Edge is the key information in the process of image smoothing. Some edges, especially the weak edges, are difficult to maintain, which result in the local area being over-smoothed. For the protection of weak edges, we...
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Edge is the key information in the process of image smoothing. Some edges, especially the weak edges, are difficult to maintain, which result in the local area being over-smoothed. For the protection of weak edges, we propose an image smoothing algorithm based on global sparse structure and parameter adaptation. The algorithm decomposes the image into high frequency and low frequency part based on global sparse structure. The low frequency part contains less texture information which is relatively easy to smoothen. The high frequency part is more sensitive to edge information so it is more suitable for the selection of smoothing parameters. To reduce the computational complexity and improve the effect, we propose a bicubic polynomial fitting method to fit all the sample values into a surface. Finally, we use Alternating Direction Method of Multipliers (ADMM) to unify the whole algorithm and obtain the smoothed results by iterative optimization. Compared with traditional methods and deep learning methods, as well as the application tasks of edge extraction, image abstraction, pseudo-boundary removal, and image enhancement, it shows that our algorithm can preserve the local weak edge of the image more effectively, and the visual effect of smoothed results is better.
Social relations, as the basic relationships in our daily life, are a phenomenon unique to human society that shows how people interact in society. Social relations understanding is to infer the existing social relati...
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The integration of deep learning with conventional structured light center extraction techniques improves the accuracy of extracting structural gold centers. The method is divided into three steps. The initial step in...
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Human keypoints detection require the capture of long-range spatial constraints and the fusion of channels information. Many studies adopt attention mechanisms to generate feature weights, thereby enhancing the inform...
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Forest fires pose a serious threat to ecological balance, air quality, and the safety of both humans and wildlife. This paper presents an improved model based on You Only Look Once version 5 (YOLOv5), named YOLO Light...
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Forest fires pose a serious threat to ecological balance, air quality, and the safety of both humans and wildlife. This paper presents an improved model based on You Only Look Once version 5 (YOLOv5), named YOLO Lightweight Fire Detector (YOLO-LFD), to address the limitations of traditional sensor-based fire detection methods in terms of real-time performance and accuracy. The proposed model is designed to enhance inference speed while maintaining high detection accuracy on resource-constrained devices such as drones and embedded systems. Firstly, we introduce Depthwise Separable Convolutions (DSConv) to reduce the complexity of the feature extraction network. Secondly, we design and implement the Lightweight Faster Implementation of Cross Stage Partial (CSP) Bottleneck with 2 Convolutions (C2f-Light) and the CSP Structure with 3 Compact Inverted Blocks (C3CIB) modules to replace the traditional C3 modules. This optimization enhances deep feature extraction and semantic information processing, thereby significantly increasing inference speed. To enhance the detection capability for small fires, the model employs a Normalized Wasserstein Distance (NWD) loss function, which effectively reduces the missed detection rate and improves the accuracy of detecting small fire sources. Experimental results demonstrate that compared to the baseline YOLOv5s model, the YOLO-LFD model not only increases inference speed by 19.3% but also significantly improves the detection accuracy for small fire targets, with only a 1.6% reduction in overall mean average precision (mAP)@0.5. Through these innovative improvements to YOLOv5s, the YOLO-LFD model achieves a balance between speed and accuracy, making it particularly suitable for real-time detection tasks on mobile and embedded devices.
In recent years, Quantized Graph Neural Networks (QGNNs) have emerged as a hot topic of extensive research and industrial interest. While quantization techniques have been utilized in traditional graph neural networks...
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Whole body bone imaging is a commonly used method for the diagnosis of bone metastases, but the images acquired by this method have some problems such as low resolution and poor contrast. In this paper, we propose an ...
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Particle image velocimetry is an optical measurement technique that uses PIV instruments to measure flow fields. However, due to background light fluctuation, noise interference, voltage fluctuation and other factors,...
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In order to address the problem of misjudgment and missing judgment in duplicate data detection by traditional similarity method. The multidimensional similarity redundancy detection algorithm MSRD is proposed in this...
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The design and synthesis of novel photocatalyst with self-temperature control function is an important topic in the field of advanced environmental functional *** this work,submicron-sized magnetic phase change microc...
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The design and synthesis of novel photocatalyst with self-temperature control function is an important topic in the field of advanced environmental functional *** this work,submicron-sized magnetic phase change microcapsules composed of paraffin core and Fe_(3)O_(4)-loaded silica shell are prepared,on which the Bi_(2)WO_(6)crystals is grown in situ through hydrothermal reaction to obtain novel magnetic phase-change-microcapsule-supported Bi_(2)WO_(6)catalyst(MP@FS/BWO).The MP@FS/BWO has a paraffin encapsulation ratio of 57.1%,and the phase change enthalpy of 105.1 J/g in a temperature range of 50–60℃,which endows the MP@FS/BWO with a certain self-temperature regulation ***@FS/BWO shows excellent catalytic performance in the decomposition of rhodamine B under the simulated sunlight *** the light source is turned off,it still has good catalytic ability by maintaining high temperature due to its temperature control function based on the phase transition *** MP@FS/BWO can be easily recycled by magnetic separation and shows good structural stability and *** work provides a new idea for the development of long-effect and energy-saving outdoor photocatalysts.
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