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1.
Tracking-by-detection (TBD) is a significant framework for visual object tracking. However, current trackers are usually updated online based on random sampling with a probability distribution. The performance of the learning-based TBD trackers is limited by the lack of discriminative features, especially when the background is full of semantic distractors. We propose an attention-driven data augmentation method, in which a residual attention mechanism is integrated into the TBD tracking network as supplementary references to identify discriminative image features. A mask generating network is used to simulate changes in target appearances to obtain positive samples, where attention information and image features are combined to identify discriminative features. In addition, we propose a method for mining hard negative samples, which searches for semantic distractors with the response of the attention module. The experiments on the OTB2015, UAV123, and LaSOT benchmarks show that this method achieves competitive performance in terms of accuracy and robustness.  相似文献   
2.
In this paper, a novel method is proposed for increasing the performance through coupling of top-down models adjusting the object detector based on a new loss function. Generally, object detectors and keypoint estimators are sequentially used in real-time multi-person pose estimations; however, these two models are separately trained. Therefore, the results of the object detector are not optimized for the keypoint estimator. To solve this problem, we analyze the relationship between the two models and propose a feedback-based loss optimization in the object detector, based on the estimation results of the keypoint estimator. In addition, the resulting bounding box of the object detector is readjusted to improve the accuracy of the keypoint estimation model. The experimental results demonstrate that the proposed approach can perform real-time operations with a high frame rate similar to that of the baseline model. Moreover, it achieved an accuracy of 74.2 average precision (AP), which is higher than the state-of-the-arts model including the human detector used in the experiment.  相似文献   
3.
随着通信技术的快速发展及智能设备的普及,网络规模、网元数量的不断增长,通信设备巡检任务成倍增加,给巡检系统的存储带来了巨大挑战,传统文件存储方式已无法满足要求。通过研究分布式对象存储,基于MinIO设计实现了一种新的巡检系统存储方案,可有效提升系统存储效率和可扩展性。该方案已经在江苏移动实际应用,支撑常态化巡检工作,对于网络运维及管理有较好的参考意义。  相似文献   
4.
5.
在信息化的互联网时代,普遍覆盖的视频监控装置,为目标人员追踪和调查取证提供了丰富的数据支持。但是目标人员的移动性和不可预知性给管理带来了很大挑战,特别是单摄像头视野的局限性增大了数据处理难度。本文基于行人重识别和目标追踪两大技术,旨在建立一个可疑人员侦察系统。该系统能够在不同地点的多摄像头场景下实现对同一可疑人员的持续追踪。其中引入行人重识别技术,在一定程度上避免了多个摄像头之间切换时目标丢失的现象,并尽可能减少跟踪过程中人工重定位的频率,从而优化侦察系统的性能。  相似文献   
6.
为了研究激光刻痕工艺参数对取向电工钢表面的磁畴形貌、刻痕线宽度和铁损的影响规律,开展了激光刻痕工艺试验。结果表明,激光刻痕后取向电工钢表面的磁畴宽度明显细化,且随着输入电流的增加,磁畴宽度先减小后增大;刻痕线宽度随着输入电流的增加而增大。对于本次试验样品,通过对比分析,确定最佳激光刻痕工艺参数为电流为 12 A,激光频率为 5 kHz,刻痕速度为 800 mm/s,该参数下铁损改善率可达 11.81%。  相似文献   
7.
设计了一种开关磁阻直线电机,使用JMAG软件对其进行了仿真和优化。进行了推力公式的推导,研究了导通顺序和初始位置对电机推力的影响,并分析了三种典型情况的磁力线分布。对电机的定子和动子的齿部和轭部高度、宽度及铁耗进行仿真优化,得出了最优参数。将有取向硅钢应用于该电机,研究了推力与轧制角的关系,并与使用普通硅钢的开关磁阻直线电机进行了对比,推力有一定提升。提出在动子齿部开切向槽的方案,结果表明,开切向槽对推力的影响较小,并能显著减小推力波动。  相似文献   
8.
对2250 mm热轧生产线生产的取向硅钢热轧钢带的合金体系进行了设计,制定了合理的加热制度和热轧轧制工艺。对添加稀土元素Ce的取向硅钢铸坯和热轧钢带进行了分析,探究了稀土元素Ce对取向硅钢低倍组织、热轧织构及成品磁性能的影响。结果表明,稀土元素Ce能够细化取向硅钢连铸坯低倍组织和热轧显微组织,提高取向硅钢成品磁性能。  相似文献   
9.
Combinatorial auction is a useful trade manner for transportation service procurements in e-marketplaces. To enhance the competition of combinatorial auction, a novel auction mechanism of two-round bidding with bundling optimization is proposed. As the recommended the auction mechanism, the shipper/auctioneer integrates the objects into several bundles based on the bidding results of first round auction. Then, carriers/bidders bid for the object bundles in second round. The bundling optimization is described as a multi-objective model with two criteria on price complementation and combination consistency. A Quantum Evolutionary Algorithm (QEA) with β-based rotation gate and the encoding scheme based on non-zero elements in complementary coefficient matrix is developed for the model solution. Comparing with a Contrast Genetic Algorithm, QEA can achieve better computational performances for small and middle size problems.  相似文献   
10.
Induction machines (IM) constitute a theoretically interesting and practically important class of nonlinear systems. They are frequently used as wind generators for their power/cost ratio. They are described by a fifth‐order nonlinear differential equation with two inputs and only three state variables available for measurement. The control task is further complicated by the fact that IM are subject to unknown (load) disturbances and the parameters can be of great uncertainty. One is then faced with the challenging problem of controlling a highly nonlinear system, with unknown time‐varying parameters, where the regulated output, besides being unmeasurable, is perturbed by an unknown additive signal. Passivity‐based control (PBC) is a well‐established structure‐preserving design methodology which has shown to be very powerful to design robust controllers for physical systems described by Euler‐Lagrange equations of motion. PBCs provide a natural procedure to "shape" the potential energy yielding controllers with a clear physical interpretation in terms of interconnection of the system with its environment and are robust vis á vis to unmodeled dissipative effects. One recent approach of PBC is the Interconnection and Damping Assignment Passivity‐Based Control (IDA‐PBC) which is a very useful technique to control nonlinear systems assigning a desired (Port‐Controlled Hamiltonian) structure to the closed‐loop. The aim of this paper is to give a survey on different PBC of IM. The originality of this work is that the author proves that the well known field oriented control of IM is a particular case of the IDA‐PBC with disturbance.  相似文献   
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