In the field of traffic management operations, in order to realize the effective inspection and control of the same target vehicle by multiple police resources, this paper proposes a multi-objective path optimization ...
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The abstract is a mandatory element that should summarize the con- tents of the paper and should contain 15–250 words. Abstract and keywords are made freely available in SpringerLink. automation technology is current...
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The efficiency of a bidirectional full-bridge DCDC converter is determined by the magnitude of the reverse power and inductor current stress. Although the presence of inner current shifting in the DPS control reduces ...
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Random-matrix based extended object tracking (EOT) has received much attention for the simple yet effective scheme. Multiple sensors can bring more information due to the different perspectives and characteristics esp...
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One of the cornerstones of Lean manufacturing, according to academic research, is the 5S+1, which introduces quality in manufacturing. This study aims to demonstrate how computer-based vision and object detection algo...
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ISBN:
(纸本)9783031381645;9783031381652
One of the cornerstones of Lean manufacturing, according to academic research, is the 5S+1, which introduces quality in manufacturing. This study aims to demonstrate how computer-based vision and object detection algorithms, can assist in the implementation of safety as 6th S in 5S+1 by monitoring and identifying employees who disregard accepted safety procedures, like wearing Personal Protective Equipment (PPE). The research evaluated the performance indicators of a detection technique and reviewed and analyzed it. To confirmworkers' PPE compliance, the suggested model used the You-Only-Look-Once (YOLO v7) architecture. A deep learning technique was subsequently applied to confirm the safety helmets and safety vests. This strategy is determined to be the most effective when using the VGG-16 algorithm, achieving an 80% F1 score and processing 11.79 frames per second (FPS), making it ideal for real-time detection.
In response to the problems of heavy workload and long handling time caused by manual forklift handling of parts in automobile manufacturing enterprises producing large parts, introduction of intelligent material hand...
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The proposed method in this paper is an innovative approach for combining Continuous Wavelet Transform (CWT), and Recurrent Convolutional Neural Network (RCNN) to analyze ECG signals. The proposed method's objecti...
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The micro-Doppler effect captures the fine motion characteristics of maritime targets, serving as a crucial feature for distinguishing between sea clutter and targets, thereby enhancing radar target detection and reco...
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A priority tracking framework to enable scalable tracking of pedestrians for self-driving cars in dense scenes is developed. Reachability analysis is used on the ego-vehicle and pedestrian tracks to assign different t...
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ISBN:
(数字)9781665490429
ISBN:
(纸本)9781665490429
A priority tracking framework to enable scalable tracking of pedestrians for self-driving cars in dense scenes is developed. Reachability analysis is used on the ego-vehicle and pedestrian tracks to assign different tracking strategies based on perceived priority. Therefore, computationally heavy algorithms such as 3D multi-object tracking (MOT) can be performed on priority objects, while less relevant tracks are maintained by lower-level trackers. The approach is empirically evaluated in simulated and real traffic scenarios with dense detection of pedestrians. We show that our approach reduces the number of objects tracked by the 3D MOT by 5 fold when compared to the standard approach, and ensures the ego vehicle satisfies the same key criteria for passive safety.
Amidst the course of drilling, the measurement while drilling (MWD) signal will be mixed with a large number of noise signals. These noises are mainly caused by various mechanical vibrations in the downhole. The usefu...
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