Electric vehicles represent a significant advancement for the automobile industry, promoting a more sustainable future with their eco-friendly approach and reduced fuel dependence. The battery is the primary source of...
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Automated Guided Vehicles (AGVs) and other autonomous conveyance vehicles play a pivotal role in enhancing efficiency and precision in packaging areas. Traditional manual methods are inefficient and prone to errors an...
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Hypergraph neural networks have demonstrated outstanding performance in various fields. However, there is still a relative lack of research on the security aspects of hypergraph neural networks, particularly in terms ...
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For the problems of slow speed, low efficiency, and labor intensity of manual measurement of crankshaft structure size of air compressor, a machine vision-based method for measuring crankshaft size of air compressor w...
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作者：
Marinov, P.Technical University of Sofia
Faculty of Computer Systems and Technologies Department of Computer Systems 8 Kliment Ohridski blvd. Sofia1000 Bulgaria
In this work recognition of human actions of daily life is studied. Such actions take place in an environment involving various objects. The performance depends on hyper-parameters. High-level 3D primitives are consid...
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Parkinson's disease (PD) is progressively emerging as a substantial global health concern, impacting multiple nations and experiencing a rise in prevalence. The diagnosis primarily depends on the analysis of sympt...
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Leaving garbage in the outdoor environment is harmful to nature, and traditionally, the collection process has been challenging, time-consuming, and labor-intensive. In order to automate the process of garbage detecti...
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This paper mainly designs a remote manipulator control system based on programmable logic controller and Internet of Things technology. The system uses Siemens PLC as the robot controller and the Internet of Things de...
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The proceedings contain 128 papers. The topics discussed include: the study of segmentation and recognition technology of breast tumor ultrasound image based on adaptive BP neural network;smart city evaluation from th...
ISBN:
(纸本)9781510661363
The proceedings contain 128 papers. The topics discussed include: the study of segmentation and recognition technology of breast tumor ultrasound image based on adaptive BP neural network;smart city evaluation from the perspective of information theory;facial recognition method based on feature fusion and data enhancing;querying specific message from chat logs of suspects based on keywords expansion;research on one of proportional guidance process based on guidance principle;construction and application of vehicle digital registration system;armored vehicle target vulnerability database software design;the numerical simulation of cylindrical fragments penetrate the multilayer aluminum targets;numerical simulation of long rod projectile penetrating non-explosive reactive armor;and analysis of the relationship between bitcoin, oil prices, and the dow jones industrial average using a wavelet-based approach.
In recent years, event cameras have achieved significant attention due to their advantages over conventional cameras. Event cameras have high dynamic range, no motion blur, and high temporal resolution. Contrary to tr...
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ISBN:
(纸本)9798350349405;9798350349399
In recent years, event cameras have achieved significant attention due to their advantages over conventional cameras. Event cameras have high dynamic range, no motion blur, and high temporal resolution. Contrary to traditional cameras which generate intensity frames, event cameras output a stream of asynchronous events based on brightness change. There is extensive ongoing research on performing computervision tasks like object detection, classification, etc via the event camera. However, due to the unconventional output format of the event camera, it is difficult to perform computervision tasks directly on the event stream. Mostly, works reconstruct the intensity image from the event stream and then perform such tasks. An important and crucial task is feature detection and description. Scale-invariant feature transform (SIFT) is a widely-used scale-invariant keypoint detector and descriptor that is invariant to transformations like scale, rotation, noise, and illumination. In this work, given an event voxel, we directly generate the LoG pyramid for SIFT keypoint detection. We fit a 3rd-degree polynomial and calculate the polynomial roots to compute the scale-space extrema response for SIFT keypoint detection. Since the extrema computation is performed after LoG thresholding, the solution is computationally less expensive. Experimental results validate the effectiveness of our system.
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