检索结果-内蒙古大学图书馆

3rd International Conference on Advance Computing and Innovative Technologies in engineering, ICACITE 2023

作者： Sathees Kumar, R. Chintamaneni, Phanikanth Kumar, Madarapu Naresh Joshi, Ankita Swathi, Bajila Dhanraj, Joshuva Arockia Jntuk University Narasaraopeta Institute of Technology Department of Cse Andhra Pradesh Narasaraopet India Department of Cse New Delhi India National Informatics Centre New Delhi India Uttaranchal University Uttaranchal Institute of Technology India Sr University School of Computer Science and Artificial Intelligence Telangana Warangal India Department of Mechatronics Engineering Padur Chennai603103 India

ISBN: (纸本)9798350399264

A serious risk to genuine organization demands is a distributed denial of service (DDoS) attack. The main DDoS attack was archived in 1996, however, from that point forward, their intricacy and refinement have consistently expanded. A 2 TBps attack on a crucial foundation, including the monetary area, was accounted for in August 2020 during the Coronavirus pandemic. In the accompanying two years, it is anticipated that the number of attacks would twofold, stretching around 15 million. Since its beginning, many relief plans have been made, however, the intricacy is rising, requiring modern arrangements in view of new innovation. A potential and common-sense method for DDoS relief is blockchain. The point of the review is to give an exhaustive examination of the fundamental and intrinsic properties of blockchain, including their decentralization, inside and outer trust lessness, unchanging nature, honesty, obscurity, and evidence, which have demonstrated to be a fantastic contender for battling this destructive cyber threat. © 2023 IEEE.

关键词： Blockchain

来源：评论

学校读者我要写书评

暂无评论

Predicting Types of Urinary Crystals and Diameter Using Image Processing Techniques and Deep Learning Models 24

Predicting Types of Urinary Crystals and Diameter Using Imag...

引用

8th International Conference on Medical and Health informatics, ICMHI 2024

作者： Huang, Yu-Ju Tseng, Yi-Shiou Chen, Tzu-Jung Chien, Ting-Ying Department of Computer Science and Engineering Yuan Ze University Taoyuan City Taiwan Department of Surgery Far Eastern Memorial Hospital Graduate Institute of Medicine Yuan Ze University Taiwan Graduate Program in Biomedical Informatics Yuan Ze University Taoyuan City Taiwan Innovation Center for Big Data and Digital Convergence Yuan Ze University Taoyuan City Taiwan

ISBN: (纸本)9798400716874

Kidney stones are primarily crystals formed from ion oversaturation in urine. Currently, the diagnosis of kidney stones involves experienced professionals manually interpreting images of urinary crystals under a microscope. In recent years, with the rapid development of artificial intelligence (AI), many researchers have proposed various methods to assist in diagnosis, hoping to improve medical quality. This study explored the application of AI in the medical field, aiming to automate the interpretation of urinary crystal images, such as red blood corpuscles (RBCs), calcium oxalate monohydrate (COM), calcium oxalate dihydrate octahedron (COD-OCT), calcium oxalate dihydrate dodecahedron (COD-DOD), debris, and others, and to use image processing techniques to classify urinary crystal types. This research is expected to assist medical personnel in quickly determining the categories of urinary crystals. Ultimately, our model achieved an F1-score of 0.93, indicating that this architecture has significant potential. © 2024 Copyright ACM.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

LISD: AN EFFICIENT MULTI-TASK LEARNING FRAMEWORK FOR LIDAR SEGMENTATION AND DETECTION

arXiv

引用

arXiv 2024年

作者： Xu, Jiahua Zuo, Si Wei, Chenfeng Zhou, Wei Wuxi Intelligent Control Research Institute Hunan University China College of Mechanical and Vehicle Engineering Hunan University China School of Computer Science and Informatics Cardiff University United Kingdom

With the rapid proliferation of autonomous driving, there has been a heightened focus on the research of lidar-based 3D semantic segmentation and object detection methodologies, aiming to ensure the safety of traffic participants. In recent decades, learning-based approaches have emerged, demonstrating remarkable performance gains in comparison to conventional algorithms. However, the segmentation and detection tasks have traditionally been examined in isolation to achieve the best precision. To this end, we propose an efficient multi-task learning framework named LiSD which can address both segmentation and detection tasks, aiming to optimize the overall performance. Our proposed LiSD is a voxel-based encoder-decoder framework that contains a hierarchical feature collaboration module and a holistic information aggregation module. Different integration methods are adopted to keep sparsity in segmentation while densifying features for query initialization in detection. Besides, cross-task information is utilized in an instance-aware refinement module to obtain more accurate predictions. Experimental results on the nuScenes dataset and Waymo Open Dataset demonstrate the effectiveness of our proposed model. It is worth noting that LiSD achieves the state-of-the-art performance of 83.3% mIoU on the nuScenes segmentation benchmark for lidar-only methods. © 2024, CC BY.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

Interpolating and Forecasting Wound Trajectory using Machine Learning Approaches

Interpolating and Forecasting Wound Trajectory using Machine...

引用

Annual IEEE Symposium on computer-Based Medical Systems

作者： Atika Rahman Paddo Shikhar Shukla Shomita S. Steiner Saptarshi Purkayastha Chandan K. Sen Electrical and Computer Engineering Purdue University Indianapolis Indianapolis USA BioHealth Informatics Indiana University Indianapolis Indianapolis USA McGowan Institute for Regenerative Medicine University of Pittsburgh Pittsburgh USA

ISBN: (数字)9798350384727

ISBN: (纸本)9798350384734

Chronic wound treatment and management heavily rely on accurate patient outcome predictions. As chronic wounds become increasingly prevalent in many US states, it’s crucial to accurately predict and classify wound progress for timely and effective clinical intervention. The trajectory and outcomes of wounds inform multiple aspects of care, from estimating healing times to understanding disparities in treatment quality and outcomes. For accurate predictions, robust time-series forecast models are required, necessitating comprehensive and consistent wound data. Yet, much of this data is frequently marred by gaps and inaccuracies. In this work, we combined two approaches to overcome this challenge: filling in missing clinical data and forecasting wound healing trajectories. We employed various interpolation techniques, time series, and machine-learning models, including Holt-Winters, ARIMA, Prophet, LSTM, and BiLSTM. Our study assessed 14,571 wounds from 6,171 patients over a five-year span, post-data imputation and interpolation. We introduced a novel approach to firstly impute missing data using XGBoost and then choose the best interpolation method for absent wound data, ensuring precise forecasting without distorting the dataset’s demographic makeup. Data for this research was sourced from four wound centers in Indiana and eight research studies, focusing on a diverse range of wound-related demographics, clinical, and omics data. This comprehensive approach enhances wound trajectory predictions, providing clinicians with valuable insights to formulate personalized treatment plans for both individual patients and demographic groups. This will aid clinicians in better understanding wound healing trends and crafting targeted treatment strategies.

关键词： Interpolation Accuracy Time series analysis Machine learning Medical services Wounds Predictive models

来源：评论

学校读者我要写书评

暂无评论

Contributing Dimension Structure of Deep Feature for Coreset Selection

arXiv

引用

arXiv 2024年

作者： Wan, Zhijing Wang, Zhixiang Wang, Yuran Wang, Zheng Zhu, Hongyuan Satoh, Shinichi National Engineering Research Center for Multimedia Software Institute of Artificial Intelligence School of Computer Science Wuhan University China Hubei Key Laboratory of Multimedia and Network Communication Engineering China The University of Tokyo Japan National Institute of Informatics Japan A*STAR Singapore

Coreset selection seeks to choose a subset of crucial training samples for efficient learning. It has gained traction in deep learning, particularly with the surge in training dataset sizes. Sample selection hinges on two main aspects: a sample's representation in enhancing performance and the role of sample diversity in averting overfitting. Existing methods typically measure both the representation and diversity of data based on similarity metrics, such as L2-norm. They have capably tackled representation via distribution matching guided by the similarities of features, gradients, or other information between data. However, the results of effectively diverse sample selection are mired in sub-optimality. This is because the similarity metrics usually simply aggregate dimension similarities without acknowledging disparities among the dimensions that significantly contribute to the final similarity. As a result, they fall short of adequately capturing diversity. To address this, we propose a feature-based diversity constraint, compelling the chosen subset to exhibit maximum diversity. Our key lies in the introduction of a novel Contributing Dimension Structure (CDS) metric. Different from similarity metrics that measure the overall similarity of high-dimensional features, our CDS metric considers not only the reduction of redundancy in feature dimensions, but also the difference between dimensions that contribute significantly to the final similarity. We reveal that existing methods tend to favor samples with similar CDS, leading to a reduced variety of CDS types within the coreset and subsequently hindering model performance. In response, we enhance the performance of five classical selection methods by integrating the CDS constraint. Our experiments on three datasets demonstrate the general effectiveness of the proposed method in boosting existing methods. Copyright © 2024, The Authors. All rights reserved.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

Absolute Pose from One or Two Scaled and Oriented Features

Absolute Pose from One or Two Scaled and Oriented Features

引用

Conference on computer Vision and Pattern Recognition (CVPR)

作者： Jonathan Ventura Zuzana Kukelova Torsten Sattler Dániel Baráth Department of Computer Science & Software Engineering Cal Poly San Luis Obispo Faculty of Electrical Engineering Visual Recognition Group Czech Technical University in Prague Czech Institute of Informatics Robotics and Cybernetics Czech Technical University in Prague Department of Computer Science Computer Vision and Geometry Group ETH Zürich

ISBN: (数字)9798350353006

ISBN: (纸本)9798350353013

Keypoints used for image matching often include an estimate of the feature scale and orientation. While recent work has demonstrated the advantages of using feature scales and orientations for relative pose estimation, relatively little work has considered their use for absolute pose estimation. We introduce minimal solutions for absolute pose from two oriented feature correspondences in the general case, or one scaled and oriented correspondence given a known vertical direction. Nowadays, assuming a known direction is not particularly restrictive as modern consumer devices, such as smartphones or drones, are equipped with Inertial Measurement Units (IMU) that provide the gravity direction by default. Compared to traditional absolute pose methods requiring three point correspondences, our solvers need a smaller minimal sample, reducing the cost and complexity of robust estimation. Evaluations on large-scale and public real datasets demonstrate the advantage of our methods for fast and accurate localization in challenging conditions. Code is available at https://***/danini/absolute-pose-from-oriented-and-sealed-features.

关键词： Location awareness Accuracy Simultaneous localization and mapping Measurement units Pose estimation Noise Inertial navigation

来源：评论

学校读者我要写书评

暂无评论

Sparse Complementary Pairs with Additional Aperiodic ZCZ Property

Sparse Complementary Pairs with Additional Aperiodic ZCZ Pro...

引用

IEEE International Symposium on Information Theory

作者： Cheng-Yu Pai Zilong Liu Chunlei Li Chao-Yu Chen Department of Engineering Science National Cheng Kung University Taiwan School of Computer Science and Electronic Engineering University of Essex UK Department of Informatics University of Bergen Norway Department of Electrical Engineering and Institute of Computer and Communication Engineering National Cheng Kung University Taiwan

This paper presents a novel class of complex-valued sparse complementary pairs (SCPs), each consisting of a number of zero values and with additional zero-correlation zone (ZCZ) property for the aperiodic autocorrelations and crosscorrelations of the two constituent sequences. Direct constructions of SCPs and their mutually-orthogonal mates based on restricted generalized Boolean functions are proposed. It is shown that such SCPs exist with arbitrary lengths and controllable sparsity levels, making them a disruptive sequence candidate for modern low-complexity, low-latency, and low-storage signal processing applications.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Feasibility of direct quantum communications between the UK and Ireland via 224 km of underwater fibre

Feasibility of direct quantum communications between the UK ...

引用

British and Irish Conference on Optics and Photonics, BICOP 2023

作者： Amies-Kin, Ben Schatz, Karolina P. Duan, Haofan Biswas, Ayan Bailey, Jack Felvinti, Adrian Winward, Jaimes Dixon, Mike Minder, Mariella Kumar, Rupesh Albosh, Sophie Lucamarini, Marco School of Physics Engineering and Technology York Centre for Quantum Technologies Institute for Safe Autonomy University of York YorkYO10 5FT United Kingdom EuNetworks Fiber UK Limited 5 Churchill Place LondonE14 5HU United Kingdom Department of Electrical Engineering Computer Engineering and Informatics Cyprus University of Technology Limassol3036 Cyprus

Quantum key distribution is required for unconditionally secure communications against an eavesdropper with a powerful quantum computer. We present the first QKD feasibility study over long-haul submarine fibre, betwe... 详细信息

关键词： Quantum cryptography

来源：评论

学校读者我要写书评

暂无评论

Characterizing Continual Learning Scenarios and Strategies for Audio Analysis

arXiv

引用

arXiv 2024年

作者： Bhatt, Ruchi Kumari, Pratibha Mahapatra, Dwarikanath Saddik, Abdulmotaleb El Saini, Mukesh The Department of Computer Science & Engineering Indian Institute of Technology Punjab Ropar India The Faculty of Informatics and Data Science University of Regensburg Regensburg Germany Inception Institute of AI Abu Dhabi United Arab Emirates Abu Dhabi United Arab Emirates School of Electrical Engineering and Computer Science University of Ottawa Canada The Department of Computer Science & Engineering Indian Institute of Technology Punjab Ropar India Abu Dhabi United Arab Emirates

Audio analysis is useful in many application scenarios. The state-of-the-art audio analysis approaches assume that the data distribution at training and deployment time will be the same. However, due to various real-life environmental factors, the data may encounter drift in its distribution or can encounter new classes in the late future. Thus, a one-time trained model might not perform adequately. In this paper, we characterize continual learning (CL) approaches in audio analysis. In this paper, we characterize continual learning (CL) approaches, intended to tackle catastrophic forgetting arising due to drifts. As there is no CL dataset for audio analysis, we use DCASE 2020 to 2023 datasets to create various CL scenarios for audio-based monitoring tasks. We have investigated the following CL and non-CL approaches: EWC, LwF, SI, GEM, A-GEM, GDumb, Replay, Naive, cumulative, and joint training. The study is very beneficial for researchers and practitioners working in the area of audio analysis for developing adaptive models. We observed that Replay achieved better results than other methods in the DCASE challenge data. It achieved an accuracy of 70.12% for the domain incremental scenario and an accuracy of 96.98% for the class incremental scenario. Copyright © 2024, The Authors. All rights reserved.

关键词： Machine learning

来源：评论

学校读者我要写书评

暂无评论

Resilient Routing Table Computation Based on Connectivity Preserving Graph Sequences

Resilient Routing Table Computation Based on Connectivity Pr...

引用

IEEE Annual Joint Conference: INFOCOM, IEEE computer and Communications Societies

作者： János Tapolcai Péter Babarczi Pin-Han Ho Lajos Rónyai Department of Telecommunications and Media Informatics Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Budapest Hungary Deptartment of Electrical and Computer Engineering University of Waterloo Canada Eötvös Loránd Research Network and Department of Algebra Institute for Computer Science and Control Institute of Mathematics Budapest University of Technology and Economics Budapest Hungary

Fast reroute (FRR) mechanisms that can instantly handle network failures in the data plane are gaining attention in packet-switched networks. In FRR no notification messages are required as the nodes adjacent to the failure are prepared with a routing table such that the packets are re-routed only based on local information. However, designing the routing algorithm for FRR is challenging because the number of possible sets of failed network links and nodes can be extremely high, while the algorithm should keep track of which nodes are aware of the failure. In this paper, we propose a generic algorithmic framework that combines the benefits of Integer Linear Programming (ILP) and an effective approach from graph theory related to constructive graph characterization of k-connected graphs, i.e., edge splitting-off. We illustrate these benefits through arborescence design for FRR and show that (i) due to the ILP we have great flexibility in defining the routing problem, while (ii) the problem can still be solved very fast. We demonstrate through simulations that our framework outperforms state-of-the-art FRR mechanisms and provides better resilience with shorter paths in the arborescences.

关键词：

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：