Handwritten mathematical expression recognition is still a challenging problem due to its two-dimensional structure and the complexity of handwriting. Handwritten Mathematical Expression Recognition (HMER) methods bas...
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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...
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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.
Despite recent advances in lane detection methods,scenarios with limited-or no-visual-clue of lanes due to factors such as lighting conditions and occlusion remain challenging and crucial for automated ***,current lan...
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Despite recent advances in lane detection methods,scenarios with limited-or no-visual-clue of lanes due to factors such as lighting conditions and occlusion remain challenging and crucial for automated ***,current lane representations require complex post-processing and struggle with specific *** by the DETR architecture,we propose LDTR,a transformer-based model to address these *** are modeled with a novel anchorchain,regarding a lane as a whole from the beginning,which enables LDTR to handle special lanes *** enhance lane instance perception,LDTR incorporates a novel multi-referenced deformable attention module to distribute attention around the ***,LDTR incorporates two line IoU algorithms to improve convergence efficiency and employs a Gaussian heatmap auxiliary branch to enhance model representation capability during *** evaluate lane detection models,we rely on Fr´echet distance,parameterized F1-score,and additional synthetic *** results demonstrate that LDTR achieves state-of-the-art performance on well-known datasets.
Recommendation system is the key to alleviate the problem of information overload. More and more platforms require customers to evaluate and evaluate various standards for products. However, the traditional collaborat...
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Hybrid Power-line/Visible-light Communication(HPVC)network has been one of the most promising Cooperative Communication(CC)technologies for constructing Smart Home due to its superior communication reliability and har...
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Hybrid Power-line/Visible-light Communication(HPVC)network has been one of the most promising Cooperative Communication(CC)technologies for constructing Smart Home due to its superior communication reliability and hardware *** research on HPVC networks focuses on the performance analysis and optimization of the Physical(PHY)layer,where the Power Line Communication(PLC)component only serves as the backbone to provide power to light Emitting Diode(LED)*** designing a Media Access Control(MAC)protocol remains a great challenge because it allows both PLC and Visible Light Communication(VLC)components to operate data transmission,i.e.,to achieve a true HPVC network *** solve this problem,we propose a new HPC network MAC protocol(HPVC MAC)based on Carrier Sense Multiple Access/Collision Avoidance(CSMA/CA)by combining IEEE 802.15.7 and IEEE 1901 ***,we add an Additional Assistance(AA)layer to provide the channel selection strategies for sensor stations,so that they can complete data transmission on the selected channel via the specified CSMA/CA mechanism,*** on this,we give a detailed working principle of the HPVC MAC,followed by the construction of a joint analytical model for mathematicalmathematical validation of the HPVC *** the modeling process,the impacts of PHY layer settings(including channel fading types and additive noise feature),CSMA/CA mechanisms of 802.15.7 and 1901,and practical configurations(such as traffic rate,transit buffer size)are comprehensively taken into ***,we prove the proposed analytical model has the ***,through extensive simulations,we characterize the HPVC MAC performance under different system parameters and verify the correctness of the corresponding analytical model with an average error rate of 4.62%between the simulation and analytical results.
Multimodal social relationship understanding is a research field that integrates information from various sources, including visual and textual modalities, to identify and comprehend interpersonal relationships. Featu...
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Bare PCB (Printed Circuit Board) surface defect detection is an important step in the automated production of PCB. To meet the requirements of production efficiency, the detection must have high real-time performance,...
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The natural gradient boosting method for probabilistic regression (NGBoost) is capable of predicting not only point estimates but also target distributions under sample conditions, thereby quantifying prediction uncer...
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The node category in the graph usually has a strong correlation with the node attribute and the domain. The embedding vector learned by the random walk method only considers the topology of the node, ignoring the cate...
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Some microbes are referred to as model organisms because they are easy to study in the laboratory and hold the ability to retain their characteristics during DNA replication, DNA transcription, and other fundamental p...
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Some microbes are referred to as model organisms because they are easy to study in the laboratory and hold the ability to retain their characteristics during DNA replication, DNA transcription, and other fundamental processes. Studying these microbes in living cells via single-molecule imaging allows us to better understand these processes at highly improved spatiotemporal resolution. Single particle tracking photoactivated localization microscopy(sptPALM) is a robust tool for detecting the positions and motions of individual molecules with tens of nanometers of spatial and millisecond temporal resolution in vivo, providing insights into intricate intracellular environments that traditional ensemble methods cannot. With this approach, the fluorophores are photoactivated stochastically, a series of images are recorded, and the positions of fluorophores are identified in these images, and ultimately the locations are linked together to yield trajectories of individual molecules. Quantitative kinetic and spatial information, such as reaction rates, diffusion coefficients, and localization maps, can be obtained by further analysis. Here, we present a single-molecule tracking protocol that includes sample preparation,data acquisition and brief data processing. This protocol will enable researchers to directly unveil molecular and cellular mechanisms underlying the essential biological processes.
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