检索结果-内蒙古大学图书馆

International Conference on Pattern Recognition and Image Analysis (IPRIA)

作者： Hossein Motamednia Pooryaa Cheraaqee Azadeh Mansouri Ahmad Mahmoudi-Aznaveh Department of Electrical and Computer Engineering Faculty of Engineering Kharazmi University Tehran Iran High Performance Computing Laboratory School of Computer Science Institute for Research in Fundamental Sciences Tehran Iran Cyber Research Institute Shahid Beheshti University Tehran Iran

Perceptual quality assessment has always been challenging due to the difficulty in modeling the no-linear human visual system. With the diversity in the contents of multimedia signals, the conventional methods for traditional media seems no longer satisfying. One of these emerging media, is the screen content images/videos (SCINs), Containing texts and computer generated graphics, SCVs cannot be sufficiently expressed with features designed for natural sceneries. Therefore, new researches tried to devise objective quality assessment metrics, specificly for screen contents. Recently, a dataset was proposed for quality assessment of screen content videos. Since screen contents are full of structures that spread in cardinal directions, we were motivated to employ the horizontal and vertical subbands of the wavelet transform to characterize these types of visual contents. The features were incorporated in a full-reference method that showed promising results on the publicly available dataset for SCV quality assessment. The method can bo accessed via: https://***/motamedNia/QASCV.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Dual-Scale Enhanced and Cross-Generative Consistency Learning for Semi-Supervised Medical Image Segmentation

SSRN

引用

SSRN 2024年

作者： Gu, Yunqi Zhou, Tao Zhang, Yizhe Zhou, Yi He, Kelei Gong, Chen Zhu, Huafu PCA Lab The Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information Ministry of Education School of Computer Science and Engineering Nanjing University of Information Science and Technology Nanjing210094 China School of Computer Science and Engineering Southeast University Nanjing211189 China Medical School Nanjing University National Institute of Healthcare Data Science Nanjing210023 China Institute of High Performance Computing A*STAR Singapore

Medical image segmentation plays a crucial role in computer-aided diagnosis. However, existing methods heavily rely on fully supervised training, which requires a large amount of labeled data with time-consuming pixel-wise annotations. Moreover, accurately segmenting lesions poses challenges due to variations in shape, size, and location. To address these issues, we propose a novel Dual-scale Enhanced and Cross-generative consistency learning framework for semi-supervised medical image Segmentation (DEC-Seg). First, we propose a Cross-level Feature Aggregation (CFA) module that integrates cross-level adjacent layers to enhance the feature representation ability across different resolutions. To address scale variation, we present a scale-enhanced consistency constraint, which ensures consistency in the segmentation maps generated from the same input image at different scales. This constraint helps handle variations in lesion sizes and improves the robustness of the model. Furthermore, we propose a cross-generative consistency scheme, in which the original and perturbed images can be reconstructed using cross-segmentation maps. This consistency constraint allows us to mine effective feature representations and boost the segmentation performance. To produce more accurate segmentation maps, we propose a Dual-scale Complementary Fusion (DCF) module that integrates features from two scale-specific decoders operating at different scales. Extensive experimental results on polyp segmentation from colonoscopy images, skin lesion segmentation from dermoscopic images, and Brain glioma segmentation from MRI images demonstrate the effectiveness of our DEC-Seg against other state-of-the-art semi-supervised segmentation approaches. © 2024, The Authors. All rights reserved.

关键词： computer aided diagnosis

来源：评论

学校读者我要写书评

暂无评论

A Comparative Study of the Coulomb’s and Franklin’s Laws Inspired Algorithm (CFA) with Modern Evolutionary Algorithms for Numerical Optimization 1st

A Comparative Study of the Coulomb’s and Franklin’s Laws I...

引用

1st International Conference on Pervasive Knowledge and Collective Intelligence on Web and Social Media, PerSOM 2022

作者： Ghasemi, Mojtaba Zare, Mohsen Zahedi, Amir Hemmati, Rasul Abualigah, Laith Forestiero, Agostino Department of Electronics and Electrical Engineering Shiraz University of Technology Shiraz Iran Department of Electrical Engineering Faculty of Engineering Jahrom University Fras Jahrom Iran Department of Electrical and Computer Engineering Tarbiat Modares University Tehran Iran Department of Electrical and Computer Engineering Marquette University MilwaukeeWI United States Hourani Center for Applied Scientific Research Al-Ahliyya Amman University Amman Jordan Faculty of Information Technology Middle East University Amman11831 Jordan Applied Science Research Center Applied Science Private University Amman11931 Jordan School of Computer Sciences Universiti Sains Malaysia Pulau Pinang George Town11800 Malaysia Computer Science Department Prince Hussein Bin Abdullah Faculty for Information Technology Al Al-Bayt University Mafraq25113 Jordan Institute for High Performance Computing and Networking National Research Council of Italy Rende Italy

ISBN: (纸本)9783031314681

Coulomb and Franklin’s electricity laws are used in this paper to model an efficient optimization algorithm based on electric particle searches, which has been named CFA. For the CFA optimizer, the influence of electrically charged particles on each other in charged things has been predicated on the forces of attraction and repulsion. Evolutionary algorithms (EA) such as hybrid real coded genetic algorithm (RCGA) which combines the global and local search (GL-25), differential evolution (DE) with strategy adaptation (SaDE), composite DE (CoDE), the improved standard particle swarm optimization 2011 (SPSO2013) and the grouped comprehensive learning PSO (GCLPSO) are compared to the CFA optimizer for finding global solutions of seven basic benchmark functions of high dimension D = 50. (GCLPSO). Experiments have shown that the suggested CFA optimizer is quite effective and competitive for the benchmark functions. Note that the source code of the CFA algorithm is publicly available at https://***/projects/cfa, https://***/matlabcentral/fileexchange/127727-franklin-s-laws-inspired-algorithm-cfa. © 2023, ICST Institute for computer sciences, Social Informatics and Telecommunications engineering.

关键词： Charged particles

来源：评论

学校读者我要写书评

暂无评论

Preparing a commercial quantum key distribution system for certification against implementation loopholes

引用

Physical Review Applied 2024年第4期22卷 044076页

作者： Vadim Makarov Alexey Abrikosov Poompong Chaiwongkhot Aleksey K. Fedorov Anqi Huang Evgeny Kiktenko Mikhail Petrov Anastasiya Ponosova Daria Ruzhitskaya Andrey Tayduganov Daniil Trefilov Konstantin Zaitsev Skolkovo Moscow 121205 Russia Vigo Quantum Communication Center NTI Center for Quantum Communications Department of Physics Faculty of Science Institute for Quantum Computing Department of Physics and Astronomy Quantum technology foundation (Thailand) Bangkok 10110 Thailand QRate Skolkovo Moscow 143026 Russia Institute for Quantum Information & State Key Laboratory of High Performance Computing College of Computer Science and Technology Moscow 119991 Russia atlanTTic Research Center School of Telecommunication Engineering Department of Signal Theory and Communications Moscow 101000 Russia

A commercial quantum key distribution (QKD) system needs to be formally certified to enable its wide deployment. The certification should include the system’s robustness against known implementation loopholes and attacks that exploit them. Here we ready a fiber-optic QKD system for this procedure. The system has a prepare-and-measure scheme with decoy-state BB84 protocol, polarization encoding, a qubit source rate of 312.5 MHz, and is manufactured by QRate. We detail its hardware and postprocessing. We analyze the hardware for known implementation loopholes, search for possible new loopholes, and discuss countermeasures. We then amend the system design to address the highest-risk loopholes identified. We also work out technical requirements on the certification lab and outline its possible structure.

关键词： Quantum communication Quantum cryptography Quantum protocols

来源：评论

学校读者我要写书评

暂无评论

Recommender System for Social Media: Research Challenges and Future Applications

Recommender System for Social Media: Research Challenges and...

引用

First International Conference on Transdisciplinary AI (TransAI)

作者： Mouzhi Ge Giovanni Pilato Fabio Persia Daniela D'Auria Faculty of European Campus Rottal-Inn Deggendorf Institute of Technology Deggendorf Germany National Research Council of Italy Institute for High Performance Computing and Networking Palermo Italy Department of Information Engineering Computer Science and Mathematics University of L'Aquila L'Aquila Italy Faculty of Computer Science Free University of Bozen-Bolzano Bozen-Bolzano Italy

Social networks have evolved as a ubiquitous means of communication in our daily lives. Users consistently generate a large amount of data on social media platforms, which on the other hand has increased the complexity when selecting relevant social media content. Thus, recommender system has been emerged as a solution to provide personalized and user-centric media recommendations. However, social media has significantly broadened the scope of available inputs such as social sensing data and new types of social media. It not only offers new research opportunities for social media recommender systems, but also indicates that various domains may benefit from the application of social media recommender systems. Therefore, this paper conducts a comprehensive survey of state-of-the-art research between social media and recommender systems. The survey results identify a set of research challenges on how social media recommender systems can be applied in various domains such as healthcare and route planning.

关键词：

来源：评论

学校读者我要写书评

暂无评论

MediFind - A Medicine Detection Framework for Vietnamese Medical Prescription

MediFind - A Medicine Detection Framework for Vietnamese Med...

引用

Advanced computing and Analytics (ACOMPA), International Conference on

作者： Khanh Le Bao Toai Tran Hoang Cong Thu Nguyen Hoang Anh Minh Vo Duc Thanh Hoang Le Hai Nam Thoai High Performance Computing Laboratory Advanced Institute of Interdisciplinary Science and Technology Faculty of Computer Science and Engineering Ho Chi Minh City University of Technology (HCMUT) Ho Chi Minh City Vietnam Vietnam National University Ho Chi Minh City Ho Chi Minh City Vietnam

The pharmaceutical industry in Vietnam faces a significant challenge due to the time-consuming and inaccurate manual operational protocols. This results in incorrect pharmaceutical administration and antibiotic resistance, seriously affecting patient health. However, the implementation of Optical Character Recognition (OCR) can help automate the extraction of medication information from prescriptions, leading to stream-lined drug administration and reduced errors. In this study, drug misuse patterns are analyzed, a novel method for extracting medication names from Vietnamese prescriptions is introduced, and an app named “MediFind” is created to enhance accessibility. This innovative solution enhances pharmaceutical practices and streamlines drug administration.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Deviation Backfilling: A Robust Backfilling Scheme for Improving the Efficiency of Job Scheduling on high performance computing Systems

Deviation Backfilling: A Robust Backfilling Scheme for Impro...

引用

Advanced computing and Analytics (ACOMPA), International Conference on

作者： Thanh Hoang Le Hai Khang Nguyen Duy Thin Nguyen Manh Danh Mai Hoang Nam Thoai High Performance Computing Laboratory Faculty of Computer Science and Engineering Advanced Institute of Interdisciplinary Science and Technology Ho Chi Minh City University of Technology (HCMUT) Ho Chi Minh City Vietnam Vietnam National University Ho Chi Minh City Ho Chi Minh City Vietnam

The Big Data era has led to the rapid development of modern sciences. Making effective use of extremely large amounts of collected data is putting extremely urgent demands on high performance computing (HPC) systems, especially the resource allocation process, which is commonly managed by the job scheduler. Despite the potential for improved scheduling outcomes offered by modern algorithms, these systems still continue to favor the FCFS and EASY backfilling approach due to its straightforward implementation and fair resource allocation. In this paper, we propose a novel and robust backfilling scheme called Deviation Backfilling to enhance the efficiency of job scheduling on HPC systems while maintaining user fairness. Combined with the job runtime prediction method using kNN, the Deviation Backfilling uses the deviation between user estimates and system prediction as the delay threshold for the first job at the backfilling queue. Our experimental results show that Deviation Backfilling outperforms existing scheduling strategies regarding performance metrics on real-world datasets. This performance improvement also signifies the capability to motivate users to offer more accurate estimates for assisting the HPC scheduling procedures.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Health Care and Management based on Block chain and Machine Learning

Health Care and Management based on Block chain and Machine ...

引用

Artificial Intelligence and Knowledge Discovery in Concurrent engineering (ICECONF), International Conference on

作者： Ruhi Bakh VeenaNair Sarkar Jerlin Priya Lovelin Auguskani Galiveeti Poornima Monali N. Shetty Meerjumla Govind Raj Dr. Ambedkar Institute of Management Studies and Research IIHMR UNIVERSITY. Department of Nursing College Aldrab Jazan University Kingdom of Saudi Arabia. High Performance Computing Lab School of Computer Science and Information Science Presidency University Bengaluru Computer Science Engineering Fr. CRCE St. Martin's Engineering College Secunderabad Telangana

With the coming of technology, we currently have an immense measure of information accessible in each field, making it conceivable to offer responses to many issues. We will utilize machine learning and block chain technology to resolve issues with healthcare information the executives in this review. With the guide of machine learning, separating just the relevant information from the data is plausible. Using prepared calculations, this is finished. The reliability of information trade turns into a test after this information has been put away. This is where block chain technology is valuable. Block chain technology's agreement guarantees that information is credible and exchanges are secure. By putting the patient at the focal point of the healthcare framework and upgrading the security and interoperability of health information, block chain technology can possibly further develop health care organization. This article fundamentally centres around settling issues with healthcare information the board using Block chain technology and including a few urgent highlights utilizing Machine Learning. The freshest technology, block chain, offers a strong and secure groundwork. With these offices, block chain has gotten some momentum in an assortment of use areas, including the food business, store network the board, energy, government support offices, and healthcare.

关键词： Telemedicine Government Medical treatment Machine learning Medical services Knowledge discovery Blockchains

来源：评论

学校读者我要写书评

暂无评论

Entirety of Quantum Uncertainty and Its Experimental Verification

引用

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

来源：评论

学校读者我要写书评

暂无评论

Self-Knowledge Distillation from Target-Embedding AutoEncoder for Multi-label Classification

Self-Knowledge Distillation from Target-Embedding AutoEncode...

引用

IEEE International Conference on Big Knowledge (ICBK)

作者： Qizheng Pan Ming Yan Guoqi Li Jianmin Li Ying Ma College of Computer and Information Engineering Xiamen University of Technology Xiamen China Institute of High Performance Computing Agency for Science Technology and Research Singapore Institute of Automation Chinese Academy of Sciences Beijing China Faculty of Computing Harbin Institute of Technology Harbin China

Target-Embedding Autoencoder (TEA) has been successfully utilized in Multi-label Classification (MLC), where each instance is associated with multiple labels. However, most existing TEA-based approaches mainly focus on the latent space alignment in their encoding phase, ignoring the output bias induced by overfitting in the training process. To address this issue, we provide a new approach named Self-Knowledge Distillation from TEA (SKDTEA) by removing the latent space alignment of TEA-based solutions with self-knowledge distillation in a simple yet effective manner. Unlike conventional self-knowledge distillation in multi-class learning, our SKDTEA leverages self-knowledge distillation by fully exploring the relationship between label smoothing and knowledge distillation. Specifically, an auxiliary module of SKDTEA is designed for ground-truth targets reconstruction, which outputs the recovered outputs as knowledge in a learned multi-label smoothing manner. The whole distillation process provides an efficient regularization to alleviate the overfitting issue in the training process. As far as we know, we are the first attempt to introduce the self-knowledge distillation into TEA-based approaches for the MLC. Experimental results demonstrate our proposed method achieves significant superiority over the well-established approaches in MLC.

关键词： Training Smoothing methods Encoding Decoding Standards

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：