The proceedings contain 24 papers. The topics discussed include: using fast multidimensional projections to reveal band and circumplex patterns in reorderable matrices;a 3D spectral-spatial classification of hyperspec...
ISBN:
(纸本)9789898704320
The proceedings contain 24 papers. The topics discussed include: using fast multidimensional projections to reveal band and circumplex patterns in reorderable matrices;a 3D spectral-spatial classification of hyperspectral remote sensing imagery using inception based network;3D face reconstruction from hard blended edges;capsule neural networks in classification of skin lesions;a single RGB image based 3D object reconstruction system;face features-based personality assessment;analysis of capsule networks for image classification;analysis and visual exploration of prediction algorithms for public bicycle sharing systems;and hello, my name is smarttram, human factors is on board, enjoy the ride! developing a human factors program for automatic trams.
Provide an attraction recommendation system that uses deep learning and is powered by the Internet of Things (IoT) to develop the smart city visitor experience. Users of a smart city app or website will be able to rec...
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In today's high technology environment, most of the workflows are migrated to the cloud and related resourcing technologies like fog, mist and edge computing. Here, in this research work, we have given a detailed ...
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Generation of computer-aided design (CAD) models from multi-view images may be useful in many practical applications. To date this problem is usually solved with an intermediate point-cloud reconstruction and involves...
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ISBN:
(纸本)9783031546044;9783031546051
Generation of computer-aided design (CAD) models from multi-view images may be useful in many practical applications. To date this problem is usually solved with an intermediate point-cloud reconstruction and involves manual work to create the final CAD models. In this contribution, we present a novel network for an automated reverse engineering task. Our network architecture combines three distinct stages: A convolutional neural network as the encoder stage, a multi-view pooling stage and a transformer-based CAD sequence generator. The model is trained and evaluated on a large number of simulated input images and extensive optimization of model architectures and hyper-parameters is performed. A proof-of-concept is demonstrated by successfully reconstructing a number of valid CAD models from simulated test image data. Various accuracy metrics are calculated and compared to a state-of-the-art point-based network. Finally, a real world test is conducted supplying the network with actual photographs of two three-dimensional test objects. It is shown that some of the capabilities of our network can be transferred to this domain, even though the training exclusively incorporates purely synthetic training data. However to date, the feasible model complexity is still limited to basic shapes.
The sustainable foraging problem is a dynamic environment testbed for exploring the forms of agent cognition in dealing with social dilemmas in a multi-agent setting. The agents need to resist the temptation of indivi...
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3D Visual Grounding (3D VG) has become increasingly important in applications such as robotics and human-computer interaction. However, accurately localizing target objects in complex 3D scenes based on natural langua...
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Industrial clusters share regional resources to form regional agglomeration effect and enhance competitiveness. The demand for talents in industrial clusters in our country is mainly characterized by the shortage of t...
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In recent times, evolutionary algorithms have been demonstrating significant benefits in feature selection due to their simplicity and global search capability. However, most of the existing evolutionary algorithms ar...
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The worldwide incidence of breast cancer continues to increase annually. Accurate classification of breast cancer subtypes is crucial for improving treatment precision. However, the diagnosis of breast cancer is time-...
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The technique of embedding the owner’s valid copyright information in an audio signal is known as digital audio watermarking. Research in this field has primarily focused on the trade-off between imperceptibility, pa...
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