Complex backgrounds, scale and occlusion variance have long limited the accuracy of pedestrian detection. In this paper, we propose a pedestrian detector named convergence and Divergence (CADNet). In "convergence...
详细信息
ISBN:
(数字)9789819756001
ISBN:
(纸本)9789819755998;9789819756001
Complex backgrounds, scale and occlusion variance have long limited the accuracy of pedestrian detection. In this paper, we propose a pedestrian detector named convergence and Divergence (CADNet). In "convergence" network, we propose a cross-scale semantic alignment block (CSAB). CSAB effectively mitigates the background interference and resolves scale variance through multi-scale global contexts aggregation, without extensive computational overhead. In "Divergence" network, we propose a receptive field differentiation block (RFDB) to tackle the challenges of scale and occlusion variance. RFDB generates discriminative features with varying receptive fields, effectively capturing pedestrians across different scales and occlusion conditions. Due to the effectiveness of the proposed components, CADNet achieves an excellent performance of 8.47% and 2.16% MR-2 on a Reasonable subset of CityPersons and Caltech, respectively. Extensive experiments demonstrate the robustness and efficiency of CADNet, ensuring its superior performance in various scenarios.
Recently, the manufacturing industry is changing into a smart manufacturing era with the development of 5G, artificial intelligence, and cloud computing technologies. As a result, Operational technology (OT), which co...
详细信息
ISBN:
(纸本)9781665456456
Recently, the manufacturing industry is changing into a smart manufacturing era with the development of 5G, artificial intelligence, and cloud computing technologies. As a result, Operational technology (OT), which controls and operates factories, has been digitized and used together with Information technology (IT). Security is indispensable in the smart manufacturing industry as a problem with equipment, facilities, and operations in charge of manufacturing can cause factory shutdown or damage. In particular, security is required in smart factories because they implement automation in the manufacturing industry by monitoring the surrounding environment and collecting meaningful information through Industrial IoT (IIoT). Therefore, in this paper, IIoT security proposed in 2022 and recent technology trends are analyzed and explained in order to understand the current status of IIoT security technology in a smart factory environment.
The Conditional GAN generates the human faces with certain conditions applied to its features. In Conditional GANs, the generator and discriminator networks are extended to take in additional conditional information d...
详细信息
Aiming at the contradiction between the globalism and the convergence speed of the UAVS task assignment method, a hybrid swarm intelligence algorithm is proposed, which combines the wolf colony algorithm and simulated...
详细信息
An enhanced variant of the Grey Wolf Optimisation (GWO) technique is presented in this paper, addressing a number of issues, including reduced population diversity, slow convergence and vulnerability to local optima. ...
详细信息
A new task scheduling scheme based on dispersed computing is proposed to address the problem of poor utilization of idle computing resources in the network by the traditional computing paradigm. The scheme designs a d...
详细信息
Industrial Internet of Things (IIoT), as a key link in the transformation of traditional manufacturing to digitalization, can be paired with Multi-access Edge computing (MEC) technology to satisfy the low-latency envi...
详细信息
ISBN:
(纸本)9789819756742;9789819756759
Industrial Internet of Things (IIoT), as a key link in the transformation of traditional manufacturing to digitalization, can be paired with Multi-access Edge computing (MEC) technology to satisfy the low-latency environment required by industry. Nonetheless, the system contends with uncertain environmental factors such as dynamic changes in channel state and random task generation. Motivated by these, this paper designs an intelligent offloading and task caching strategy to reduce the overall execution latency of tasks. The interaction process within system is modeled as an Markov Decision Process (MDP), and we introduce a low-latency scheduling strategy leveraging Deep Reinforcement Learning (DRL), termed DDPG-LL. Besides, the proposed strategy is tailored for optimizing the task queue of the MEC server. By considering factors such as priority, waiting time, and completion expectations, queue adjustments are dynamically made at each time slot. Simulation results demonstrate that the proposed strategy achieves rapid and stable convergence, and effectively reduces the completion latency of tasks compared to the baseline strategies.
In this paper, we study the multi-source data security fusion analysis technology based on federated learning. A rapid model convergence technique based on data distribution difference evolution comparison is proposed...
详细信息
With the rapid development of the economy and industrial production, industrial automation technology continues to improve, and the application of single-chip microcomputer automatic control systems in the industrial ...
详细信息
This paper deals with In-Memory computing (IMC), where computations are performed within the memory. IMC is a memory architecture to overcome the performance gap between processors and memory. In this work, A novel vo...
详细信息
暂无评论