Many application from the bee colony health state monitoring could be efficiently solved using a computer vision techniques. One of such challenges is an efficient way for counting the number of incoming and outcoming...
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Many application from the bee colony health state monitoring could be efficiently solved using a computer vision techniques. One of such challenges is an efficient way for counting the number of incoming and outcoming bees, which could be used to further analyse many trends, such as the bee colony health state, blooming periods, or for investigating the effects of agricultural spraying. In this paper, we compare three methods for the automated bee counting over two own datasets. The best performing method is based on the ResNet-50 convolutional neural network classifier, which achieved accuracy of 87% over the BUT1 dataset and the accuracy of 93% over the BUT2 dataset. Copyright (c) 2024 The Authors.
The project addresses the challenge of accurately identifying blurred faces in computer vision and facial recognition. It introduces a novel framework that integrates deblurring techniques, utilizing point spread func...
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Most current pavement crack detection tasks depend on Convolutional Neural Networks (CNNs) and vision Transformer Networks (ViT) for feature extraction, and this dependency often makes it difficult to effectively capt...
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Human-robot interaction is composed of multiple aspects that together create a single experience. In this paper we present a humanoid head that is designed for human-robot interaction as a tele-operated robot meant to...
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ISBN:
(纸本)9788993215243
Human-robot interaction is composed of multiple aspects that together create a single experience. In this paper we present a humanoid head that is designed for human-robot interaction as a tele-operated robot meant to be controlled as a remote Avatar. A real-time audio signalprocessing algorithm is presented that uses an abstracted representation of speaking to provide users with a clear sense of presence during an interaction. We avoid using any video feeds of real human faces, nor creating artificial skins, which emphasizes the capabilities and intent of our robot to be a friendly and unique contribution to the emerging field of physical humanoid avatars.
Flower Species recognition has been a major field in image processing. Recognition fails many times the reason behind this is lack of knowledge about medicinal flower among the normal ones. vision based technique has ...
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The main goal of this article is to propose a software architecture allowing the integration of RFID (Radio Frequency Identification ) sensors in the motion strategy for a simulated mobile robot. RFID systems are comp...
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In recent years, video matting has become a hot topic across various industries, especially with the extensive use of portrait video matting. Therefore, achieving precise and rapid matting results has become a focal p...
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During the last few years, remote sensing is considerably used for Earth observation for the environment and sustainable development. The temporal classes of satellite images provide better information for monitoring ...
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Accurate temperature estimation is crucial in metal additive manufacturing ensuring component quality and process efficiency. This study introduces the use of Convolutional Neural Networks (CNNs), namely MobileNet and...
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ISBN:
(纸本)9788080406370;9798350362688
Accurate temperature estimation is crucial in metal additive manufacturing ensuring component quality and process efficiency. This study introduces the use of Convolutional Neural Networks (CNNs), namely MobileNet and ResNet, to predict temperatures directly from melt pool images without the need for extensive preprocessing. Through comparative analysis, MobileNet demonstrated superior performance over ResNet, achieving a mean absolute error of 0.0562 and a correlation coefficient of 0.9900. These findings underscore the effectiveness of CNNs in real-time temperature prediction tasks within Laser-Directed Energy Deposition with wire (DED-LB/w), highlighting significant advancements and setting the stage for further technological enhancements.
Scene Graph Generation (SGG) aims to identify objects and their relationships in visual scenes but faces two key challenges: high computational overhead, particularly for real-time applications, and the long-tailed di...
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