2021
DOI: 10.1016/j.eswa.2020.114535
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A 6-DOFs event-based camera relocalization system by CNN-LSTM and image denoising

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Cited by 20 publications
(7 citation statements)
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“…This, for the first time, reveals the potential of event data to address the large-scale relocalization problem. Later on, additional denoising modules to further increase the pose estimation performance are introduced in [200]. Remarks: Currently, the event-based SLAM systems employing deep learning are generally decoupled as separate modules rather than the cross-event frame and pose-map joint estimation as traditionally processed in visual SLAM.…”
Section: Visual Slammentioning
confidence: 99%
“…This, for the first time, reveals the potential of event data to address the large-scale relocalization problem. Later on, additional denoising modules to further increase the pose estimation performance are introduced in [200]. Remarks: Currently, the event-based SLAM systems employing deep learning are generally decoupled as separate modules rather than the cross-event frame and pose-map joint estimation as traditionally processed in visual SLAM.…”
Section: Visual Slammentioning
confidence: 99%
“…Rezaei et al ( 33 ) applied data mining technology to stock forecasting. Jin et al ( 34 ) applied CNN and LSTM models to camera positioning research. Vidal and Kristjanpoller ( 35 ) used a CNN-LSTM model to predict gold volatility.…”
Section: Literature Reviewmentioning
confidence: 99%
“…A model evaluation index is commonly used in prediction research ( 32 , 34 , 35 ). In this study, the root mean square error (RMSE), mean absolute percentage error (MAPE), and mean absolute error (MAE) were selected to evaluate the performances of the proposed models.…”
Section: Proposed Modelmentioning
confidence: 99%
“…Among them, English composition is gradually converted from manual marking to automatic marking, which gradually improves marking efficiency and reduces teachers' teaching pressure. However, the traditional English composition error detection system has a low accuracy rate of grammar detection and a high rate of error detection for words such as verbs, prepositions, and coronals, which cannot meet the current requirements of college English grammar-assisted teaching [1][2][3]. In response to this problem, a large number of studies have been proposed by scholars and experts.…”
Section: Introductionmentioning
confidence: 99%