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Polyp-PVT:Polyp Segmentation with Pyramid Vision Transformers

CAAI Artificial Intelligence Research 2023年第1期2卷 1-15页

作者： Bo Dong Wenhai Wang Deng-Ping Fan Jinpeng Li Huazhu Fu Ling Shao College of Computer Science Nankai UniversityTianjin 300350China Shanghai Artificial Intelligence Laboratory Shanghai 200232China Computer Vision Lab Inception Institute of Artificial IntelligenceAbu DhabiUnited Arab Emirates Institute of High Performance Computing Agency for ScienceTechnology and ResearchSingapore 138632Singapore UCAS-Terminus AI Lab Terminus GroupChongqing 400042China

Most polyp segmentation methods use convolutional neural networks(CNNs)as their backbone,leading to two key issues when exchanging information between the encoder and decoder:(1)taking into account the differences in contribution between different-level features,and(2)designing an effective mechanism for fusing these *** existing CNN-based methods,we adopt a transformer encoder,which learns more powerful and robust *** addition,considering the image acquisition influence and elusive properties of polyps,we introduce three standard modules,including a cascaded fusion module(CFM),a camouflage identification module(CIM),and a similarity aggregation module(SAM).Among these,the CFM is used to collect the semantic and location information of polyps from high-level features;the CIM is applied to capture polyp information disguised in low-level features,and the SAM extends the pixel features of the polyp area with high-level semantic position information to the entire polyp area,thereby effectively fusing cross-level *** proposed model,named Polyp-PVT,effectively suppresses noises in the features and significantly improves their expressive *** experiments on five widely adopted datasets show that the proposed model is more robust to various challenging situations(e.g.,appearance changes,small objects,and rotation)than existing representative *** proposed model is available at https://***/DengPingFan/Polyp-PVT.

关键词： polyp segmentation pyramid vision transformer colonoscopy computer vision

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Editorial

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Journal of Reliable Intelligent Environments 2022年第2期8卷 77-77页

作者： Coronato, Antonio Augusto, Juan Carlos Department of Computer Science Research Group on Development of Intelligent Environments Middlesex University London United Kingdom Institute for High Performance Computing and Networking National Research Council Naples Italy

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INDUCTIVE LIMITS OF COMPACT QUANTUM METRIC SPACES

arXiv

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arXiv 2025年

作者： Long, Botao Sadeghi, Ghadir School of Mathematics MIIT Key Laboratory of Mathematical Modelling and High Performance Computing of Air Vehicles Nanjing University of Aeronautics and Astronautics Jiangsu Nanjing211106 China Department of Mathematics and Computer Sciences Hakim Sabzevari University P. O. Box 397 Sabzevar Iran

A compact quantum metric space is a unital C∗-algebra equipped with a Lip-norm. Let {(An, Ln)} be a sequence of compact quantum metric spaces, and let φn: An → An+1 be a unital ∗-homomorphism preserving Lipschitz elements for n ≥ 1. We show that there exists a compact quantum metric space structure on the inductive limit (Formula Presented) by means of the inverse limit of the state spaces {S(An)}. We also give some sufficient conditions that two inductive limits of compact quantum metric spaces are Lipschitz *** Codes 46L85(Primary) 46L87, 58B34(Secondary) Copyright © 2025, The Authors. All rights reserved.

关键词： Inverse problems

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Improving Software Defined Network Controllers in a Multi-Vendor Environment

SSRN

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SSRN 2023年

作者： Deneke, Bereketeab Berhanu Beyene, Asrat Mulatu Haile, Endalew Ayenew Department of Computer Science School of Graduate Studies St. Mary’s University Addis Ababa Ethiopia High Performance Computing & Big Data Analytics CoE Department of Electrical and Computer Engineering Addis Ababa Science and Technology University Addis Ababa Ethiopia Adama Science and Technology University School of Electrical Engineering and Computing Electrical Power and Control Engineering Adama Ethiopia

Software Defined Networking (SDN) is an emerging networking paradigm with the potential to foster innovation through programmable networks. SDNs are characterized by the separation of control and data planes where, in a logically centralized controller, it’s possible to make routing decisions on behalf of forwarding elements. For this, there are different protocols used like Open Flow, Forward and Control Element Separation (FORCES), Path Computation Element Protocol (PCEP), Network Configuration Protocol (NETCONF), and Interface to Routing System (IRS). Border Gateway Protocol (BGP) is one such protocol that can enable the network programmability promised by SDNs. The controllers used in BGP as control plane protocol leverages RESTCONF (RFC 8040) as management plane protocol to interact with physical routers, switches, and network service firewalls. Therefore, the aim of this work is to improve the performance of SDN controllers using BGP enabling a multi-vendor environment without requiring infrastructure upgrade showcasing how interoperability can be achieved. The proposed system is implemented using OpenDaylight controllers. The performance of the prototype is evaluated using Latency, Throughput, CPU consumption, and TTL (Time to Live). Based on the simulation results it is observed that the SDN controllers that use BGP show improvements in terms of Latency and Throughput. © 2023, The Authors. All rights reserved.

关键词： Controllers

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Entirety of Quantum Uncertainty and Its Experimental Verification

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Chinese Physics Letters 2021年第7期38卷 11-16页

作者： Jie Xie Li Zhou Aonan Zhang Huichao Xu Man-Hong Yung Ping Xu Nengkun Yu Lijian Zhang National Laboratory of Solid State Microstructures College of Engineering and Applied Sciences and School of PhysicsNanjing UniversityNanjing 210093China Collaborative Innovation Center of Advanced Microstructures Nanjing UniversityNanjing 210093China Department of Computer Science and Technology Tsinghua UniversityBeijing 100084China Shenzhen Institute for Quantum Science and Engineering and Department of Physics Southern University of Science and TechnologyShenzhen 518055China Shenzhen Key Laboratory of Quantum Science and Engineering Southern University of Science and TechnologyShenzhen 518055China Institute for Quantum Information&State Key Laboratory of High Performance Computing College of ComputerNational University of Defense TechnologyChangsha 410073China Centre for Quantum Software and Information School of SoftwareFaculty of Engineering and Information TechnologyUniversity of Technology SydneyNSWAustralia

As a foundation of quantum physics,uncertainty relations describe ultimate limit for the measurement uncertainty of incompatible ***,uncertainty relations are formulated by mathematical bounds for a specific *** we present a method for geometrically characterizing uncertainty relations as an entire area of variances of the observables,ranging over all possible input *** find that for the pair of position and momentum operators,Heisenberg's uncertainty principle points exactly to the attainable area of the variances of position and ***,for finite-dimensional systems,we prove that the corresponding area is necessarily semialgebraic;in other words,this set can be represented via finite polynomial equations and inequalities,or any finite union of such *** particular,we give the analytical characterization of the areas of variances of(a)a pair of one-qubit observables and(b)a pair of projective observables for arbitrary dimension,and give the first experimental observation of such areas in a photonic system.

关键词： observable union operators

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Editorial:Special Topic on Federated Learning for IoT and Edge computing

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ZTE Communications 2022年第3期20卷 1-2页

作者： PAN Yi CUI Laizhong CAI Zhipeng LI Wei Faculty of Computer Science and Control Engineering at Shenzhen Institute of Advanced Technology Chinese Academy of SciencesChina the Academy of the United Nations Sciences and Technology Organization Ukrainian Academy of Engineering Sciences American Institute for Medical and Biological Engineering Institute of Engineering Technology the College of Computer Science and Software Engineering at Shenzhen University China Department of Computer Science and the College of Business at Georgia State University USA the Center for Distributed and High Performance Computing School of Computer ScienceThe University of Sydney the Australia-China Joint Research Center on Energy Informatics and Demand Response Technologies

Recent years have witnessed the proliferation of Internet of Things(IoT),in which billions of devices are connected to the Internet,generating an overwhelming amount of *** is challenging and infeasible to transfer an... 详细信息

关键词： cloud generating data.

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A Novel Deep Learning Approach Featuring Graph-Based Algorithm for Cell Segmentation and Tracking

A Novel Deep Learning Approach Featuring Graph-Based Algorit...

引用

2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Zhao, Keliang Niyogisubizo, Jovial Xiao, Linxia Pan, Yi Wei, Dongqing Rosiyadi, Didi Wei, Yanjie Chinese Academy of Sciences Shenzhen Key Laboratory of Intelligent Bioinformatics and Center for High Performance Computing Shenzhen Institute of Advanced Technology Shenzhen518055 China Chinese Academy of Sciences College of Computer Science and Control Engineering Shenzhen Institutes of Advanced Technology Shenzhen518055 China Shanghai Jiao Tong University State Key Laboratory of Microbial Metabolism School of Life Sciences and Biotechnology Shanghai200240 China National Research and Innovation Agency Research Center for Artificial Intelligence and Cybersecurity Bandung Indonesia

ISBN: (纸本)9798350337488

The precise segmentation and tracking of cells in microscopy image sequences play a pivotal role in biomedical research, facilitating the study of tissue, organ, and organism development. However, manual segmentation and tracking of cells is time-consuming and often require professional experiences. Besides, segmenting cells in the images with a low signal-to-noise ratio remains difficult. While deep learning (DL) has become a common method for cell segmentation, few DL- based methods address concurrent cell segmentation and tracking. In this paper, we propose a novel DL approach featuring graph-based tracking for cell segmentation and tracking in microscopy images. We combine Deeplabv3+ for semantic segmentation and ResNet50 for enhanced feature extraction, enabling comprehensive cell detection and instance segmentation. Post-processing, involving non-maxima suppression and outlier detection, refines predictions and produces final segmentation. The tracking method is based on the relative position of graph nodes to track segmented cells, encompassing cell division and apoptosis. We conduct our experiments on the induced pluripotent stem (iPS) cell datasets, and the results show that the segmentation and tracking performance of our method yields superior performance compared to the benchmark models. More specifically, our approach achieved DET values of 0.955 and 0.913, TRA values of 0.951 and 0.906, and SEG values of 0.690 and 0.665 on two iPS dataset videos, respectively. Additionally, the performance assessment encompasses four real microscopy datasets from the Cell Tracking Challenge (CTC). Our method greatly reduces the cost of manual labeling and labor-intensive costs. © 2023 IEEE.

关键词： cell segmentation cell tracking deep learning Deeplabv3+ instance segmentation iPS cell reprogramming

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$\text{MR}^{2}$-Net: Retinal OCTA Image Stitching via Multi-Scale Representation Learning and Dynamic Location Guidance

引用

IEEE Journal of Biomedical and Health Informatics 2024年第1期29卷 482-494页

作者： Haiting Mao Yuhui Ma Dan Zhang Yanda Meng Shaodong Ma Yuchuan Qiao Huazhu Fu Caifeng Shan Da Chen Yitian Zhao Jiong Zhang Laboratory of Advanced Theranostic Materials and Technology Ningbo Institute of Materials Technology and Engineering Chinese Academy of Sciences Ningbo China School of Cyber Science and Engineering Ningbo University of Technology Ningbo China Department of Computer Science University of Exeter Exeter U.K. Institution of Science and Technology for Brain-Inspired Intelligence Fudan University Shanghai China Institute of High Performance Computing (IHPC) A*STAR Singapore School of Intelligence Science and Technology Nanjing University Nanjing China Qilu University of Technology Jinan China

Optical coherence tomography angiography (OCTA) plays a crucial role in quantifying and analyzing retinal vascular diseases. However, the limited field of view (FOV) inherent in most commercial OCTA imaging systems poses a significant challenge for clinicians, restricting the possibility to analyze larger retinal regions of high resolution. Automatic stitching of OCTA scans in adjacent regions may provide a promising solution to extend the region of interest. However, commonly-used stitching algorithms face difficulties in achieving effective alignment due to noise, artifacts and dense vasculature present in OCTA images. To address these challenges, we propose a novel retinal OCTA image stitching network, named $\text{MR}^{2}$ -Net, which integrates multi-scale representation learning and dynamic location guidance. In the first stage, an image registration network with a progressive multi-resolution feature fusion is proposed to derive deep semantic information effectively. Additionally, we introduce a dynamic guidance strategy to locate the foveal avascular zone (FAZ) and constrain registration errors in overlapping vascular regions. In the second stage, an image fusion network based on multiple mask constraints and adjacent image aggregation (AIA) strategies is developed to further eliminate the artifacts in the overlapping areas of stitched images, thereby achieving precise vessel alignment. To validate the effectiveness of our method, we conduct a series of experiments on two delicately constructed datasets, i.e., OPTOVUE-OCTA and SVision-OCTA. Experimental results demonstrate that our method outperforms other image stitching methods and effectively generates high-quality wide-field OCTA images, achieving a structural similarity index (SSIM) score of 0.8264 and 0.8014 on the two datasets, respectively.

关键词： Feature extraction Image stitching Retina Image registration Convolutional codes Bioinformatics Representation learning

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Partitioned Reduction for Heterogeneous Environments

Partitioned Reduction for Heterogeneous Environments

引用

Euromicro Conference on Parallel, Distributed and Network-Based Processing

作者： Alessio De Rango Gladys Utrera Marisa Gil Xavier Martorell Andrea Giordano Donato D'Ambrosio Giuseppe Mendicino Department of Environmental Engineering (DIAm) University of Calabria Rende CS Italy Computer Architecture Department BarcelonaTECH Universitat Politècnica de Catalunya Barcelona Spain National Research Counsil (CNR) Institute of High Performance Computing (ICAR) Rende CS Italy Department of Mathematics and Computer Science (DEMACS) University of Calabria Rende CS Italy

Nowadays, performance in HPC applications focuses on MPI efficiency as the de facto message-passing library to exploit parallelism. Features such as multithread and communication and processing overlap are continuously studied to adapt to new platforms and a more significant number of processing units like GPU platforms. In this sense, recently, the MPI-4.0 standard introduced the partitioned point-to-point communication primitives to potentiate computation and communication overlapping. This paper introduces an innovative extension to MPI, specifically addressing partitioned communication for MPI-reduction primitives. Traditional reduction tasks conventionally involve processing the complete input vector following the conclusion of GPU computations. In contrast, our proposed methodology exploits message partitioning to process reduction tasks in real-time incrementally. This approach allows the system to process individual partitions of the input vector as they become available, removing the necessity to await the full completion of GPU computations before initiating the reduction. Our results demonstrate promising benefits, particularly for large message sizes. However, it is essential to acknowledge that optimizations at synchronization points remain potential bottlenecks, requiring meticulous analysis and consideration.

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Symbolic Execution of MPI Programs with One-Sided Communications

Symbolic Execution of MPI Programs with One-Sided Communicat...

引用

Asia-Pacific Conference on Software Engineering

作者： Nenghui Hu Zheng Bian Ziqi Shuai Zhenbang Chen Yufeng Zhang College of Computer National University of Defense Technology China Key Laboratory of Software Engineering for Complex Systems National University of Defense Technology China State Key Laboratory of High Performance Computing National University of Defense Technology China College of Computer Science and Electronic Engineering Hunan University Changsha China

Message-passing interface (MPI) programs are non-deterministic and challenging to ensure correctness. The introduction of one-sided communications makes the problem of non-determinism more severe for MPI programs. This paper reports our in-progress work of symbolic execution for the MPI programs with one-sided communications. Our approach can cover the non-determinism caused by the inputs, one-sided communication, and message- passing operations of MPI programs. The preliminary evaluation's results indicate the promising of our approach.

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