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WRC Symposium on Advanced Robotics and Automation (WRC SARA)

作者： Linqi Zhou Zhihua Chen Jun Liu Zhi Liu Yumeng Chen Liting Zhang key Laboratory of Jiangxi Province for Image Processing and Pattern Recognition and MOE Key Lab of Nondestructive Testing Technology Nanchang Hangkong University Nanchang China State Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing China

Gait planning of quadruped robots plays an important role in achieving less walking, including dynamic and static gait. In this article, a static and dynamic gait control method based on center of gravity stability margin is proposed. Firstly, the robot model and kinematics modeling are introduced. Secondly, the robot’s foot static and dynamic gait were planned and the foot trajectory was designed. Finally, two types of gait of the robot were simulated using Vrep simulation software, and the differences in stability and speed between the coordinated gait with speed and stability in the static and dynamic gait of a 12 degree of freedom robot were analyzed, verifying the effectiveness of the gait control method proposed in this paper.

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Edge direction dispersion and its application in automatic suitable-matching area selection

Edge direction dispersion and its application in automatic s...

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Chinese Control and Decision Conference

作者： Qing-Hai, Ding Xin-Rong, Yu Hai-Bo, Luo Hong-Mei, Liu Research Institute of General Development and Demonstration of Equipment Equipment of Air Force Bejing 100076 China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang 110016 China Graduate School Chinese Academy of Sciences Beijing 100039 China Key Laboratory of Optical-Electronics Information Processing Chinese Academy of Science Shenyang 110016 China Key Laboratory of Image Understanding Computer Vision Liaoning Province 110016 China AVIC HONGDU Aviation Industry Group Ltd. Nanchang 330024 China

ISBN: (纸本)9781424487363

Automatic suitable-matching area selection is an important research in visual guidance, scene matching and local non-texture target tracking. Meanwhile, it is the major research subject in computer vision and accurate guidance. In this paper, a new characteristic quantity, i.e., the edge direction dispersion was defined. Then the computation method, parameters selection and real-time realization of this characteristic quantity were investigated. Furthermore, the application of its characteristic in automatic suitable-matching area selection was studied. With a reasonable design for calculation precision, solving method for arctan(x) function in [-∞,+∞ ] could be simplified to linearization calculations in [0, 0.25], then a fast algorithm for arctan(x) function was presented. Experimental results showed that the sub-image extracted by our fast algorithm had higher matching level and was suitable to be a matching template. All the calculations involved in the proposed matching algorithm could be done in one filed period and the real-time request could be satisfied. Moreover, this characteristic of edge direction could also be used to measure the comparability of template and real-time images, which could be widely used in automatic target recognition and target tracking. © 2011 IEEE.

关键词： Target tracking

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Multi-adapter RGBT tracking

arXiv

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arXiv 2019年

作者： Li, Chenglong Lu, Andong Zheng, Aihua Tu, Zhengzheng Tang, Jin School of Computer Science and Technology Anhui University Hefei230601 China Key Laboratory of Industrial Image Processing and Analysis of Anhui Province Institute of Physical Science and Information Technology Anhui University Hefei230601 China

The task of RGBT tracking aims to take the complementary advantages from visible spectrum and thermal infrared data to achieve robust visual tracking, and receives more and more attention in recent years. Existing works focus on modality-specific information integration by introducing modality weights to achieve adaptive fusion or learning robust feature representations of different modalities. Although these methods could effectively deploy the modality-specific properties, they ignore the potential values of modality-shared cues as well as instance-aware information, which are crucial for effective fusion of different modalities in RGBT tracking. In this paper, we propose a novel Multi-Adapter convolutional Network (MANet) to jointly perform modality-shared, modality-specific and instance-aware feature learning in an end-to-end trained deep framework for RGBT tracking. We design three kinds of adapters within our network. In a specific, the generality adapter is to extract shared object representations, the modality adapter aims at encoding modality-specific information to deploy their complementary advantages, and the instance adapter is to model the appearance properties and temporal variations of a certain object. Moreover, to reduce computational complexity for real-time demand of visual tracking, we design a parallel structure of generic adapter and modality adapter. Extensive experiments on two RGBT tracking benchmark datasets demonstrate the outstanding performance of the proposed tracker against other state-of-the-art RGB and RGBT tracking algorithms. Copyright © 2019, The Authors. All rights reserved.

关键词： Machine learning

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Exploration of Red and Deep Red Thermally Activated Delayed Fluorescence Molecules Constructed Via Intramolecular Locking Strategy

SSRN

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SSRN 2024年

作者： Fan, Jianzhong Liu, Huanling Wang, Yan Zhao, Xin Song, Yuzhi Lin, Lili Wang, Chuan-Kui Shandong Province Key Laboratory of Medical Physics and Image Processing Technology Institute of Materials and Clean Energy School of Physics and Electronics Shandong Normal University Jinan250014 China State Key Laboratory of Luminescent Materials and Devices South China University of Technology China

Red and deep red (DR) organic light-emitting diodes (OLEDs) have garnered increasing attention due to their widespread applications in display technology and lighting devices. However, most red OLEDs exhibit low luminescence efficiency, severely limiting their practical applications. To address this challenge, we theoretically design four novel TADF molecules with red and DR luminescence using intramolecular locking strategies building upon the experimental findings of DCN-DLB and DCN-DSP, and their crystal structures are predicted with the lower energy and higher packing density. The photophysical properties and luminescence mechanism of six molecules in toluene and crystal are clarified using the first principles calculation and thermal vibration correlation function (TVCF) method. The proposed design strategy is anticipated to offer several advantages: enhanced electron-donating capabilities, more rigid structures, longer emission wavelengths and higher luminescence efficiency. Specifically, we introduce oxygen atoms and nitrogen atoms as intramolecular locks, and the newly developed DCN-DBF and DCN-PHC have redshifted emission, narrow singlet-triplet energy gap (ΔEST), fast reverse intersystem crossing rate and enhanced photoluminescence quantum yield (PLQY). Notably, DCN-DBF achieves both long wavelength emission and high efficiency, with emission peaks at 598 nm and 587 nm corresponding to PLQY of 52.16% and 43.37% in toluene and crystal, respectively. Our work not only elucidates the relationship between molecular structures and photophysical properties, but also proposes feasible intramolecular locking design strategies and four promising red and DR TADF molecule, which could provide a valuable reference for the design of more efficient red and DR TADF emitters. © 2024, The Authors. All rights reserved.

关键词： Toluene

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Improved frame-layer bit allocation scheme for H.264/AVC rate control

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Journal of Shanghai Jiaotong University (Science) 2009年第2期14 E卷 143-148页

作者： Lin, Gui-Xu Zheng, Shi-Bao Zhu, Liang-Jia Institute of Image Communication and Information Processing Department of Electronic Engineering Shanghai Jiaotong University Shanghai 200240 China Shanghai Key Laboratory of Digital Media Processing and Transmissions Shanghai Jiaotong University Shanghai 200240 China Department of Automatic Control National University of Defense Technology Changsha 410073 China

In this paper, we aim at improving the video quality degradation due to high motions or scene changes. An improved frame-layer bit allocation scheme for H.264/AVC rate control is proposed. First, current frame is pre-encoded in 16 × 16 modes with a fixed quantization parameter (QP). The frame coding complexity is then measured based on the resulting bits and peak signal-to-ratio (PSNR) in the pre-coding stage. Finally, a bit budget is calculated for current frame according to its coding complexity and inter-frame PSNR fluctuation, combined with the buffer status. Simulation results show that, in comparison with the H.264 adopted rate control scheme, our method is more efficient to suppress the sharp PSNR drops caused by high motions and scene changes. The visual quality variations in a sequence are also relieved. Copyright.

关键词： Budget control

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A Research of Heart Rate Prediction Model Based on Evolutionary Neural Network

A Research of Heart Rate Prediction Model Based on Evolution...

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International Conference on Intelligent Computation and Bio-Medical Instrumentation (ICBMI)

作者： Feng Xiao Ming Yuchi Mingyue Ding Jun Jo Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Life College of Science and Technology Huazhong University of Science and Technology Wuhan China School of Information and Communication Technology Griffith University QLD Australia

Heart rate (HR) signal analysis is widely used in the medicine and medical research area. Physical activities (PA) are commonly recognized to greatly affect the changes of heart rate. A method of Evolutionary Neural Network - Neuro-evolution of Augmenting Topologies (NEAT) is used to build a PA-based HR predictor model. Through special coding, crossover and mutation operator, NEAT can implement network topology and connectivity weights evolution simultaneously. The common problem in evolutionary neural network, like competing conventions, how to protect the new innovation are effectively solved. The experimental results demonstrated the application potential of the approach.

关键词： Heart rate Biological neural networks Training Monitoring Neurons Encoding Biomedical monitoring

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Transclaw U-Net: Claw U-Net With Transformers for Medical image Segmentation

Transclaw U-Net: Claw U-Net With Transformers for Medical Im...

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IEEE International Conference on Information communication and Signal processing (ICICSP)

作者： Chang Yao Menghan Hu Qingli Li Guangtao Zhai Xiao-Ping Zhang Shanghai Key Laboratory of Multidimensional Information Processing East China Normal University Shanghai China Institute of Image Communication and Information Processing Shanghai Jiao Tong University Shanghai China Department of Electrical Computer and Biomedical Engineering Ryerson University Toronto Canada

In medical image analysis, the long-range spatial features are often not accurately obtained by the traditional convolutional neural networks. Hence, we propose a TransClaw U-Net network structure. The transformer part is added after three convolution operations to fuse shallow features extracted by convolution operations for maximally encoding the long-range spatial features between patches. The “Claw” in TransClaw U-net means that we add the bottom upsampling part to retain the deepest feature information for detail segmentation. In addition, the modified three-channel global attention mechanism to blend the outputs of three channels (the encoding part, the bottom upsampling part and the decoding part) to effectively extract image contours. The experimental results on Synapse Multi-organ Segmentation Dataset show that TransClaw U-Net performs better than other networks. The results of ablation experiments prove the effectiveness of the three improved components of the network and influence of input image size and skip-connection numbers on network performance. The source code will be publicly available once the paper is accepted.

关键词： Measurement image segmentation image coding Convolution Fuses Source coding Transformers

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Theoretical Insights on Highly Efficient X-Shaped Near-Infrared Thermal Activation Delayed Fluorescence Emitter

SSRN

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SSRN 2024年

作者： Zhang, Kai Liu, Huanling Cai, Lei Fan, Jianzhong Lin, Lili Wang, Chuan-Kui Li, Jing School of Physics and Physical Engineering Qufu Normal University Qufu273165 China Shandong Province Key Laboratory of Medical Physics and Image Processing Technology School of Physics and Electronics Shandong Normal University Jinan250014 China

The near-infrared (NIR) thermally activated delayed fluorescence (TADF) molecules hold practical application value in various fields, including biological imaging, anti-counterfeiting, sensors, telemedicine, photomicrography, and night vision display. These molecules have emerged as a significant development direction in organic electroluminescent devices, offering exciting possibilities for future technological advancements. Despite the remarkable potential of NIR-TADF molecules in various applications, the development of molecules that exhibit both long-wavelength emission and high efficiency remains a significant challenge. Herein, based on T-type and Y-type TADF molecules BCN-TPA and ECN-TPA, a novel X-type TADF molecule X-ECN-TPA is theoretically designed through a molecular fusion strategy. Utilizing first-principles calculations and the thermal vibration correlation function (TVCF) method, the photophysical properties and luminescent mechanisms of these three molecules in both solvent and solid states (doped films) are revealed. A comparison of the luminescent properties of isomeric BCN-TPA and ECN-TPA shows that the enhanced luminescence efficiency of BCN-TPA in the solid states is attributed to higher radiative rates and lower non-radiative rates. Furthermore, compared to BCN-TPA and ECN-TPA, X-ECN-TPA exhibits significant conjugation extension, resulting in a pronounced redshift, reaching 831 nm and 813 nm in solvent and solid, respectively. Importantly, molecular fusion significantly increases the transition dipole moment density between the donor and acceptor, leading to a substantial increase in radiative transition rates. Additionally, molecular fusion effectively reduces the energy gap between the first singlet excited state (S1) and the first triplet excited state (T1), facilitating the improvement of the reverse intersystem crossing (RISC) process. This work not only designs a novel efficient NIR-TADF molecule but also proposes a strategy for design

关键词： Molecules

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Research on Multi-level Attention-based Human Pose Estimation

Research on Multi-level Attention-based Human Pose Estimatio...

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Algorithms, High Performance Computing and Artificial Intelligence (AHPCAI), International Conference on

作者： Jun Gao Hua Huang QiShen Li ShaoQi Xia School of Information Engineering Nanchang Hangkong University Nanchang Jiangxi China Key Laboratory of Jiangxi Province for Image Processing and Pattern Recognition Nanchang Jiangxi China School of Software Nanchang Hangkong University Nanchang Jiangxi China

Detecting human key points from a single image is very challenging due to occlusion, blurring, illumination and scale changes. In this paper, this problem is addressed by designing an effective network structure. Since global and local information plays an important role in reasoning about human body structure and invisible keypoints, Multi-level Attention Network (MAN) is proposed. First, compared with traditional multi-resolution networks, it enables multi-resolution feature maps with greater information variance by generating them directly from the highest resolution feature map, which in turn increases the abundance of feature information after final fusion. Secondly, it effectively integrates global and local information in different resolution feature maps through the Feature Alignment Attention Block(FAAB), and intensifies them in a targeted manner. On the COCO dataset, with HRNet (Sun K. et al [1]) as the baseline network, HRNet of inserted MAN improves 1.1-2.3 AP points over the baseline network.

关键词： Computational modeling High performance computing Pose estimation Lighting Feature extraction Cognition Sun

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Research on attention-based multiscale information fusion with the real-time instance segmentation method

Research on attention-based multiscale information fusion wi...

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Algorithms, High Performance Computing and Artificial Intelligence (AHPCAI), International Conference on

作者： Yifan He Hua Huang Qishen Li Guiwen Zhang School of Information Engineering Nanchang Hangkong University Nanchang Jiangxi China Key Laboratory of Jiangxi Province for Image Processing and Pattern Recognition Nanchang Jiangxi China School of Software Nanchang Hangkong University Nanchang Jiangxi China

Instance segmentation is a comprehensive computer vision task that involves a wide range of other tasks. Recently, the study of real-time instance segmentation methods has received more attention for the development of autonomous driving. Although existing real-time instance segmentation methods are fast, their accuracy does not meet practical needs. Most methods go for segmentation based on object detection, and their effectiveness is overly dependent on the effectiveness of detection. This paper proposes a new attention-based multiscale information fusion method based on Cheng, T. et al. [1]. Firstly, the PPM module of the baseline network is replaced with the module Multiscale Context Attention (MSCA) designed in this paper based on the baseline network, which uses atrous convolution with different ratios to obtain information of four scales, and then uses non-local attention to enhance the information of features. It can effectively suppress the interference of redundant information on the instance segmentation results. Secondly, a new feature fusion approach is designed, which no longer uses bilinear interpolation, but sub-pixel up sampling combined with attention. We did experiments related to this module on the coco dataset and demonstrated its effectiveness, with a 0.5% improvement over the baseline network.

关键词： Interpolation Computer vision Convolution High performance computing Interference Object detection Real-time systems

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