With the growth of location-based services, the accumulation of large amounts of trajectory data comes with the challenge of missing data. Existing trajectory imputation methods rely on deterministic models that canno...
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Current mainstream unsupervised video object segmentation(UVOS) approaches typically incorporate optical flow as motion information to locate the primary objects in coherent video frames. However, they fuse appearance...
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Current mainstream unsupervised video object segmentation(UVOS) approaches typically incorporate optical flow as motion information to locate the primary objects in coherent video frames. However, they fuse appearance and motion information without evaluating the quality of the optical flow. When poor-quality optical flow is used for the interaction with the appearance information, it introduces significant noise and leads to a decline in overall performance. To alleviate this issue, we first employ a quality evaluation module(QEM) to evaluate the optical flow. Then, we select high-quality optical flow as motion cues to fuse with the appearance information, which can prevent poor-quality optical flow from diverting the network's attention. Moreover, we design an appearance-guided fusion module(AGFM) to better integrate appearance and motion information. Extensive experiments on several widely utilized datasets, including DAVIS-16, FBMS-59, and You Tube-Objects, demonstrate that the proposed method outperforms existing methods.
With the benefits of reducing time and workforce,automated testing has been widely used for the quality assurance of mobile applications(APPs).Compared with automated testing,manual testing can achieve higher coverage...
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With the benefits of reducing time and workforce,automated testing has been widely used for the quality assurance of mobile applications(APPs).Compared with automated testing,manual testing can achieve higher coverage in complex interactive *** the effectiveness of manual testing is highly dependent on the user operation process(UOP)of experienced *** on the UOP,we propose an iterative Android automated testing(IAAT)method that automatically records,extracts,and integrates UOPs to guide the test logic of the tool across the complex Activity *** feedback test results can train the UOPs to achieve higher coverage in each *** extracted 50 UOPs and conducted experiments on 10 popular mobile APPs to demonstrate IAAT’s effectiveness compared with Monkey and the initial automated *** experimental results show a noticeable improvement in the IAAT compared with the test logic without human *** the 60 minutes test time,the average code coverage is improved by 13.98%to 37.83%,higher than the 27.48%of Monkey under the same conditions.
The application of contrastive learning (CL) to collaborative filtering (CF) in recommender systems has achieved remarkable success. CL-based recommendation models mainly focus on creating multiple augmented views by ...
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This study focuses on BTLC, a peer-to-peer international trade model based on blockchain and smart contracts, which aims to reform the traditional let- ter of credit process, improve international trade efficiency, re...
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作者：
Deng, ShiyuLi, LiXiong, YichenZhang, JianSchool of Computer Science
Beijing International Science and Technology Cooperation Base of Intelligent Decision and Big Data Application Beijing Information Science and Technology University Laboratory of Big Data Decision Making for Green Development Beijing China School of Economics and Management
Beijing International Science and Technology Cooperation Base of Intelligent Decision and Big Data Application Beijing Information Science and Technology University Laboratory of Big Data Decision Making for Green Development Beijing China
Aiming at solving the problem of high time complexity of association rule mining among item-sets in Apriori algorithm and obtaining the set of goal-association relations of single-to-single point type, this paper impr...
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Precipitation forecasting plays an important role in disaster warning,agricultural production,and other *** solve this issue,some deep learning methods are proposed to forecast future radar echo images and convert the...
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Precipitation forecasting plays an important role in disaster warning,agricultural production,and other *** solve this issue,some deep learning methods are proposed to forecast future radar echo images and convert them into rainfall *** spatiotemporal sequence prediction methods are usually based on a ConvRNN structure that combines a Convolutional Neural Network and Recurrent Neural ***,these existing methods ignore the image change prediction,which causes the coherence of the predicted image has ***,these approaches mainly focus on complicating model structure to exploit more historical spatiotemporal ***,they ignore introducing other valuable information to improve *** tackle these two issues,we propose GCMT‐ConvRNN,a multi‐ask framework of *** for precipitation nowcasting as the main task,it combines the motion field estimation and sub‐regression as auxiliary *** this framework,the motion field estimation task can provide motion information,and the sub‐regression task offers future ***,to reduce the negative transfer between the auxiliary tasks and the main task,we propose a new loss function based on the correlation of gradients in different *** experiments show that all models applied in our framework achieve stable and effective improvement.
Aiming to address the shortcomings of Dung Beetle Optimizer (DBO) in the areas of accuracy and convergence speed in dealing with cloud computing task scheduling issues, this paper suggests an advanced Dung Beetle Opti...
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In the field of simultaneous localization and mapping (SLAM), visual odometry (VO) always has great application prospects. In recent years, with the progress in the field of machine learning, methods based on neural n...
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Edge artificial intelligence (AI) has been a promising solution towards 6G to empower a series of advanced techniques such as digital twins, holographic projection, semantic communications, and auto-driving, for achie...
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