Flexible sliding windows with adaptive pixel strides

Jiang, Xiaoheng; Pang, Yanwei; Pan, Jing; Li, Xuelong

doi:10.1016/j.sigpro.2014.08.004

Cited by 13 publications

(5 citation statements)

References 33 publications

(41 reference statements)

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“…You [29] studied the seat control problem of two-class pricing on a multi-segment passenger train. Jiang et al [30] proposed a dynamic adjustment method for seat allocation. However, these studies attempted to solve the deterministic seat allocation problem of railways on the basis of fixed ticket, while the uncertainty of passenger demand has not been resolved.…”

Section: Introductionmentioning

confidence: 99%

Time-Dependent Pricing for High-Speed Railway in China Based on Revenue Management

et al. 2019

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High-speed railway (HSR) is recognized as a green transportation mode with lower energy consumption and less pollution emission than other transportation. At present, China has the largest HSR network globally, but the maximum revenue of railway transportation corporations has not been realized. In order to make HSR achieve a favorable position within the fierce competition in the market, increase corporate revenue, and achieve the sustainable development of HSR and railway corporations, we introduce the concept of revenue management in HSR operations and propose an innovative model to optimize the price and seat allocation for HSR simultaneously. In the study, we formulate the optimization problem as a mixed-integer nonlinear programming (MINLP) model, which appropriately captures passengers’ choice behavior. To reduce the computational complexity, we further transform the proposed MINLP model into an equivalent model. Finally, the effectiveness of both the proposed model and solution algorithm are tested and validated by numerical experiments. The research results show that the model can flexibly adjust the price and seat allocation of the corresponding ticketing period according to the passenger demand, and increase the total expected revenue by 5.92% without increasing the capacity.

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Section: Introductionmentioning

confidence: 99%

Time-Dependent Pricing for High-Speed Railway in China Based on Revenue Management

et al. 2019

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“…Yan et al [9] developed a seat allocation model for multiple HSR trains with flexible train formation. Jiang et al [10] proposed a dynamic adjustment method for ticket allocation. Zhao et al [11] proposed a probabilistic nonlinear programming model for the problem of railway passenger ticket allocation.…”

Section: Literature Review and Innovation Of This Papermentioning

confidence: 99%

Ticket Allocation Optimization of Fuxing Train Based on Overcrowding Control: An Empirical Study from China

et al. 2022

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At the peak of passenger flow, some passengers extend travel sections, which will be likely to lead to overcrowding of high-speed railway (HSR) trains. Therefore, the problem of train overcrowding control needs to be considered in ticket allocation. Firstly, by simulating the passenger demand function and utility function, an optimization model of ticket allocation for multiple trains and multiple stops with the goal of maximizing revenue is constructed. Secondly, the concepts of the travel extension coefficient and risk coefficient are introduced, the number of passengers is estimated under the risk coefficient as the probability, and the total number of passengers on the train arriving at any station is obtained. Thus, preventing the number of passengers on the train from exceeding the train capacity is introduced to the ticket allocation optimization model of multiple trains and multiple stops as a constraint. Finally, this model is solved by the particle swarm optimization algorithm (PSO). The research results show that the idea of controlling passenger numbers so as not to exceed train capacity based on ticket allocation proposed in this paper has strong practical feasibility. By reasonably and accurately allocating the tickets to the departure terminal section and long-distance terminal sections, it can ensure that, even if there are some passengers extending their travel section, the train will not be overcrowded under a certain probability, improving the train safety and passenger travel experiences.

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“…While computer vision has advanced significantly, there are still some differences between its approach to environmental perception and that of humans. Computers typically conduct direct feature extraction across the entire image [17,18], whereas humans utilize attention mechanisms to focus on areas of interest. Due to these differences in information processing, researchers have been exploring the use of human-like attention mechanisms to enhance computer vision performance.…”

Section: Introductionmentioning

confidence: 99%

Hybrid Cross-Feature Interaction Attention Module for Object Detection in Intelligent Mobile Scenes

Tian,

Han,

Liu

et al. 2023

Remote Sensing

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Object detection is one of the fundamental tasks in computer vision, holding immense significance in the realm of intelligent mobile scenes. This paper proposes a hybrid cross-feature interaction (HCFI) attention module for object detection in intelligent mobile scenes. Firstly, the paper introduces multiple kernel (MK) spatial pyramid pooling (SPP) based on SPP and improves the channel attention using its structure. This results in a hybrid cross-channel interaction (HCCI) attention module with better cross-channel interaction performance. Additionally, we bolster spatial attention by incorporating dilated convolutions, leading to the creation of the cross-spatial interaction (CSI) attention module with superior cross-spatial interaction performance. By seamlessly combining the above two modules, we achieve an improved HCFI attention module without resorting to computationally expensive operations. Through a series of experiments involving various detectors and datasets, our proposed method consistently demonstrates superior performance. This results in a performance improvement of 1.53% for YOLOX on COCO and a performance boost of 2.05% for YOLOv5 on BDD100K. Furthermore, we propose a solution that combines HCCI and HCFI to address the challenge of extremely small output feature layers in detectors, such as SSD. The experimental results indicate that the proposed method significantly improves the attention capability of object detection in intelligent mobile scenes.

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Flexible sliding windows with adaptive pixel strides

Cited by 13 publications

References 33 publications

Time-Dependent Pricing for High-Speed Railway in China Based on Revenue Management

Time-Dependent Pricing for High-Speed Railway in China Based on Revenue Management

Ticket Allocation Optimization of Fuxing Train Based on Overcrowding Control: An Empirical Study from China

Hybrid Cross-Feature Interaction Attention Module for Object Detection in Intelligent Mobile Scenes

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