检索结果-内蒙古大学图书馆

5th International Conference on Smart Sensors and Application, ICSSA 2024

作者： Murtaza, Ali Khairuddin, Uswah Faudzi, Ahmad A.M. Hamamoto, Kazuhiko Malaysia-Japan International Institute of Technology Universiti Teknologi Malaysia Kuala Lumpur Malaysia Centre for Artificial Intelligence and Robotics Universiti Teknologi Malaysia Johor Baru Malaysia School of Information Science and Technology Tokai University Tokyo Japan

ISBN: (纸本)9798350354294

Shadow removal poses a significant challenge in computer vision as it seeks to accurately restore image details obscured by shadowed areas. Existing methods for shadow removal often struggle to strike a balance between computational complexity, speed, and performance, rendering many models either too resource-intensive or inadequately effective for real-world applications. Recognizing this gap, we introduce a novel Frequency Guided Network that integrates the benefits of frequency domain processing using Discrete Wavelet Transform with the benefits of deep learning. By decomposing input signals into low and high frequencies, our approach enables the network to prioritize the recovery of crucial information from low-frequency regions while preserving essential high-frequency details, which risk getting lost in the deeper network layers. Notably, our model exhibits impressive efficiency, with a mere parameter count of less than half a million while rivaling the performance of models with significantly more parameters – up to 200 times in some cases. This architecture allows us to process a 1024x1024 image in just 0.14s, demonstrating it’s suitability for real world scenarios. © 2024 IEEE.

关键词： Frequency domain analysis

来源：评论

学校读者我要写书评

暂无评论

Dark Object Detection Based on Detail Feature Enhancement and Cross-aligned Attention

Dark Object Detection Based on Detail Feature Enhancement an...

引用

2024 8th International Conference on Electrical, Mechanical and Computer Engineering (ICEMCE)

作者： Song Xiong Weiliang Zuo Zhongye Liu Jingmin Xin Nanning Zheng National Key Laboratory of Human Machine Hybrid Augmented Intelligence Institute of Artificial Intelligence and Robotics Xi’an Jiaotong University Xi’an China

ISBN: (数字)9798331506230

ISBN: (纸本)9798331506247

Images captured in dark and low-light environments present significant challenges for feature extraction algorithms in computer vision, particularly impacting the performance of object detection tasks due to inadequate lighting and severe noise. Previous multi-level feature extraction methods aimed to enhance performance by directly fusing features from different layers but often overlooked the misalignment and degradation of cross-scale features during fusion. We hypothesize that reducing differences between cross-level features before fusion can yield stronger feature representations. In this paper, we propose a Detail Feature Enhancement Block (DFEB) and a Detail Feature Enhancement Network (DFEN) based on it, specifically designed to enhance low-texture detail features in low-light images, thereby improving the model’s ability to capture image features from the source. Additionally, we introduce a Cross-Aligned Attention-based (CAFF) multi-level feature fusion method. Specifically, we compute cross-attention between adjacent feature layers before fusion and use deformable convolutions to integrate degraded differential feature maps into the neighboring intermediate image features, eliminating differences between multi-level detail features. This ensures that subsequent feature fusion captures more comprehensive and accurate low-light image information. By combining these components, we present a new framework for dark object detection based on detail feature enhancement and cross-aligned attention. Extensive experiments on the ExDark dataset demonstrate the effectiveness of our method in enhancing feature extraction, yielding state-of-the-art results in dark object detection tasks.

关键词： Degradation Computer vision Pedestrians Fuses Wildlife Noise Lighting Object detection Feature extraction Monitoring

来源：评论

学校读者我要写书评

暂无评论

LIIF-GAN: Learning Representations With Local Implicit Image Function and GAN for Realistic Images on a Continuous Scale 33

LIIF-GAN: Learning Representations With Local Implicit Image...

引用

33rd British Machine Vision Conference Proceedings, BMVC 2022

作者： Kang, Jun Seok Ahn, Sang Chul KIST school University of Science and Technology Seoul Korea Republic of Artificial Intelligence and Robotics Institute Korea Institute of Science and Technology Seoul Korea Republic of

Recently, the Local Implicit Image Function (LIIF) has been proposed, which can generate continuous 2D image representation for pixel-based images. The continuous image representation can be presented at any resolution. However, the LIIF representation has limited fidelity when presented at higher resolution, resulting in unrealistic images. To solve this problem, simply adding a GAN can produce a realistic image, but it degrades the local structure of the image. In this paper, we propose the LIIF-GAN, a novel architecture-based deep model, to generate realistic images at continuous scales while maintaining local image structures. It utilizes a generative adversarial network (GAN) and multiple decoders for encoder features at different levels. We show that the LIIF-GAN can generate a more realistic continuous image representation than previous methods. Furthermore, we show that our new architecture retains the local image structure better than simply using a GAN with the existing architecture. The performance of the proposed method is demonstrated qualitatively and quantitatively through various experiments. © 2022. The copyright of this document resides with its authors. It may be distributed unchanged freely in print or electronic forms.

关键词： Generative adversarial networks

来源：评论

学校读者我要写书评

暂无评论

Investigation on Mechanical and Tribological Characteristics of Al–Zn Alloys Under Different Conditions

引用

Journal of The Institution of Engineers (India): Series D 2024年 1-9页

作者： Pruthvi, H.M. Biradar, Srikumar Chetan Kumar, D.S. Biradar, Iranna M. Manjunatha, M.C. Prem Chand, R. Anil Kumar, B.N. Shenoy, Ghanashyam Department of Mechanical Engineering Dr. T Thimmaiah Institute of Technology Karnataka KGF India Department of Mechanical Engineering Atria Institute of Technology Karnataka Bengaluru India Department of Mechanical Engineering New Horizon College of Engineering Karnataka Bengaluru India BAZE University Abuja Nigeria Department of Mechanical Engineering Bangalore Institute of Technology Karnataka Bengaluru India Department of Robotics and Artificial Intelligence Bangalore Institute of Technology Karnataka Bengaluru India

Aluminum alloys are a crucial material due to their high resistance to corrosion and strength to weight ratio, particularly in pressure systems and transport applications. However, they have low melting temperatures and are relatively soft compared to other engineering materials. Utilising secondary reinforcing components such as tungsten carbide, fly ash, mica, boron carbide, silicon carbide, graphite, e-glass, and aluminium oxide, researchers have recently concentrated on creating metal matrix composites. Stir casting was used to create aluminium alloys with different weight percentages of magnesium and zinc. The alloys were then re-aged at 150 °C for different holding times. SEM image of a worn-out surface reveals material flow, scratches, and narrow grooves that are caused by wear parameters including applied stress, sliding velocity, and sliding distance. Only 5.57% more ultimate tensile strength was achieved for the highest weight percentage of magnesium and zinc after 7 h of ageing. Improved mechanical qualities were seen in SEM pictures, and regression analysis confirmed the experimental findings. © The Institution of Engineers (India) 2024.

关键词： Heat treatment

来源：评论

学校读者我要写书评

暂无评论

Robust Practical Stabilization for Complex Dynamical Networks With DoS Attacks and Actuator Saturation

引用

IEEE Transactions on Systems, Man, and Cybernetics: Systems 2025年第5期55卷 3108-3118页

作者： Shi, Xueya Peng, Zhinan Yu, Junzhi Li, Hongfei Southwest University College of Electronic and Information Engineering Chongqing400715 China Sichuan Artificial Intelligence Research Institute Yibin644000 China University of Electronic Science and Technology of China School of Automation Engineering Chengdu611731 China Peking University State Key Laboratory for Turbulence and Complex Systems Department of Advanced Manufacturing and Robotics College of Engineering Beijing100871 China

This article addresses the problem of designing an attack-resilient adaptive event-triggered (AET) controller for complex dynamical networks (CDNs) under DoS attacks and actuator saturation, with a focus on robust practical stability (RPS). First, considering the impact of DoS attacks on closed-loop systems, an AET controller against DoS attacks is designed. Unlike other event-triggered controllers, the complete timeline is divided, and the AET controller is built with two switching modes based on the intervals of dormant and active periods of DoS attacks in which the system is located. Second, to reconcile AET controller with actuator saturation, a switched system modeling approach is established that explicitly incorporates saturation constraints into the coupled network dynamics. Third, a switched Lyapunov-Krasovskii functional (LKF) is proposed, with which sufficient conditions are provided to ensured the RPS, and a joint design strategy is developed for the desired triggered matrix and feedback gain using linear matrix inequalities (LMIs). Moreover, the results are generalized to the case of actuator faults, indicating that the system is able to achieve RPS with actuator faults. Finally, the proposed method is verified through an example. © 2013 IEEE.

关键词： Lyapunov functions

来源：评论

学校读者我要写书评

暂无评论

Toward few-shot domain adaptation with perturbation-invariant representation and transferable prototypes

引用

Frontiers of Computer Science 2022年第3期16卷 83-93页

作者： Junsong FAN Yuxi WANG He GUAN Chunfeng SONG Zhaoxiang ZHANG Center for Research on Intelligent Perception and Computing National Laboratory of Pattern RecognitionInstitute of AutomationChinese Academy of SciencesBeijing 100190China University of Chinese Academy of Sciences Beijing 100049China Centre for Artificial Intelligence and Robotics HKISI CASHongKong 999077China

Domain adaptation(DA)for semantic segmentation aims to reduce the annotation burden for the dense pixellevel prediction *** focuses on tackling the domain gap problem and manages to transfer knowledge learned from abundant source data to new target *** recent works have achieved rapid progress in this field,they still underperform fully supervised models with a large margin due to the absence of any available hints in the target *** that few-shot labels are cheap to obtain in practical applications,wc attempt to leverage them to mitigate the performance gap between DA and fully supervised *** key to this problem is to leverage the few-shot labels to learn robust domain-invariant predictions *** this end,we first design a data perturbation strategy to enhance the robustness of the ***,a transferable prototype module is proposed to bridge the domain gap based on the source data and few-shot *** means of these proposed methods,our approach can perform on par with the fully supervised models to some *** conduct extensive experiments to demonstrate the effectiveness of the proposed methods and report the state-of-the-art performance on two popular DA tasks,i.e.,from GTA5 to Cityscapes and SYNTHIA to Cityscapes.

关键词： domain adaptation semantic segmentation

来源：评论

学校读者我要写书评

暂无评论

sEMG-based Sarcopenia risk classification using empirical mode decomposition and machine learning algorithms

引用

Mathematical Biosciences and Engineering 2024年第2期21卷 2901-2921页

作者： Kumar, Konki Sravan Lee, Daehyun Jamsrandoj, Ankhzaya Soylu, Necla Nisa Jung, Dawoon Kim, Jinwook Mun, Kyung Ryoul Center for Artificial Intelligence Korea Institute of Science and Technology Seoul Korea Republic of KHU-KIST Department of Converging Science and Technology Graduate School Kyung Hee University Seoul Korea Republic of Department of Human Computer Interface and Robotics Engineering University of Science and Technology Daejeon Korea Republic of Department of Computer Science Ozyegin University Istanbul Turkey

Early detection of the risk of sarcopenia at younger ages is crucial for implementing preventive strategies, fostering healthy muscle development, and minimizing the negative impact of sarcopenia on health and aging. In this study, we propose a novel sarcopenia risk detection technique that combines surface electromyography (sEMG) signals and empirical mode decomposition (EMD) with machine learning algorithms. First, we recorded and preprocessed sEMG data from both healthy and at-risk individuals during various physical activities, including normal walking, fast walking, performing a standard squat, and performing a wide squat. Next, electromyography (EMG) features were extracted from a normalized EMG and its intrinsic mode functions (IMFs) were obtained through EMD. Subsequently, a minimum redundancy maximum relevance (mRMR) feature selection method was employed to identify the most influential subset of features. Finally, the performances of state-of-the-art machine learning (ML) classifiers were evaluated using a leave-one-subject-out cross-validation technique, and the effectiveness of the classifiers for sarcopenia risk classification was assessed through various performance metrics. The proposed method shows a high accuracy, with accuracy rates of 0.88 for normal walking, 0.89 for fast walking, 0.81 for a standard squat, and 0.80 for a wide squat, providing reliable identification of sarcopenia risk during physical activities. Beyond early sarcopenia risk detection, this sEMG-EMD-ML system offers practical values for assessing muscle function, muscle health monitoring, and managing muscle quality for an improved daily life and well-being. © 2024 American institute of Mathematical Sciences. All rights reserved.

关键词： Empirical mode decomposition

来源：评论

学校读者我要写书评

暂无评论

Multi-Step Model Predictive Safety Filters: Reducing Chattering by Increasing the Prediction Horizon

Multi-Step Model Predictive Safety Filters: Reducing Chatter...

引用

IEEE Conference on Decision and Control

作者： Federico Pizarro Bejarano Lukas Brunke Angela P. Schoellig the Learning Systems and Robotics Lab University of Toronto Robotics Institute and the Vector Institute for Artificial Intelligence Toronto Canada Technical University of Munich and the Munich Institute for Robotics and Machine Intelligence (MIRMI) Germany

Learning-based controllers have demonstrated su-perior performance compared to classical controllers in various tasks. However, providing safety guarantees is not trivial. Safety, the satisfaction of state and input constraints, can be guaranteed by augmenting the learned control policy with a safety filter. Model predictive safety filters (MPSFs) are a common safety filtering approach based on model predictive control (MPC). MPSFs seek to guarantee safety while minimizing the difference between the proposed and applied inputs in the immediate next time step. This limited foresight can lead to jerky motions and undesired oscillations close to constraint boundaries, known as chattering. In this paper, we reduce chattering by considering input corrections over a longer horizon. Under the assumption of bounded model uncertainties, we prove recursive feasibility using techniques from robust MPC. We verified the proposed approach in both extensive simulation and quadrotor exper-iments. In experiments with a Crazyflie 2.0 drone, we show that, in addition to preserving the desired safety guarantees, the proposed MPSF reduces chattering by more than a factor of 4 compared to previous MPSF formulations.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Contralateral Movement Constraint Based Gait Intervention Using a Powered Hip Exoskeleton 8

Contralateral Movement Constraint Based Gait Intervention Us...

引用

8th IEEE International Conference on Advanced robotics and Mechatronics, ICARM 2023

作者： Wang, Zilu Zhou, Zhihao Wang, Qining College of Engineering Peking University Beijing100871 China Institute for Artificial Intelligence Peking University Beijing100871 China Beijing Engineering Research Center of Intelligent Rehabilitation Engineering Beijing100871 China Department of Advanced Manufacturing and Robotics College of Engineering The Institute for Artificial Intelligence Peking University Beijing100871 China University of Health and Rehabilitation Sciences Qingdao266071 China National Key Laboratory of General Artificial Intelligence BIGAI Beijing100080 China

ISBN: (纸本)9798350300178

Hemiparetic gait patterns of stroke survivors has been widely focused on nowadays with various robot-assist gait intervention approaches. In this paper, we use a powered hip exoskeleton to provide resistance on one side of the wearer during walking and explored the variation of the other side of the lower limb in kinematics, ground reaction forces, and EMG signals. The preliminary results on healthy adults indicated that the difference in hip joint angles, EMG area under the curve, co-contraction index, and synergy weight were observed under the contra-lateral intervention. This study shows potentials that powered hip exoskeleton-induced non-hemiplegic side constraints may be a new rehabilitation way for stroke patients in the near future. © 2023 IEEE.

关键词： Patient rehabilitation

来源：评论

学校读者我要写书评

暂无评论

Control of the Wheeled Bipedal Robot on Roads with Large and Unknown Inclination 16th

Control of the Wheeled Bipedal Robot on Roads with Large...

引用

16th International Conference on Intelligent robotics and Applications, ICIRA 2023

作者： Tu, Baining Lu, Biao Piao, Minnan Institute of Robotics and Automatic Information Systems College of Artificial Intelligence Nankai University Tianjin300350 China Institute of Intelligence Technology and Robotic Systems Shenzhen Research Institute of Nankai University Shenzhen518083 China College of Computer Science and Technology Civil Aviation University of China Tianjin300300 China

ISBN: (纸本)9789819964918

To keep the balance and the stable movement of a wheeled bipedal robot (WBR) on a road with large, unknown and continuously variable inclination, a control strategy based on nonlinear sliding mode controller (SMC) and unscented kalman filter (UKF) is proposed in this study. This strategy can directly identify the angle of the slope in real-time based on the nonlinear model, which helps to cope with various unknown road conditions. Simulations have shown that the proposed control architecture can tackle with gentle, sharp and sinusoidal terrains in both small and large scale with the extreme inclination of 47. 5 ∘. Besides, the WBR can start at a slope even exceed 20 ∘ without any prior information about the surroundings, which demonstrates its robustness to the initial terrain condition. Results also show that the proposed strategy works more swift and stable, compared to three other control architectures: single LQR, single SMC and SMC combined with extended kalman filter (EKF). © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2023.

关键词： Sliding mode control

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：