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检索条件"任意字段=11th International Conference on Intelligent Data Engineering and Automated Learning"

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Application of intelligent Image Technology in River and Coastal engineering Research 11th

Application of Intelligent Image Technology in River and Coa...

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11th international conference on Asian and Pacific Coasts, APAC 2023

作者： Chen, Cheng Wang, Yanhong Li, Ziyang Yufang, Han Huang, Hailong Zhou, Liangping Zhao, Riming Miu, Zhanghua State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering Nanjing Hydraulic Research Institute Nanjing China

ISBN: (纸本)9789819974085

Flow data are key information for river and coastal engineering research. In this paper, an intelligent large-scale particle image velocimetry (LSPIV) system was developed to measure flow field for large physical model test of river and coastal engineering. the LSPIV system was successfully applied to study the impact of hydrodynamic forces on coastal engineering in Shenzhen Bay of China and show good results. Based on the LSPIV system, this paper presents an unmanned aerial vehicle (UAV)-based PIV method for measuring flow field around engineering. A self-calibration method based on UAV RTK (real-time kinematic) is used to calibrate the relationship between image coordinates and world coordinates. the UAV-based PIV system can solve the measurement problem of the surface flow field of flood discharge in river. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Flow fields

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APPROXIMATE VANISHING IDEAL COMPUTATIONS AT SCALE 11

APPROXIMATE VANISHING IDEAL COMPUTATIONS AT SCALE

引用

11th international conference on learning Representations, ICLR 2023

作者： Wirth, Elias Kera, Hiroshi Pokutta, Sebastian Institute of Mathematics Berlin Institute of Technology Berlin Germany Graduate School of Engineering Chiba University Chiba Japan Institute of Mathematics & AI in Society Science and Technology Berlin Institute of Technology Zuse Institute Berlin Berlin Germany

the vanishing ideal of a set of points X = {x1, ..., xm} ⊆ Rn is the set of polynomials that evaluate to 0 over all points x ∈ X and admits an efficient representation by a finite subset of *** practice, to accommodate noise in the data, algorithms that construct generators of the approximate vanishing ideal are widely studied but their computational complexities remain *** this paper, we scale up the oracle approximate vanishing ideal algorithm (OAVI), the only generator-constructing algorithm with known learning *** prove that the computational complexity of OAVI is not superlinear, as previously claimed, but linear in the number of samples *** addition, we propose two modifications that accelerate OAVI's training time: Our analysis reveals that replacing the pairwise conditional gradients algorithm, one of the solvers used in OAVI, with the faster blended pairwise conditional gradients algorithm leads to an exponential speed-up in the number of features ***, using a new inverse Hessian boosting approach, intermediate convex optimization problems can be solved almost instantly, improving OAVI's training time by multiple orders of magnitude in a variety of numerical experiments. © 2023 11th international conference on learning Representations, ICLR 2023. All rights reserved.

关键词： Computational complexity

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Breast Cancer Detection with Optimized Machine-learning Techniques 8th

Breast Cancer Detection with Optimized Machine-Learning Tech...

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8th international conference on Information and Communication Technology for intelligent Systems, ICTIS 2024

作者： Shahapurkar, Vyankatesh Dhamdhere, Vidya Ansari, Nahista G H Raisoni College of Engineering and Management Pune India

ISBN: (纸本)9789819766802

Breast cancer, ranking as the second-leading cause of cancer-related deaths in women globally, necessitates swift detection and advanced treatment strategies to mitigate its high mortality rate. this research explores the fusion of machine learning and image analysis techniques for early breast cancer detection using blood analysis data. the study introduces a novel approach by converting numerical blood analysis data into image data, significantly enhancing classification accuracy. Employing popular Convolutional Neural Network (CNN) models, namely AlexNet, ResNet50, and DenseNet201, the research achieves a superior classification accuracy of 95.33% with ResNet50. this surpasses existing studies using similar data and establishes the effectiveness of the proposed methodology. Furthermore, the conversion of numerical blood analysis images into image data represents a pioneering strategy. this research underscores the critical role of automated systems in breast cancer detection and emphasizes the potential for improved outcomes through early diagnosis. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Lung cancer

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DFLOW: learning TO SYNthESIZE BETTER OPTICAL FLOW dataSETS VIA A DIFFERENTIABLE PIPELINE 11

DFLOW: LEARNING TO SYNTHESIZE BETTER OPTICAL FLOW DATASETS V...

引用

11th international conference on learning Representations, ICLR 2023

作者： Byung-Ki, Kwon Hyeon-Woo, Nam Kim, Ji-Yun Oh, Tae-Hyun Department of Electrical Engineering POSTECH Korea Republic of Graduate School of AI POSTECH Korea Republic of Institute for Convergence Research and Education in Advanced Technology Yonsei University Korea Republic of

Comprehensive studies of synthetic optical flow datasets have attempted to reveal what properties lead to accuracy improvement in learning-based optical flow estimation. However, manually identifying and verifying the properties that contribute to accurate optical flow estimation require large-scale trial-and-error experiments with iteratively generating whole synthetic datasets and training on them, i.e., impractical. To address this challenge, we propose a differentiable optical flow data generation pipeline and a loss function to drive the pipeline, called DFlow. DFlow efficiently synthesizes a dataset effective for a target domain without the need for cumbersome try-and-errors. this favorable property is achieved by proposing an efficient dataset comparison method that uses neural networks to approximately encode each dataset and compares the proxy networks instead of explicitly comparing datasets in a pairwise way. Our experiments show the competitive performance of our DFlow against the prior arts in pre-training. Furthermore, compared to competing datasets, DFlow achieves the best fine-tuning performance on the Sintel public benchmark with RAFT. © 2023 11th international conference on learning Representations, ICLR 2023. All rights reserved.

关键词： Pipelines

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A Geospatial data and Model Hub for Online Geospatial Analysis 11

A Geospatial Data and Model Hub for Online Geospatial Analys...

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11th international conference on Agro-Geoinformatics, Agro-Geoinformatics 2023

作者： Deng, Haipeng Yue, Peng Yu, Dayu Cao, Zhipeng Liu, Ruixiang Wang, Kaixuan Wuhan University School of Remote Sensing and Information Engineering Wuhan China Wuhan University Hubei Province Engineering Center for Intelligent Geoprocessing Wuhan China

ISBN: (纸本)9798350303513

In recent years, the availability of online geospatial analysis tools has increased, allowing users to access and manipulate large geospatial datasets and perform complex analyses through Web-based interfaces. It is still a challenge on how to manage geospatial resources including data and analysis functions in a distributed infrastructure. To address this issue, the study proposes a geospatial data and model hub approach for online geospatial analysis. Two core components, named the data Center and the Model Center, are involved. the data Center serves as a data hub for integrating, storing, and sharing geospatial datasets and metadata. It employs Cloud-optimized GeoTIFF (COG) and GeoCube for efficient handling of cloud-based data organization. the Model Center as a model hub focuses on the registration and sharing of geospatial analysis models, facilitating collaboration and interoperability among models. Both components are integrated into an online cloud-based geoprocessing platform, named the Open Geospatial Engine (OGE). the applicability is demonstrated through a case study involving the discovery, access, and manipulation of large datasets and models. © 2023 IEEE.

关键词： Interoperability

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MINIMUM VARIANCE UNBIASED N:M SPARSITY FOR thE NEURAL GRADIENTS 11

MINIMUM VARIANCE UNBIASED N:M SPARSITY FOR THE NEURAL GRADIE...

引用

11th international conference on learning Representations, ICLR 2023

作者： Chmiel, Brian Hubara, Itay Banner, Ron Soudry, Daniel Habana Labs An Intel company Caesarea Israel Department of Electrical Engineering Technion Haifa Israel

In deep learning, fine-grained N:M sparsity reduces the data footprint and bandwidth of a General Matrix multiply (GEMM) up to x2, and doubles throughput by skipping computation of zero values. So far, it was mainly only used to prune weights to accelerate the forward and backward phases. We examine how this method can be used also for the neural gradients (i.e., loss gradients with respect to the intermediate neural layer outputs). To this end, we first establish a tensor-level optimality criteria. Previous works aimed to minimize the mean-square-error (MSE) of each pruned block. We show that while minimization of the MSE works fine for pruning the weights and activations, it catastrophically fails for the neural gradients. Instead, we show that accurate pruning of the neural gradients requires an unbiased minimum-variance pruning mask. We design such specialized masks, and find that in most cases, 1:2 sparsity is sufficient for training, and 2:4 sparsity is usually enough when this is not the case. Further, we suggest combining several such methods together in order to potentially speed up training even more. A reference implementation is supplied in the supplementary material. © 2023 11th international conference on learning Representations, ICLR 2023. All rights reserved.

关键词： Mean square error

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Design and Implementation of intelligent Algorithm Optimization Network Access Control Strategy in SDN Architecture 11th

Design and Implementation of Intelligent Algorithm Optimizat...

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11th international conference on Applications and Techniques in Cyber Intelligence, ATCI 2023

作者： Luo, Jianbo Chengdu Neusoft University Sichuan Dujiangyan China

With the rapid progress of network technology, intelligence and virtualization have become the trend. People pay more and more attention to artificial intelligence, and the user behavior information analysis and reasoning function based on IPC and machine learning algorithm is widely used in computer applications. Traditional SDN algorithms may encounter performance bottlenecks when dealing with large-scale networks, resulting in the inability to continue to expand the network scale. this limits applications in complex network environments such as large enterprises or cloud data centers. Based on SDN architecture, this paper proposes a new intelligent optimized web crawler system, which covers user access control strategy. the research focuses on improving the IP address mapping capability, and verifies the characteristics of different node-level permissions with examples. the experimental results show that the resource utilization of the traditional algorithm is 75%, 80%, 70%, 85% and 78%, while the resource utilization of the SDN routing algorithm is above 79%, which is less than 10% higher than the traditional one. It can be seen that the intelligent algorithm shows a higher utilization of the five resources. © 2024 the Authors. Published by Elsevier B.V.

关键词： Control Strategy intelligent Algorithm Network Access SDN Architecture

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A Modular Detection System for Smart Cities: Integrating Monocular and LiDAR Solutions for Scalable Traffic Monitoring 11

A Modular Detection System for Smart Cities: Integrating Mon...

引用

11th international conference on Vehicle Technology and intelligent Transport Systems, VEHITS 2025

作者： Borau-Bernad, Javier Ramajo-Ballester, Álvaro María Armingol Moreno, José Sanchis de Miguel, Araceli Intelligent Systems Lab University Carlos III of Madrid Av. de la Universidad 30 Leganés Madrid28911 Spain Control Learning and Systems Optimization Group University Carlos III of Madrid Av. de la Universidad 30 Leganés Madrid28911 Spain

ISBN: (纸本)9789897587450

As smart cities continue to develop, they require scalable and efficient traffic monitoring systems. this paper presents a modular detection system that switches between monocular and multimodal modes, depending on the available sensors. the monocular mode, based on the MonoLSS algorithm, offers a cost-effective vehicle detection solution using a single camera, ideal for simpler or low-budget setups. In contrast, the multimodal mode integrates camera and LiDAR data via the MVX-Net model, enhancing 3D accuracy in complex traffic scenarios. this dual-mode flexibility allows smart cities to adapt the system to their infrastructure and budgetary needs, ensuring scalability as urban demands evolve. Inference results demonstrate the superior accuracy of the multimodal approach in challenging environments while validating the efficiency of the monocular mode for simpler settings. therefore, the modular detection system offers a flexible solution that optimizes both cost and performance, effectively addressing the varied requirements of smart city traffic management. Copyright © 2025 by SCITEPRESS - Science and Technology Publications, Lda.

关键词： Budget control

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7th international Russian Automation conference, RusAutoCon 2024

7th International Russian Automation Conference, RusAutoCon ...

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7th international Russian Automation conference, RusAutoCon 2024

ISBN: (纸本)9783031824937

the proceedings contain 37 papers. the special focus in this conference is on Russian Automation. the topics include: Mapping and Path Planning Methods for Highly automated Vehicles in Agriculture;morphological Analysis and Synthesis Features of Technological Processes;a Modern Method of Wireless Control of Unguarded Railway Crossings;duties and Obligations of the Railway Staff Concerned When the Microprocessorized Contactless Controlling Gauge Device Signal Is Triggered;integration of automated Management Systems for Enterprises’ Transport and Technical Services;development of an Automation Module for Planning Trajectories for Painting Aircraft Fuselage Elements;identification of Metal Sheets in the Flow, Based on the Marking Imprint, Using Neural Networks;study of the Performance of Adaptive Sensor Networks for Collecting and Processing thermoelectric data;development and Research of a Cartographic Model for Municipal Planning as the Basis of an intelligent Geoinformation System;BIM Visual Programming of Bionic Architecture Construction Using Dynamo and Revit;development of a Model and Algorithms for Trigger Control of Technological Processes of Resource Provision;system for Statistical Assessment of Means of Controlling Engineers’ Qualification for Information Support to Manage the Recruiting Process in Industry;smart Enumeration Technology;comparative Analysis of C-Band Conical Horn Antenna Sparse Structures Characteristics at Different Frequencies;software Implementation of Heuristic Methods of Optimization and Integration into a Cloud Service;computer System for Modeling Fluid Flow Around Bodies and Its Potential in Industry;the Effect of Regular and Irregular Segmentations on Characteristics and Charge Distribution Densities of Microstrip Lines;reinforcement learning with External Teacher for Building Energy Management.

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Business Process Redesign of Sales Monitoring Business Process Management to be a Smart Logistic Shipment Company 5

Business Process Redesign of Sales Monitoring Business Proce...

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5th international conference on Advancement in data Science, E-learning and Information Systems, ICADEIS 2023

作者： Firdaus, Taufiq Maulana Fajri, Hanif Fakhrurroja, Hanif Telkom University School of Industrial and System Engineering Bandung Indonesia Telkom University National Research and Innovation Agency School of Industrial Engineering Bandung Indonesia

ISBN: (纸本)9798350303414

the sales process in every company is important. therefore, every sales record must be stored in an integrated database so that tracking sales records is easy. However, there are still many sales recording practices that are still done manually, making the process of recording sales complicated and time-consuming. therefore, it needs a sales record automation process that can track all sales recording processes that provide standardization in the form of KPIs and progress at each stage of sales records. With the growth of smart logistics, it can drastically change the business process of dashboard monitoring in a logistics company. With the smart logistic concepts and the use of business process redesign methodology, it resulted in a more simplified yet integrated automated sales monitoring system. © 2023 IEEE.

关键词： Standardization

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