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IEEE Transactions on Signal and Power Integrity 2024年 3卷 37-46页

作者： Chen, Quankun Ma, Hanzhi Li, Da Tao, Tuomin Tan, Shurun Liu, En-Xiao Schutt-Aine, Jose Li, Er-Ping Zhejiang University Key Laboratory of Advanced Micro/Nano Electronic Devices and Smart Systems and Applications College of Information Science and Electronic Engineering Hangzhou310027 China Zhejiang University University of Illinois at Urbana-Champaign Institute Haining314400 China A∗star Institute of High Performance Computing Singapore138632 Singapore University of Illinois at Urbana-Champaign Department of Electrical and Computer Engineering UrbanaIL61820 United States

This article introduces a comprehensive approach for designing and analyzing signal integrity in heterogeneous integrated systems that incorporate neuromorphic Darwin chips. The proposed integrated system architecture includes a neuromorphic Darwin chip, digital signal processing unit, microcontroller unit, field programmable gate arrays, and coding and decoding modules to encode and reconstruct analog spiking signals. The study evaluates the encoding module and the heterogeneous integration structure and conducts signal integrity analysis. To achieve optimal signal integrity performance, the article proposes a novel binocular eye diagram analysis technique. This innovative approach guides the encoding algorithm modification and improves the overall system performance. This research is the first to combine joint field-circuit simulation, heterogeneous integration modeling, and signal integrity analysis of the Darwin neuromorphic chip, and it is expected to serve as a valuable reference for future studies on similar systems. © 2022 IEEE.

关键词： Neural networks

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DAMPER: A Dual-Stage Medical Report Generation Framework with Coarse-Grained MeSH Alignment and Fine-Grained Hypergraph Matching

arXiv

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arXiv 2024年

作者： Huang, Xiaofei Chen, Wenting Liu, Jie Lu, Qisheng Luo, Xiaoling Shen, Linlin Computer Vision Institute College of Computer Science and Software Engineering Shenzhen University Shenzhen China Department of Electrical Engineering City University of Hong Kong Kowloon Hong Kong National Engineering Laboratory for Big Data System Computing Technology Shenzhen University China Guangdong Provincial Key Laboratory of Intelligent Information Processing China

Medical report generation is crucial for clinical diagnosis and patient management, summarizing diagnoses and recommendations based on medical imaging. However, existing work often overlook the clinical pipeline involved in report writing, where physicians typically conduct an initial quick review followed by a detailed examination. Moreover, current alignment methods may lead to misaligned relationships. To address these issues, we propose DAMPER, a dual-stage framework for medical report generation that mimics the clinical pipeline of report writing in two stages. In the first stage, a MeSH-Guided Coarse-Grained Alignment (MCG) stage that aligns chest X-ray (CXR) image features with medical subject headings (MeSH) features to generate a rough keyphrase representation of the overall impression. In the second stage, a Hypergraph-Enhanced Fine-Grained Alignment (HFG) stage that constructs hypergraphs for image patches and report annotations, modeling high-order relationships within each modality and performing hypergraph matching to capture semantic correlations between image regions and textual phrases. Finally,the coarse-grained visual features, generated MeSH representations, and visual hypergraph features are fed into a report decoder to produce the final medical report. Extensive experiments on public datasets demonstrate the effectiveness of DAMPER in generating comprehensive and accurate medical reports, outperforming state-of-the-art methods across various evaluation metrics. Copyright © 2024, The Authors. All rights reserved.

关键词： Coarse-grained modeling

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SweepEvGS: Event-Based 3D Gaussian Splatting for Macro and Micro Radiance Field Rendering from a Single Sweep

arXiv

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arXiv 2024年

作者： Wu, Jingqian Zhu, Shuo Wang, Chutian Shi, Boxin Lam, Edmund Y. Department of Electrical and Electronic Engineering The University of Hong Kong Pokfulam Hong Kong National Key Laboratory for Multimedia Information Processing and National Engineering Research Center of Visual Technology School of Computer Science Peking University Beijing100871 China

—Recent advancements in 3D Gaussian Splatting (3D-GS) have demonstrated the potential of using 3D Gaussian primitives for high-speed, high-fidelity, and cost-efficient novel view synthesis from continuously calibrated input views. However, conventional methods require high-frame-rate dense and high-quality sharp images, which are time-consuming and inefficient to capture, especially in dynamic environments. Event cameras, with their high temporal resolution and ability to capture asynchronous brightness changes, offer a promising alternative for more reliable scene reconstruction without motion blur. In this paper, we propose SweepEvGS, a novel hardware-integrated method that leverages event cameras for robust and accurate novel view synthesis across various imaging settings from a single sweep. SweepEvGS utilizes the initial static frame with dense event streams captured during a single camera sweep to effectively reconstruct detailed scene views. We also introduce different real-world hardware imaging systems for real-world data collection and evaluation for future research. We validate the robustness and efficiency of SweepEvGS through experiments in three different imaging settings: synthetic objects, real-world macro-level, and real-world micro-level view synthesis. Our results demonstrate that SweepEvGS surpasses existing methods in visual rendering quality, rendering speed, and computational efficiency, highlighting its potential for dynamic practical applications. Copyright © 2024, The Authors. All rights reserved.

关键词： Rendering (computer graphics)

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A Knowledge Acquisition Method for Consumer Electronics Based on Triadic Hesitant Fuzzy Concept

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IEEE Transactions on Consumer Electronics 2025年

作者： Xin, Xianwei Zhao, Ye Wang, Chenyang Xu, Jiucheng Taleb, Tarik Henan Normal University School of Computer and Information Engineering Xinxiang453007 China Key Laboratory of Computational Intelligence and Chinese Information Processing Ministry of Education Taiyuan237016 China Computer and Software Engineering School of College of Shenzhen University Guangdong Shenzhen518060 China Key Laboratory of Artificial Intelligence and Personalized Learning in Education of Henan Province Henan Province 453007 China Ruhr University Bochum Faculty of Electrical Engineering and Information Technology Bochum44801 Germany

With the growing intelligence and personalization of consumer electronic products, extracting effective information has become a key challenge in Consumer Electronics (CE). Triadic Concept Analysis (TCA), an important extension of Formal Concept Analysis (FCA), is widely applied but often struggles to handle the hesitant fuzzy characteristics in real-world data. To address this gap, we propose a Triadic Hesitant Fuzzy Concept (THFC) model. First, we introduce the concept of a triadic hesitant fuzzy background, integrating the fuzzy and hesitant nature of data in the CE environment. We propose a knowledge acquisition method based on THFC, which constructs a multi-granularity knowledge space with a dynamic adjustment mechanism. This method captures subtle distinctions between different types of information and their hierarchical structures in the context of CE, offering significant support for knowledge discovery and decision-making in complex environments. Building on this, we design a variable-precision hybrid similarity measurement (VP-HSM) method to extract core, adjunct, and edge concepts, thus providing more precise and structured knowledge for data analysis and decision-making in CE. Experimental results on publicly available datasets show that the proposed method significantly improves classification accuracy and stability, effectively handling hesitant fuzzy data and improving the accuracy of concept extraction. © 1975-2011 IEEE.

关键词： Data accuracy

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Audio-Visual Quality Assessment for User Generated Content: Database and Method

Audio-Visual Quality Assessment for User Generated Content: ...

引用

IEEE International Conference on Image processing

作者： Yuqin Cao Xiongkuo Min Wei Sun Xiaoping Zhang Guangtao Zhai Institute of Image Communication and Information Processing Shanghai Jiao Tong University Department of Electrical Computer and Biomedical Engineering Toronto Metropolitan University

With the explosive increase of User Generated Content (UGC), UGC video quality assessment (VQA) becomes more and more important for improving users’ Quality of Experience (QoE). However, most existing UGC VQA studies only focus on the visual distortions of videos, ignoring that the user’s QoE also depends on the accompanying audio signals. In this paper, we conduct the first study to address the problem of UGC audio and video quality assessment (AVQA). Specifically, we construct the first UGC AVQA database named the SJTU-UAV database, which includes 520 in-the-wild UGC audio and video (A/V) sequences, and conduct a user study to obtain the mean opinion scores of the A/V sequences. The content of the SJTU-UAV database is then analyzed from both the audio and video aspects to show the database characteristics. We also design a family of AVQA models, which fuse the popular VQA methods and audio features via support vector regressor (SVR). We validate the effectiveness of the proposed models on the three databases. The experimental results show that with the help of audio signals, the VQA models can evaluate the perceptual quality more accurately. The database will be released to facilitate further research.

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Sequential generation of self-starting diverse operations in all-fiber laser based on thulium-doped fiber saturable absorber

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Chinese Physics B 2022年第6期31卷 87-90页

作者： Pei Zhang Kaharudin Dimyati Bilal Nizamani Mustafa M.Najm S.W.Harun School of Electrical and Information Engineering Huaihua UniversityHuaihua 418008China Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province Huaihua UniversityHuaihua 418008China Department of Electrical Engineering Faculty of EngineeringUniversity of MalayaKuala Lumpur 50603Malaysia Faculty of Advanced Technology and Multidiscipline Airlangga UniversitySurabaya 60115Indonesia Institute of Computer Science and Digital Innovation UCSI UniversityKuala LumpurMalaysia

Self-starting Q-switching,Q-switched mode-locking and mode-locking operation modes are achieved sequentially in an all-fiber erbium-doped fiber laser with thulium-doped fiber saturable absorber for the first *** central wavelengths of Q-switching,Q-switched mode-locking and mode-locking operation modes are 1569.7 nm,1570.9 nm,and 1572 nm,*** mode-locking operation of the proposed fiber laser generates stable dark soliton with a repetition rate of 0.99 MHz and signal-to-noise ratio of 65 *** results validate the capability of generating soliton pulse by doped fiber saturable ***,the proposed fiber laser is beneficial to the applications of optical communication and signal processing system.

关键词： all-fiber laser Q-switched mode-locking dark soliton fiber saturable absorber

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Segmentation and Recognition of Lung Adenocarcinoma Cells Based on U-Net Model 16

Segmentation and Recognition of Lung Adenocarcinoma Cells Ba...

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16th International Congress on Image and Signal processing, BioMedical engineering and Informatics, CISP-BMEI 2023

作者： Jin, Ziyang Zhang, Qing Sun, Zhen Li, Qingli Zhejiang University ZJU-UIUC Institute Department of Electrical Engineering Haining China East China Normal University Shanghai Key Laboratory of Multidimensional Information Processing Shanghai China Four Districts for Convalescence of Air Force Hangzhou Special Service Recuperation Center Nanjing China

ISBN: (纸本)9798350330755

Lung adenocarcinoma poses a great threat to human health, and early diagnosis is very important for treatment. Currently, pathologists analyze and diagnose pathological cells by observing their distribution (normal cells, hyperplasia and cancer cells). So, accurate segmentation of lung cells is very important to help pathologists make diagnosis. However, it is a heavy workload to obtain information from whole slide images by human eye observation. And with the development of deep learning, its application in medical image is increasing. We can segment and recognize cells based on this technology. U-Net model, one of the most classic segmentation models, has obtained enormous number of achievements in pathological image processing. Therefore, in this paper, we propose a segmentation model for lung adenocarcinoma cells based on U-Net model. This model is trained by synthesizing pseudo-color images generated from three bands of hyperspectral images as input. We have conducted experiments on a home-made lung adenocarcinoma dataset and the results show that this method can get precise segmentation results. © 2023 IEEE.

关键词： Diagnosis

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Crop-Guided Neural Network Segmentation of High-Resolution Skin Lesion Images 2nd

Crop-Guided Neural Network Segmentation of High-Resolution ...

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2nd International Conference on Digital Transformation in Education and Artificial Intelligence Applications, MoStart 2024

作者： Benčević, Marin Habijan, Marija Galić, Irena Faculty of Electrical Engineering Computer Science and Information Technology Osijek Josip Juraj Strossmayer University of Osijek Osijek Croatia Department of Telecommunications and Information Processing TELIN-GAIM Ghent University Ghent Belgium

ISBN: (纸本)9783031620577

Medical images are often exceedingly large in width and height, limiting the maximum batch size when training convolutional neural networks and requiring models with a large number of parameters. Typically, images are uniformly downsampled, leading to losing fine-detailed information. Instead of uniformly downsampling images, we introduce a two-stage end-to-end segmentation network utilizing image crops to reduce network input size. Initially, a uniformly downscaled image is first segmented with a rough segmentation module, and the rough segmentation is used as a saliency map to crop the original high-resolution image to a region of interest. This crop is then re-segmented with a fine segmentation module. Our method’s effectiveness is demonstrated in segmenting lesion boundaries in clinical images across two datasets. We establish that this technique maintains comparable segmentation quality to a baseline model while reducing the network input size. Furthermore, our approach enhances the robustness of segmentation outcomes with smaller input sizes, outperforming uniformly downscaled images and baseline models. This improvement is consistent in both in-sample and out-of-sample evaluations. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Crops

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Computing on Surface: A Multi-Task Multi-Access Offloading Scheme in Maritime Edge Networks

Computing on Surface: A Multi-Task Multi-Access Offloading S...

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2024 International Conference on Cloud and Network Computing, ICCNC 2024

作者： Dai, Minghui Dou, Chenglong Wu, Yuan Qian, Liping Lin, Bin Su, Zhou Shen, Xuemin Sherman University of Macau State Key Laboratory of Internet of Things for Smart City China Zhuhai UM Science and Technology Research Institute Zhuhai China Zhejiang University of Technology College of Information Engineering Hangzhou China Dalian Maritime University Department of Communication Engineering Dalian China Xi'An Jiaotong University School of Cyber Science and Engineering Xi'an China University of Waterloo Department of Electrical and Computer Engineering Waterloo Canada

ISBN: (纸本)9798350367805

The recent development of unmanned aerial vehicles (UAVs) technology has been envisioned as a promising paradigm to cater for the growing maritime activities. However, the increasing growth of marine services poses challenges for processing maritime data. In this paper, we propose a surface computing paradigm in maritime networks, in which multi-Task sensed by UAVs can be offloaded to multiple beacon stations. Multiple UAVs can process their workloads locally or offload to surface computing. Taking the system welfare and energy consumption into consideration, we present an optimization problem to determine the selection of beacon stations and the offloading decision, with the objective of maximizing the system welfare. We propose a hybrid auction and convex optimization approach to address the formulated problem. Finally, simulation results demonstrate the effectiveness of our proposed algorithms compared to several baselines. © 2024 IEEE.

关键词： Convex optimization

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Soliton Vortex Comb Generation in an AlGaAs Microresonator for Self-Torque Pulse Synthesis

Soliton Vortex Comb Generation in an AlGaAs Microresonator f...

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CLEO: Science and Innovations in CLEO 2024, CLEO: S and I 2024 - Part of Conference on Lasers and Electro-Optics

作者： Liu, Y. Chen, B. Zhou, Y. Ye, C. Cao, Q. Huang, P. Kim, C. Zheng, Y. Oxenløwe, L.K. Yvind, K. Li, J. Li, J. Zhang, Y. Dong, C. Fu, S. Zhan, Q. Wang, X. Liu, J. Pu, M. DTU Electro Department of Electrical and Photonics Engineering Technical University of Denmark Kgs. LyngbyDK-2800 Denmark State Key Laboratory of Optoelectronic Materials and Technologies School of Physics School of Electronics and Information Technology Sun Yat-sen University Guangzhou China School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai China Zhangjiang Laboratory Shanghai China CAS Key Laboratory of Quantum Information University of Science and Technology of China Hefei China Institute of Advanced Photonics Technology School of Information Engineering Guangdong University of Technology Guangzhou China Quantum Science Center of Guangdong-Hong Kong-Macao Greater Bay Area Shenzhen China

We demonstrate bright soliton generation at room temperature within a grating-dressed AlGaAs-on-insulator microresonator and the simultaneous emission of phase-locked vortices, enabling the synthesis of self-torque pu... 详细信息

关键词： Microresonators

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