In this paper, a deep residual network based on convolutional block attention module (CBAM) is proposed, which is utilized for feature extraction of partially occluded face expression data. The proposed method overcom...
In this paper, a deep residual network based on convolutional block attention module (CBAM) is proposed, which is utilized for feature extraction of partially occluded face expression data. The proposed method overcomes the problem of localized occlusion face feature extraction by focusing on the regions and channels containing important information in the occluded face data through CBAM. Multi-task cascaded convolutional networks (MTCNN) are firstly utilized to localize the key regions of face emotion, and then deep emotion features are extracted by CBAM-ResNet network. The final emotion labels are generated. The effectiveness of this paper's method is verified on the RAF-DB dataset and the occluded CK+ dataset. The experimental accuracy in the RAF-DB dataset is 76.3%, which is 3.74% and 1.64% higher than the accuracy produced by the method of RGBT, and the WLS-RF, respectively. Application experiments are carried out in the real teaching scenario, which verifies the applicability of the algorithm in the real teaching scene.
Occlusion remains an issue in multiple object tracking, which could cause ambiguity in object detection, such as incorrect or missing detection. Under occlusion, a track could experience an early termination, resultin...
Occlusion remains an issue in multiple object tracking, which could cause ambiguity in object detection, such as incorrect or missing detection. Under occlusion, a track could experience an early termination, resulting in identity switches and/or fragmentation. To recover from different lengths of occlusions, the track should be maintained by considering its occlusion status. To address the issues mentioned above, we propose an indicator that can model the track's occlusion extent via geometric information provided by LiDAR data. Through incorporating the indicator into the track management and data association process, it is feasible to prevent tracks from premature termination. The proposed method is evaluated on the collected dataset which undergoes frequent and severe occlusions. Compared to the state-of-the-art probabilistic tracking approach, our approach achieves improvements of 3.26% in MOTA and 5.36% in IDF1. Additionally, we obtain 9.89% improvements in IDF1 specifically for objects experiencing severe occlusions.
In this paper, we propose the innovative use of Intelligent Vehicle Carriers (IVCs) as a key solution to address the energy constraints of small-scale unmanned Intelligent Vehicles (IVs). IVCs function as both transpo...
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ISBN:
(数字)9798350348811
ISBN:
(纸本)9798350348828
In this paper, we propose the innovative use of Intelligent Vehicle Carriers (IVCs) as a key solution to address the energy constraints of small-scale unmanned Intelligent Vehicles (IVs). IVCs function as both transporters and charging stations, significantly boosting the operational range and efficiency of IVs. Our research delves into the IV-IVC collaborative framework, highlighting the existing challenges, exploring potential solutions, and examining a range of applications. This study offers a visionary approach to revolutionizing intelligent transportation systems by leveraging the synergistic relationship between IVs and IVCs.
Phase mixing of Alfvén waves is one of the most promising mechanisms for heating of the solar atmosphere. The damping of waves in this case requires small transversal scales, relative to the magnetic field direct...
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Occupancy grid mapping is an important component in a road scene understanding for autonomous driving. It can encapsulate data from heterogeneous sensor sources like radars, LiDARs, cameras and ultrasonics. At the cor...
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Considering real-valued clocks in timed automata (TA) makes it a practical modeling framework for discrete-event systems. However, the infinite state space brings challenges to the control of TA. To synthesize a super...
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This article considers the problem of the impact of the pandemic on medical personnel in the Russian Federation. During the pandemic, one of the most acute problems is the shortage of medical personnel. The study of t...
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This article considers the problem of the impact of the pandemic on medical personnel in the Russian Federation. During the pandemic, one of the most acute problems is the shortage of medical personnel. The study of the issue of shortage of medical personnel is relevant both for the whole world and for Russia. The authorities of several Russian regions at once, against the backdrop of an increase in the incidence of coronavirus, announced an acute shortage of doctors and mid-level health workers. In Russia, first of all, there was a shortage of primary health care doctors - general practitioners, general practitioners, and pediatricians. Staffing problems were discussed even before the pandemic, but during the pandemic, the workload on the medical staff increased and existing specialists began to leave. This paper presents possible solutions. Such as increasing wages and attracting students to increase staff. The purpose of the study is to analyze the reasons for the lack of personnel, identify existing problems, and formulate recommendations for their elimination.
In this work, the position control of R4 parallel manipulator in Cartesian space has been performed using two types of controllers: proportional and derivative (PD) and adaptive controller. One scenario has been prese...
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Turbo codes are used to reduce the errors that occur when sending a message through a communication channel. They do that by detecting and correcting these errors. They are widely used in applications that need to tra...
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This article is concerned with the design and performance optimization of feedback controllers for state-based switching bilinear systems (SBLSs), where subsystems take the form of bilinear systems in different state ...
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