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SSRN 2022年

作者： Fan, Chao Yang, Litao Lin, Hao Qiu, Yingying School of Artificial Intelligence and Big Data Henan University of Technology Henan Province Zhengzhou City China Key Laboratory of Grain Information Processing and Control Ministry of Education Henan Province Zhengzhou City China School of Information Science and Engineering Henan University of Technology Henan Province Zhengzhou City China

Skin lesion segmentation is a critical method for extracting pathological information from dermoscopy images, which is of great significance for lesion location, recognition, monitoring and treatment. Due to the varied sizes of lesions, different forms and colors, and blurring boundaries, the present detection methods are unable to accurately anticipate local features, which has an impact on the segmentation accuracy. Therefore, the Dual-branch Feature Extraction Network (DFE-Net) is suggested in this paper. We designed two types of encoders based on the Transformer and Efficient Channel Attention (ECA) module, one for extracting the global feature and another for the local feature, before fusing and decoding. Simultaneously, the skip connections from the Enhanced ECA Feature Extraction Modules to decoders are designed to reduce feature loss during decoding, this will restore the boundaries and local features to the greatest extent possible. We test the model on three publicly available skin lesion datasets: PH2, ISIC-2016, and ISIC-2018. The results show that our model is superior to other previous methods, and the segmentation characteristics are more accurate representations of the actual lesion. © 2022, The Authors. All rights reserved.

关键词： Feature extraction

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TRAIL: Trust-Aware Client Scheduling for Semi-Decentralized Federated Learning

arXiv

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arXiv 2024年

作者： Hu, Gangqiang Lu, Jianfeng Han, Jianmin Cao, Shuqin Liu, Jing Fu, Hao School of Computer Science and Technology Zhejiang Normal University China School of Computer Science and Technology Wuhan University of Science and Technology China Key Laboratory of Social Computing and Cognitive Intelligence Dalian University of Technology Ministry of Education China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan Universityof Science and Technology China

Due to the sensitivity of data, Federated Learning (FL) is employed to enable distributed machine learning while safeguarding data privacy and accommodating the requirements of various devices. However, in the context of semidecentralized FL, clients' communication and training states are dynamic. This variability arises from local training fluctuations, heterogeneous data distributions, and intermittent client participation. Most existing studies primarily focus on stable client states, neglecting the dynamic challenges inherent in real-world scenarios. To tackle this issue, we propose a TRust-Aware clIent scheduLing mechanism called TRAIL, which assesses client states and contributions, enhancing model training efficiency through selective client participation. We focus on a semi-decentralized FL framework where edge servers and clients train a shared global model using unreliable intra-cluster model aggregation and inter-cluster model consensus. First, we propose an adaptive hidden semi- Markov model to estimate clients' communication states and contributions. Next, we address a client-server association optimization problem to minimize global training loss. Using convergence analysis, we propose a greedy client scheduling algorithm. Finally, our experiments conducted on real-world datasets demonstrate that TRAIL outperforms state-of-the-art baselines, achieving an improvement of 8.7% in test accuracy and a reduction of 15.3% in training loss. © 2024, CC BY.

关键词： Federated learning

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A Dynamic Safe Arbitrator for Human-Machine Shared control

A Dynamic Safe Arbitrator for Human-Machine Shared Control

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Chinese Automation Congress (CAC)

作者： Haocong Chen Yutao Chen Wu Wang Dingci Lin Jie Huang College of Electrical Engineering and Automation Fuzhou University Fuzhou China 5G+Industrial Internet Institute Fuzhou University Fuzhou China Education Department of Fujian Province Key Laboratory of Industrial Automation Control Technology and Information Processing Fuzhou China

Shared control has become a popular subject of human-machine hybrid intelligence. This paper presents a dynamic safety arbitrator for shared control in an automated vehicle. The vehicle is controlled autonomously by a model predictive controller (MPC) tracking a given trajectory, while at the same time human input is provided via a joystick. Unlike traditional mixed-initiative control methods that blend weighted human and vehicle inputs, the proposed arbitrator first adopts control barrier function (CBF) to generate weights for human and vehicle inputs under safety critical situations, and then employs the null-space based control (NSBC) to merge the two inputs with priorities determined by the weights. As a result, the final input to the vehicle has a clear physical meaning that represents dynamic priorities of human and vehicle autonomous inputs, in which the higher priority input is fully adopted and the lower priority input is partially adopted without intervening the higher priority input. An immediate advantage of the proposed arbitrator is that there is no need to tune the weights between human and autonomous inputs. Simulation results show that the dynamic safe arbitrator is effective for shared control.

关键词： Automation Decision making Predictive models Real-time systems Human in the loop Safety Trajectory

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An inverse-system method for identification of damping rate functions in non-Markovian quantum systems

arXiv

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arXiv 2020年

作者： Xue, Shibei Tan, Lingyu Wu, Rebing Jiang, Min Petersen, Ian R. Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Department of Automation Tsinghua University Beijing100084 China Center for Quantum Information Science and Technology TNList Beijing100084 China School of Electronic and Information Engineering Soochow University Suzhou215006 China Research School of Electrical Energy and Materials Engineering Australian National University Canberra0200 Australia

Identification of complicated quantum environments lies in the core of quantum engineering, which systematically constructs an environment model with the aim of accurate control of quantum systems. In this paper, we present an inverse-system method to identify damping rate functions which describe non-Markovian environments in time-convolution-less master equations. To access information on the environment, we couple a finite-level quantum system to the environment and measure time traces of local observables of the system. By using sufficient measurement results, an algorithm is designed, which can simultaneously estimate multiple damping rate functions for different dissipative channels. Further, we show that identifiability for the damping rate functions corresponds to the invertibility of the system and a necessary condition for identifiability is also given. The effectiveness of our method is shown in examples of an atom and three-spin-chain non-Markovian systems. Copyright © 2020, The Authors. All rights reserved.

关键词： Quantum optics

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OpenHI2 - Open source histopathological image platform

OpenHI2 - Open source histopathological image platform

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2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019

作者： Puttapirat, Pargorn Li, Chen Zhang, Haichuan Deng, Jingyi Dong, Yuxin Shi, Jiangbo He, Hongyu Gao, Zeyu Wang, Chunbao Zhang, Xiangrong Shaanxi Province Key Laboratory of Satellite and Terrestrial Network Tech. RD Xi'an Jiaotong University Xi'an Shaanxi710049 China Xi'an Jiaotong University Department of Software Engineering Xian Shaanxi710049 China School of Electrical Engineering Xi'an Jiaotong University Department of Power System and Automation Xi'an Shaanxi710049 China First Affiliated Hospital of Xi'an Jiaotong University Department of Pathology Xi'an Shaanxi710061 China Institute of Intelligent Information Processing Xidian University Xi'an Shaanxi710071 China

ISBN: (纸本)9781728118673

Transition from conventional to digital pathology requires a new category of biomedical informatic infrastructure which could facilitate delicate pathological routine. Pathological diagnoses are sensitive to many external factors and is known to be subjective. Only systems that can meet strict requirements in pathology would be able to run along pathological routines and eventually digitized the area, and the developed platform should comply with existing pathological routines and international standards. Currently, there are a number of available software tools which can perform histopathological tasks including virtual slide viewing, annotating, and basic image analysis, however, none of them can serve as a digital platform for pathology. Here we describe OpenHI2, an enhanced version Open Histopathological Image platform which is capable of supporting all basic pathological tasks and file formats;ready to be deployed in medical institutions on a standard server environment or cloud computing infrastructure. In this paper, we also describe the development decisions for the platform and propose solutions to overcome technical challenges including responsive region retrieval and viewing, virtual slide magnification, recording of diagnostic areas. These factors would promote OpenHI2 be used as a platform for histopathological images in real-world clinical settings. Furthermore, in research, OpenHI2 inherited the annotation functionality from the previous version, thus acquired annotations can be directly utilized by the newly added machine learning module which include popular machine learning models to perform tasks such as histology image classification and segmentation in the same environment. Addition can be made to the platform since each component is modularized and fully documented. OpenHI2 is free, open-source, and available at https://***/BioAI/OpenHI. © 2019 IEEE.

关键词： Open source software

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Efficient Design of Hybrid Half-band Multi-stage Filter Based on Simulated Annealing Algorithm

Efficient Design of Hybrid Half-band Multi-stage Filter Base...

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IEEE International Conference on High Performance Computing and Communications (HPCC)

作者： Wei Hu Chongwei Zheng Yonghao Wang Jin Zhang Cen Chen Zeng Zeng College of Computer Science and Technology Wuhan University of Science and Technology Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan China Digital Media Technology lab Birmingham City University Birmingham UK Institute for Infocomm Research Singapore

ISBN: (纸本)9781728176499;9781728176505

The oversampling sigma-delta based analog-to-digital converter and digital-to-analog converter (ADC/DAC) architecture can achieve high resolution with effective low hardware cost. It normally introduces latency due to the internal high-performance finite impulse response (FIR) digital filters. In this work, we proposed a novel approach to reduce latency and accurately predict latency caused by the group delay. We propose a filter structure applied to ADC, using the infinite impulse response (IIR) filter and half-band filter (HBF) to construct a hybrid half-band filter (HHBF). A novel modified Simulated Annealing (SA) algorithm is proposed to optimize the best distribution of passband ripple and transition bandwidth that is suitable for audio processing with low latency and computation cost. The experiments show that hybrid HBF proposed in this paper improves the efficiency of the filter in terms of filter cost and group delay comparing to traditional design.

关键词： Sigma-delta modulation Finite impulse response filters IIR filters Simulated annealing Bandwidth Filtering algorithms Prediction algorithms

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A new formal modeling method for web service composition

International Journal of Signal Processing, Image Processing...

引用

International Journal of Signal processing, Image processing and Pattern Recognition 2015年第7期8卷 341-350页

作者： Li, Lin Wang, Cheng College of Computer Science and Technology Wuhan University of Science and Technology WuhanHubei China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System WuhanHubei China Department of Common Required Courses Hubei Institute of Fine Arts China

With the rapid development of e-commerce, the application of web service composition is becoming increasingly important in many areas. If we apply unchecked web service composition, then we can only discover problems afterwards, and we have to devote unnecessary energy to repair. Here, formal modeling serves to be a premise to check. This paper brings up a formal modeling method for web service composition based on BDL (behavioral description language). The structure of this essay is to analyze the description of BPEL process, and we can get the formal model from the BPEL-to-BDL mapping relation. © 2015 SERSC.

关键词： Modeling languages

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A Novel Economical Design of Multistage Decimators for Low Latency Audio Applications

A Novel Economical Design of Multistage Decimators for Low L...

引用

IEEE International Conference on High Performance Computing and Communications (HPCC)

作者： Wei Hu Chongwei Zheng Yonghao Wang Jing Liu Cen Chen Zeng Zeng College of Computer Science and Technology Wuhan University of Science and Technology Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan China Digital Media Technology lab Birmingham City University Birmingham UK Institute for Infocomm Research Singapore

ISBN: (纸本)9781728176499;9781728176505

The oversampling sigma-delta analog-to-digital converter (ADC) is widely used in digital audio systems for its low hardware cost and high precision. The digital filter part of the ADC is the primary source of the silicon and power cost. In this work, we proposed an economical multistage decimation filter architecture to meet the requirements of commercial ADC specifications with a further novel multi-objective optimization strategy. We took group delay and computational cost as objective functions and used annealing algorithm to readjust the stopband attenuation, stopband edge and passband ripple of each filter. Our multistage architecture combines cascaded integrator-comb (CIC) filters, compensating filters and equiripple finite impulse response (FIR) filters at the different stages to balance the overall performance. The experimental results showed that our design approach worked with multi-objective optimization strategy could achieve low group delay with lower cost compared to traditional designs.

关键词： Sigma-delta modulation Finite impulse response filters Computer architecture Filtering algorithms Attenuation Linear programming Silicon

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Optimization of Coordinate Transformation Matrix for Discrete-Time H∞ Static-Output-Feedback control Problems

Optimization of Coordinate Transformation Matrix for Discret...

引用

第三十三届中国控制会议

作者： Zhi-Yong Feng Li Xu Ye Li Huijin Fan Xue-Xun Guo Hubei Key Laboratory of Advanced Technology of Automotive Parts Wuhan University of Technology Hubei Collaborative Innovation Center for Automotive Components Technology Department of Electronics and Information Systems Akita Prefectural UniversityYuri-HonjoAkita 015-0055Japan Department of Control Science and Engineering University of Shanghai for Science and Technology Key Laboratory of Image Processing and Intelligent Control School of AutomationHuazhong University of Science and Technology

ISBN: (纸本)9781479947249

The problem of how to select a coordinate transformation matrix to improve the LMI conditions for H∞ staticoutput-feedback(SOF) control of discrete-time systems is a challenging open *** paper applies a newly proposed strategy to solve this *** iterative algorithm is developed to produce controllers with locally optimal closed-loop H∞*** algorithm is also applied to other H∞ SOF control problems,such as decentralized H∞ SOF control and simultaneous H∞ SOF ***,numerical examples are provided to demonstrate the effectiveness and advantages of the proposed method.

关键词： H∞ control,Static output feedback,Decentralized control,Simultaneous control,Linear matrix inequality(LMI)

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Classification of Large-Scale High-Resolution SAR Images with Deep Transfer Learning

TechRxiv

引用

TechRxiv 2019年

作者： Huang, Zhongling Dumitru, Corneliu Octavian Pan, Zongxu Lei, Bin Datcu, Mihai The Aerospace Information Research Institute Chinese Academy of Sciences Beijing100094 China School of Electronic Electrical and Communication Engineering University of Chinese Academy of Sciences Huairou District Beijing101408 China Key Laboratory of Technology in Geo-spatial Information Processing and Application System Chinese Academy of Sciences Beijing China Wessling 82234 Germany

The classification of large-scale high-resolution SAR land cover images acquired by satellites is a challenging task, facing several difficulties such as semantic annotation with expertise, changing data characteristics due to varying imaging parameters or regional target area differences, and complex scattering mechanisms being different from optical imaging. Given a large-scale SAR land cover dataset collected from TerraSAR-X images with a hierarchical three-level annotation of 150 categories and comprising more than 100,000 patches, three main challenges in automatically interpreting SAR images of highly imbalanced classes, geographic diversity, and label noise are addressed. In this letter, a deep transfer learning method is proposed based on a similarly annotated optical land cover dataset (NWPU-RESISC45). Besides, a top-2 smooth loss function with cost-sensitive parameters was introduced to tackle the label noise and imbalanced classes’ problems. The proposed method shows high efficiency in transferring information from a similarly annotated remote sensing dataset, a robust performance on highly imbalanced classes, and is alleviating the over-fitting problem caused by label noise. What’s more, the learned deep model has a good generalization for other SAR-specific tasks, such as MSTAR target recognition with a state-of-the-art classification accuracy of 99.46%. © 2019, CC BY.

关键词： Synthetic aperture radar

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