52,499 Result(s)
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A lightweight road crack detection algorithm based on improved YOLOv7 model
Road crack detection plays a crucial role in protecting road safety. However, early manual detection is not only time-consuming and laborious but also highly inefficient. Although existing road inspection vehi...
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A new uncertainty processing method for trajectory prediction
In many domains, trajectory prediction a crucial task. Uncertain information, such as complementary and correlated information between multiple features, complex interactive information, weather and temperatur...
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Research on water level measurement technology based on the residual length ratio of image characters
Aiming at the low efficiency and poor adaptability of traditional water level measurement methods, a water level measurement technology based on the residual length ratio of image characters is proposed in thi...
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Source bias reduction for source-free domain adaptation
Source-free domain adaptation (SFDA) mainly aims to the problem of not being able to access the source domain data during the model migration process. Although significant breakthroughs have been achieved, the...
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Attention-driven residual-dense network for no-reference image quality assessment
With the rapid development of deep learning, convolutional neural networks have been applied to no-reference image quality assessment (NR-IQA), but most methods focus on the design of complex networks, which n...
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A novel approach to geometric algebra-based variable step-size LMS adaptive filtering algorithm
The study of signal processing has recently devoted significantly more attention to adaptive filtering techniques. By addressing the shortcoming of the conventional geometric algebra-based fixed step-size leas...
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Detecting the penetration of malicious behavior in big data using hybrid algorithms
Information security must be maintained because the amount of data in the world today is growing exponentially. The issues related to security are growing as big data usage increases. Finding ways to identify ...
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Towards stronger illumination robustness of local feature detection and description based on auxiliary learning
Local feature detection and description play a crucial role in various computer vision tasks, including image matching. Variations in illumination conditions significantly affect the accuracy of these applicat...
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TAENet: transencoder-based all-in-one image enhancement with depth awareness
Recently, CNN-based all-in-one image enhancement methods have been proposed to solve multiple image degradation tasks. However, these CNN-based methods usually have two limitations. One limitation is that they...
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Emotion recognition with attention mechanism-guided dual-feature multi-path interaction network
Electroencephalography (EEG)-based emotion recognition has gained widespread attention recently. Although many deep learning methods have been proposed, it is still challenging to simultaneously fuse informati...
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Probabilistic load forecasting based on quantile regression parallel CNN and BiGRU networks
In the dynamic smart grid landscape, accurate probabilistic forecasting of electric load is critical. This paper presents a novel 24-hour-ahead probabilistic load forecasting model by integrating quantile regr...
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Effective polarization-based image dehazing through 3D convolution network
The presence of numerous microscopic particles within haze contributes to the scattering of atmospheric light, leading to a notable degradation in the quality of captured images. Polarization, an intrinsic att...
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Patchlpr: a multi-level feature fusion transformer network for LiDAR-based place recognition
LiDAR-based place recognition plays a crucial role in autonomous vehicles, enabling the identification of locations in GPS-invalid environments that were previously accessed. Localization in place recognition ...
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Small target detection in drone aerial images based on feature fusion
The use of object detection technology in unmanned aerial vehicles is a crucial area of research in computer vision. Aerial images captured by drones exhibit differences in object shape and size compared to tr...
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A multi-scale feature extraction and fusion method for bearing fault diagnosis based on hybrid attention mechanism
Bearing failure is one of the most common failures in rotating mechanical. Therefore, rapid and accurate diagnosis of bearing faults is of great significance for ensuring the reliability of equipment. In recen...
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A MDA-LSTM network for remaining useful life estimation of lithium batteries
Remaining useful life (RUL) of energy storage batteries estimation is of great significance to battery failure warning and battery safety. Previous methods have primarily relied on the battery’s capacity as th...
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PMENet: a parallel UNet based on the fusion of multiple attention mechanisms for road crack segmentation
The presence of road cracks significantly impacts both traffic safety and road maintenance. Therefore, accurate detection of road cracks plays a crucial role in road maintenance and management. This study focu...
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A shrinkage adaptive filtering algorithm with graph filter models
In this study, we focus on an adaptive filtering algorithm that utilizes variable step-size and incorporates graph filter models within the realm of graph signal processing. The algorithm optimizes the step-si...
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Mind-bridge: reconstructing visual images based on diffusion model from human brain activity
Human brain vision is mysterious and complex, and it interprets the world through the connection between the brain and the eyes. In recent years, several methods have relied on fMRI to successfully reconstruct...
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Msap: multi-scale attention probabilistic network for underwater image enhancement network
Underwater image enhancement is a key technology for improving underwater image quality and enhancing visualization. Due to the light propagation characteristics and absorption scattering by water bodies in un...