Background: The IoT (Internet of Things) assigns to the capacity of Device-to-Machine (D2M) connections, which is a vital component in the development of the digital economy. IoT integration with a human being enables...
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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 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.
Task scheduling for virtual machines (VMs) has shown to be essential for the effective development of cloud computing at the lowest cost and fastest turnaround time. A number of research gaps about job schedule optimi...
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Gesture recognition has diverse application prospects in the field of human-computer ***,gesture recognition devices based on strain sensors have achieved remarkable results,among which liquid metal materials have con...
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Gesture recognition has diverse application prospects in the field of human-computer ***,gesture recognition devices based on strain sensors have achieved remarkable results,among which liquid metal materials have considerable advantages due to their high tensile strength and *** improve the detection sensitivity of liquid metal strain sensors,a sawtooth-enhanced bending sensor is proposed in this *** with the results from previous studies,the bending sensor shows enhanced resistance *** addition,combined with machine learning algorithms,a gesture recognition glove based on the sawtooth-enhanced bending sensor is also fabricated in this study,and various gestures are accurately *** the fields of human-computer interaction,wearable sensing,and medical health,the sawtooth-enhanced bending sensor shows great potential and can have wide application prospects.
The Traveling Salesman Problem (TSP) seeks the shortest closed tour that visits each city once and returns to the starting city. This problem is NP-hard, so it is not easy to solve using conventional methods. The grey...
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This paper introduces an advanced road damage detection algorithm that effectively addresses the shortcomings of existing models, including limited detection performance and large parameter sizes, by utilizing the YOL...
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The maintainability of source code is a key quality characteristic for software *** approaches have been proposed to quantitatively measure code *** approaches rely heavily on code metrics,e.g.,the number of Lines of ...
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The maintainability of source code is a key quality characteristic for software *** approaches have been proposed to quantitatively measure code *** approaches rely heavily on code metrics,e.g.,the number of Lines of Code and McCabe’s Cyclomatic *** employed code metrics are essentially statistics regarding code elements,e.g.,the numbers of tokens,lines,references,and branch ***,natural language in source code,especially identifiers,is rarely exploited by such *** a result,replacing meaningful identifiers with nonsense tokens would not significantly influence their outputs,although the replacement should have significantly reduced code *** this end,in this paper,we propose a novel approach(called DeepM)to measure code maintainability by exploiting the lexical semantics of text in source *** leverages deep learning techniques(e.g.,LSTM and attention mechanism)to exploit these lexical semantics in measuring code *** key rationale of DeepM is that measuring code maintainability is complex and often far beyond the capabilities of statistics or simple ***,DeepM leverages deep learning techniques to automatically select useful features from complex and lengthy inputs and to construct a complex mapping(rather than simple heuristics)from the input to the output(code maintainability index).DeepM is evaluated on a manually-assessed *** evaluation results suggest that DeepM is accurate,and it generates the same rankings of code maintainability as those of experienced programmers on 87.5%of manually ranked pairs of Java classes.
Diabetes retinopathy (DR) is one of the complications of diabetes. Early diagnosis of retinopathy is helpful to avoid vision loss or blindness. The difficulty of this task lies in the significant differences in the si...
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Background: The main objective of the Internet of Things (IoT) has significantly influenced and altered technology, such as interconnection, interoperability, and sensor devices. To ensure seamless healthcare faciliti...
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The flexible job shop scheduling problem (FJSP) is a classic NP-hard problem, and the quality of its scheduling solution directly affects the operational efficiency of the manufacturing system. However, the traditiona...
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