检索结果-内蒙古大学图书馆

17th Asian Conference on Computer Vision, ACCV 2024

作者： Gordon, Cameron E. MacDonald, Lachlan Saratchandran, Hemanth Lucey, Simon Australian Institute for Machine Learning University of Adelaide AdelaideSA5000 Australia Mathematical Institute for Data Science John Hopkins University BaltimoreMD21218 United States

ISBN: (纸本)9789819609628

Deep implicit functions have been found to be an effective tool for efficiently encoding all manner of natural signals. Their attractiveness stems from their ability to compactly represent signals with little to no offline training data. Instead, they leverage the implicit bias of deep networks to decouple hidden redundancies within the signal. In this paper, we explore the hypothesis that additional compression can be achieved by leveraging redundancies that exist between layers. We propose to use a novel runtime decoder-only hypernetwork – that uses no offline training data – to better exploit cross-layer parameter redundancy. Previous applications of hypernetworks with deep implicit functions have employed feed-forward encoder/decoder frameworks that rely on large offline datasets that do not generalize beyond the signals they were trained on. We instead present a strategy for the optimization of runtime deep implicit functions for single-instance signals through a Decoder-Only randomly projected Hypernetwork (D’OH). By directly changing the latent code dimension, we provide a natural way to vary the memory footprint of neural representations without the costly need for neural architecture search on a space of alternative low-rate structures. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Decoding

来源：评论

学校读者我要写书评

暂无评论

Secure Photo Sharing Across Platforms Using Blockchain Technology 4

Secure Photo Sharing Across Platforms Using Blockchain Techn...

引用

4th International Conference on Sentiment Analysis and Deep learning, ICSADL 2025

作者： Nivetha, K. Harini, M. Harshinni, V. Nivetha, N. Tamilselvan, P. M Kumarasamy College of Engineering Department of Artificial Intelligence and Data Science Karur India M Kumarasamy College of Engineering Department of Artificial Intelligence and Machine Learning Karur India

ISBN: (数字)9798331523923

ISBN: (纸本)9798331523923

With the rapid expansion of online social networks (OSNs), photo sharing has become increasingly prevalent, raising significant privacy and security concern. Existing approaches, like centralized access control mechanisms and encryption-based privacy solutions, suffer from inconsistent policy enforcement, unauthorized access risk, and lack of transparency. Moreover, traditional OSN platforms afford limited control over the dissemination of content with respect to counteracting illegal reproductions. In order to address these challenges, Photo Chain is designed. The relevance of this name derives from its concept of using a blockchain mechanism to enable photo sharing in social networks securely and in a controlled manner. The system has smart contracts for dynamic access control, PreHash for photo integrity verification, and Gaussian Blur for the protection of sensitive regions. Dissemination control also provides various ways to prevent unauthorized sharing of photos. Ethereum-based smart contracts maintain an immutable log of transactions to guarantee privacy and transparency through user-defined access policies. A functional prototype has also been developed and tested for security, privacy, and controlled dissemination of pictures through OSNs. This prototype has demonstrated the usefulness of Photo Chain. © 2025 IEEE.

关键词： Differential privacy

来源：评论

学校读者我要写书评

暂无评论

Enhancing Career Development: An AI-Driven Mentorship Platform for Student-Mentor Connections

Enhancing Career Development: An AI-Driven Mentorship Platfo...

引用

2025 IEEE International Conference on Computational, Communication and Information Technology, ICCCIT 2025

作者： Charanya, P. Nidhish, M. Prajesh, U.R. Saktheeswar, K. Pillai, Sanjana S. Sri Eshwar College of Engineering Intelligence and Machine Learning Department of Artificial Coimbatore India Sri Eshwar College of Engineering Department of Artificial Intelligence and Data Science Coimbatore India

ISBN: (纸本)9798331512965

Thunai is an AI-powered mentorship platform that connects users with personalized mentors for career guidance. Key features include automated calendar booking, video communication with privacy-enhancing dynamic emojis, and AI-driven mentor matching aligned with mentee goals. The AI assistant, GURU, supports task management, resource recommendations, and LinkedIn-based evaluations to foster growth. Thunai offers subscription plans and partnerships with educational and mental health organizations, enhancing engagement, leadership development, and networking. Leveraging AI technologies like sentiment analysis and feedback, Thunai improves mentor matching, user satisfaction, and mentee engagement for career and emotional well-being. © 2025 IEEE.

关键词： Professional aspects

来源：评论

学校读者我要写书评

暂无评论

Marine Predators Algorithm for Energy Scheduling Problem Using Renewable Energy 2

Marine Predators Algorithm for Energy Scheduling Problem Usi...

引用

2nd International Conference on Cyber Resilience, ICCR 2024

作者： Makhadmeh, Sharif Naser Abasi, Ammar Kamal Al-Betar, Mohammed Azmi University Of Petra Department Of Data Science And Artificial Intelligence Amman Jordan Machine Learning Department Abu Dhabi United Arab Emirates Ajman United Arab Emirates

ISBN: (纸本)9798350394962

The Energy Scheduling Problem (ESP) involves scheduling smart home appliances based on electricity pricing schemes. This entails adjusting the timing of operations for these appliances across different periods. The primary aim of this scheduling approach is to reduce cost and the Peak-to-Average Ratio (PAR), while enhancing user comfort. This study employs the Marine Predators Algorithm (MPA) to address ESP and derive an optimal schedule for smart home appliances. Additionally, a renewable energy source (RES) on the basis of a PV system is introduced to further optimize appliance schedules by providing a smart home with energy, particularly during peak periods. The obtained outcomes demonstrate the effectiveness of the introduced RES in reducing costs of electricity and enhancing user satisfaction. Furthermore, the performance of MPA is compared with that of the wind-driven optimization algorithm, with MPA proving superior in achieving ESP objectives. © 2024 IEEE.

关键词： Domestic appliances

来源：评论

学校读者我要写书评

暂无评论

Towards Highly Efficient Anomaly Detection for Predictive Maintenance 23

Towards Highly Efficient Anomaly Detection for Predictive Ma...

引用

23rd IEEE International Conference on machine learning and Applications, ICMLA 2024

作者： Klüttermann, Simon Peka, Vanlal Doebler, Philipp Müller, Emmanuel Tu Dortmund University Dortmund Germany Lamarr Institute for Machine Learning and Artificial Intelligence Dortmund Germany Research Center Trustworthy Data Science and Security Dortmund Germany

ISBN: (纸本)9798350374889

This paper introduces SEAN, a novel anomaly detection algorithm designed for real-time applications in predictive maintenance. SEAN leverages an ensemble-based approach to deliver competitive performance while drastically reducing computational costs. In our comprehensive evaluation across 121 datasets, SEAN consistently outperforms comparable shallow anomaly detection algorithms. Our comparisons reveal that SEAN operates over 20,000 times faster than a similar state-of-the-art deep learning alternative, with negligible sacrifice in detection accuracy. We further demonstrate SEAN's versatility through an ablation study, highlighting how its hyperparameters can be tuned to balance runtime and performance effectively. Additionally, we present a practical C++ export tool that enables the deployment of SEAN on resource-constrained devices, meeting the stringent requirements of on-device predictive maintenance tasks. Our findings underscore SEAN as a powerful and efficient solution for anomaly detection in real-world engineering applications. © 2024 IEEE.

关键词： Predictive maintenance

来源：评论

学校读者我要写书评

暂无评论

Predicting Indian Sign Language Gestures Using Deep learning and machine learning Techniques 4

Predicting Indian Sign Language Gestures Using Deep Learning...

引用

4th International Conference on Sustainable Expert Systems, ICSES 2024

作者： Fulkar, Bhushan Burle, Rushikesh Mahale, Pramod Pacaharaney, Utkrsha Datta Meghe institute of Higher Education and Research Department of Artificial intelligence And Data science Wardha India Department of Artificial Intelligence And Machine Learning Maharashtra Wardha India Datta Meghe institute of Higher Education and Research Department of Artificial Intelligence And Machine Learning Wardha India

ISBN: (纸本)9798331540364

Indian Sign Language is the language used by people with disabilities in India. Unfortunately, the general public's ignorance of sign language makes it difficult for the especially abled and the general public to communicate. We are releasing a strategy to reduce this difference. We have adopted two distinct strategies to deal with this problem. first by employing the depth+RGB data acquired with a Microsoft Kinect to make gesture predictions in real-time. To segment the hand region from the RGB-D camera data, we used affine transformation and 3D reconstruction to map the RGB and depth information. Convolutional neural networks were trained with inputs that were segmented hand images or videos. With 50 static Indian Sign Language hand gestures used for training, a 97.18% classification accuracy was achieved on test data. Furthermore, this model achieved a 97.71 % classification accuracy when we transferred learning American Sign Language. A convolutional kernel and an LSP were used to train twenty dynamic gestures. This model's classification accuracy was 98.88%. Nevertheless, as soon as we implemented this system, we found that the methodology was flawed. Essentially, it is absurd to need to carry around both a bulky Microsoft Kinect and a device capable of performing the computation required for human-to-person interaction. We attempted to address this issue by using semantic segmentation of the hands. U-Net and ResNet 101 were combined. © 2024 IEEE.

关键词： Affine transforms

来源：评论

学校读者我要写书评

暂无评论

Game-Theoretic Statistics and Safe Anytime-Valid Inference

引用

Statistical science 2023年第4期38卷 576-597页

作者： Ramdas, Aaditya Grünwald, Peter Vovk, Vladimir Shafer, Glenn Statistics and Data Science Machine Learning Carnegie Mellon University Pittsburgh 15213 PA United States Machine Learning Group Centrum Wiskunde Informatica Amsterdam Netherlands Computer Science Royal Holloway University of London United Kingdom Rutgers University Piscataway 08854-8019 NJ United States

Safe anytime-valid inference (SAVI) provides measures of statistical evidence and certainty—e-processes for testing and confidence sequences for estimation—that remain valid at all stopping times, accommodating continuous monitoring and analysis of accumulating data and optional stopping or continuation for any reason. These measures crucially rely on test martingales, which are nonnegative martingales starting at one. Since a test martingale is the wealth process of a player in a betting game, SAVI centrally employs game-theoretic intuition, language and *** summarize the SAVI goals and philosophy, and report recent advances in testing composite hypotheses and estimating functionals in nonparametric settings. © (2023) All Rights Reserved.

关键词： confidence sequence e-process nonparametric composite hypothesis testing optional stopping reverse information projection Test martingales universal inference Ville’s inequality

来源：评论

学校读者我要写书评

暂无评论

Dynamic k-Anonymity for Electronic Health Records: A Topological Framework 19th

Dynamic k-Anonymity for Electronic Health Records: A Topolo...

引用

19th International Workshop on data Privacy Management, DPM 2024, 8th International Workshop on Cryptocurrencies and Blockchain Technology, CBT 2024 and 10th Workshop on the Security of Industrial Control Systems and of Cyber-Physical Systems, CyberICPS 2024 which were held in conjunction with the 29th European Symposium on Research in Computer Security, ESORICS 2024

作者： Swaminathan, Arjhun Akgün, Mete Medical Data Privacy and Privacy Preserving Machine Learning Department of Computer Science University of Tübingen Tübingen Germany Institute for Bioinformatics and Medical Informatics Tübingen Germany

ISBN: (纸本)9783031823480

With the rapid digitization of Electronic Health Records (EHRs), fast and adaptive data anonymization methods have become increasingly important. While tools from topological data analysis (TDA) have been proposed to anonymize static datasets—allowing the creation of multiple generalizations for different anonymization needs from a single computation—the application to dynamic datasets remains unexplored. To address this, our work adapts existing methodologies to the dynamic setting. We develop an improved version of weighted persistence barcodes that track higher-dimensional holes in data, allowing us to edit persistence information on the fly. Additionally, we introduce filtration trimming, a novel technique designed to update persistence data quickly with minimal computing effort when data is added. Our work represents a significant advancement in healthcare data privacy, offering a refined approach to protecting highly sensitive and evolving patient data through dynamic k-anonymity. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Electronic health record

来源：评论

学校读者我要写书评

暂无评论

Digital Halftoning via Mixed-Order Weighted ΣΔ Modulation

Digital Halftoning via Mixed-Order Weighted ΣΔ Modulation

引用

2023 International Conference on Sampling Theory and Applications, SampTA 2023

作者： Krahmer, Felix Veselovska, Anna Technical University of Munich and Munich Center for Machine Learning Dept. of Mathematics & Munich Data Science Institute Garching/Munich Germany

ISBN: (纸本)9798350328851

In this paper, we propose 1-bit weighted Σ quantization schemes of mixed order as a technique for digital halftoning. These schemes combine weighted Σ schemes of different orders for two-dimensional signals so one can profit both from the better stability properties of low order schemes and the better accuracy properties of higher order schemes. We demonstrate that the resulting mixed-order Σ schemes in combination with a padding strategy yield improved representation quality in digital halftoning as measured in the Feature Similarity *** empirical results are complemented by mathematical error bounds for the model of two-dimensional bandlimited signals as motivated by a mathematical model of human visual perception. © 2023 IEEE.

关键词： Stability

来源：评论

学校读者我要写书评

暂无评论

System for Identifying and Avoiding Obstructions on Railway Tracks in Forest Areas 10

System for Identifying and Avoiding Obstructions on Railway ...

引用

10th International Conference on Advanced Computing and Communication Systems, ICACCS 2024

作者： Hemanthkumar, P.B. Benjamin, Ruth Moly Karunya Institute of Technology and Sciences Division of Data Science and Cyber Security Coimbatore India Karunya Institute of Technology and Sciences Division of Artificial Intelligence and Machine Learning Coimbatore India

ISBN: (纸本)9798350384369

Railways often faces the challenge of obstructions on the tracks especially passing through the forest area as not much precautions or announcements will be given to there also animals won't be able to understand the arrival of the train. Which results a significant safety risk to trains, travelling passengers and intruding creatures. This paper addresses for identifying the obstacles on railway tracks especially in forest areas which helps to take necessary actions to avoid those obstructions above. The system needs a camera, that has to be installed on the adjacent sides of the railway path which captures the real time data of the track. This captured data is then processed and analyzed to identify any potential obstruction on the tracks using Convolutional Neural Networks You Only Look Once version 8 is used. YOLOv8 is a high speed and accurate model;is trained with a custom dataset which is proposed in this paper. If any obstruction is detected it will inform to the train pilot and nearest stations for testing purpose mailing service is used which helps in taking necessary actions. With appropriate alerts will improve safety and efficiency on railway tracks in the forest areas by providing real time information about potential obstructions on the tracks. This directly helps in preventing accidents and delays. Ensures a safer and more reliable railway network. © 2024 IEEE.

关键词： Convolutional neural networks

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：