...
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The article is devoted to the analysis of the possibilities of improving the methodology for selecting the operation parameters of the longitudinal differential protection of a power transformer when using new types o...
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We study the problem of policy estimation for the Linear Quadratic Regulator (LQR) in discrete-time linear timeinvariant uncertain dynamical systems. We propose a Moreau Envelope-based surrogate LQR cost, built from a...
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