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Colored ICP: Advancing 2D to 3D Shape Registration for Enhanced Accuracy and Visualization 23

Colored ICP: Advancing 2D to 3D Shape Registration for Enhan...

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proceedings of the 7th international conference on algorithms, computing and systems

作者： Alexandros Vrochidis Stelios Krinidis Dimitrios Tzovaras Information Technologies Institute Center for Research and Technology Hellas Greece and Department of Management Science & Technology International Hellenic University Greece Information Technologies Institute Center for Research and Technology Hellas Greece

ISBN: (纸本)9798400709098

Robust and accurate registration is a fundamental capability for numerous computer vision and robotics applications. this paper proposes a novel colored 2D to 3D registration method that exploits keypoints from Scale-Invariant Feature Transform (SIFT) and Intrinsic Shape Signatures (ISS). the proposed method works on multiple models without utilizing a neural network or requiring a training dataset. After detecting keypoints and their colors in the L*a*b* color space, a modified Iterative Closest Point (ICP) algorithm is utilized to find the correspondences between the image and 3D model points and the transformation matrix. Additionally, there is an experimental evaluation using publicly available colored models for 3D-3D and 2D-3D registration to show that color information can increase accuracy in both tasks. On 3D-3D registration, the use of color information decreased Relative Root Mean Square Error (RRMSE) by 85.69% when the k-d tree was used and 92.63% when color was utilized in combination with the geometric information. For the 2D-3D registration, the mean distance decreased by 25.52% for the k-d tree and 28.76% for the weighted colored ICP, proving that color can efficiently enhance accuracy in this task.

关键词： Colored 2D to 3D Registration Colored ICP Point Cloud Registration Shape Alignment

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7th international conference on Geoinformatics in Sustainable Ecosystem and Society, GSES 2019, and 1st international conference on Geospatial Artificial Intelligence for Urban computing, GeoAI 2019

7th International Conference on Geoinformatics in Sustainabl...

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7th international conference on Geoinformatics in Sustainable Ecosystem and Society, GSES 2019, and 1st international conference on Geospatial Artificial Intelligence for Urban computing, GeoAI 2019

ISBN: (纸本)9789811561054

the proceedings contain 32 papers. the special focus in this conference is on Geoinformatics in Sustainable Ecosystem and Society. the topics include: Spatialization Method of Atmospheric Quality Public Opinion Based on Natural Language Processing;Extension and Expression of OWL Modeling Primitives Based on Spatio-Temporal Ontology of Ocean Flow Field;research on Domain Ontology Modeling and Formal Expression of Ocean Flow Field;study on Space-Time Development of Urban Areas in Shenyang Using Landsat Remote Sensing Data;ecological Environment Evaluation of Liuxi River Basin During Rapid Urbanization;analysis of Urban Greenness Landscape and Its Spatial Association with Urbanization and Climate Changes;urban-Expansion Driven Farmland Loss Follows with the Environmental Kuznets Curve Hypothesis: Evidence from Temporal Analysis in Beijing, China;investigating Evolutions of Metro Station Functions in Shenzhen with Long-Term Smart Card Data;spatio-Temporal Evolution of Environmental Efficiency of Construction Land in Yangtze River Economic Zone;analysis of Potential Factors Influencing Ground-Level Ozone Concentrations in Chinese Cities;spectral Characteristics and Model Inversion of Common Greening Plants in Guangzhou Under Dust Pollution;analysis of Landscape Pattern Spatial Scale in Middle and Upper Reaches of Meijiang River Basin;Design of Distribution Network Pre-planning System Based on GIS;Validation and Comparison Among Different VIIRS Cloud Mask Products;a Semi-supervised Regression Method Based on Geography Weighted Regression Model;quality Evaluation of Sea Level Height Data of Jason-3 Satellite Based on Jason-2;evaluating Spatial Details of Luojia-1 Night-Time Images Using Road Network Analysis;preface;evaluation on Suitability of Oil and Gas Zoning in Nansha Sea.

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Multiple Regression and K-Nearest-Neighbor Based Algorithm for Estimating Missing Values within Sensor 7

Multiple Regression and K-Nearest-Neighbor Based Algorithm f...

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7th Annual international conference on Network and Information systems for Computers, ICNISC 2021

作者： Li, Xiantong Sui, Yuan School of Transportation Science and Engineering Harbin Institute of Technology Harbin China Beijing-Dublin International College Beijing University of Technology Beijing China

ISBN: (纸本)9781665402323

the missing of sensor data is unavoidable when sensors are using to monitor in a system. this missing has very big effecting on the applications of sensor itself. When missing occurred, the best method is to estimate a value as closest as possible to replace it. An algorithm, named KMRA (K-Nearest-Neighbor on Multiple Regression Algorithm), builds on K nearest neighbor and multiple regression is introduced in this paper. In the process of estimation, it considers both spatial correlations from its neighbor sensor and temporal correlations from its own time serials. After computed these two correlations, the algorithm combines them into a unified estimation to be the monitored value. As algorithm KMRA counted both spatial and temporal correlations, it reaches a high efficiency and practicability in performance. the examination results show that KMRA in this paper can estimate the missing data precisely. © 2021 IEEE.

关键词： Sensor networks

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19th international Colloquium on theoretical Aspects of computing, ICTAC 2022

19th International Colloquium on Theoretical Aspects of Comp...

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19th international Colloquium on theoretical Aspects of computing, ICTAC 2022

ISBN: (纸本)9783031177149

the proceedings contain 29 papers. the special focus in this conference is on theoretical Aspects of computing. the topics include: Structural Rules and Algebraic Properties of Intersection Types;quantitative Weak Linearisation;on the Formalization and Computational Complexity of Resilience Problems for Cyber-Physical systems;spatial and Timing Properties in Highway Traffic;preface;veriMon: A Formally Verified Monitoring Tool;Denotational and Algebraic Semantics for the CaIT Calculus;reconciling Communication Delays and Negation;a Combinatorial Study of Async/Await Processes;unsatisfiability of Comparison-Based Non-malleability for Commitments;alternating Automatic Register Machines;functional Choreographic Programming;a Model Checking Based Approach to Detect Safety-Critical Adversarial Examples on Autonomous Driving systems;ground Confluence and Strong Commutation Modulo Alpha-Equivalence in Nominal Rewriting;Local XOR Unification: Definitions, algorithms and Application to Cryptography;a Matching Logic Foundation for Alk;generalized Test Tables: A Domain-Specific Specification Language for Automated Production systems;a Type System with Subtyping for WebAssembly’s Stack Polymorphism;A Verified Implementation of B + -Trees in Isabelle/HOL;active Learning for Deterministic Bottom-Up Nominal Tree Automata;towards a User Interface Description Language Based on Bigraphs;a Specification Logic for Programs in the Probabilistic Guarded Command Language;card-Minimal Protocols for Symmetric Boolean Functions of More than Seven Inputs;runners for Interleaving Algebraic Effects;formal Grammars for Turn-Bounded Deterministic Context-Free Languages;towards a Unifying Logical Framework for Neural Networks;type Inference for Rank-2 Intersection Types Using Set Unification.

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Simulation Testbed for Evaluating Distributed Querying and Searching of Mass Spectrometry Big Data in a Network-based Infrastructure 7

Simulation Testbed for Evaluating Distributed Querying and S...

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7th IEEE international conference on Big Data computing Service and Applications, BigDataService 2021

作者： Mohammad, Umair Saeed, Fahad School of Computing and Information Sciences Florida International University MiamiFL33199 United States

ISBN: (纸本)9781665434836

Advance access and reuse mechanisms for large-scale Mass Spectrometry (MS) data are essential for democratizing data for the omics research community and making it adhere to FAIR (Findable, Accessible, Interoperable, Reusable) principles. Although a number of centralized data repositories have been established, they have been limited to search mechanisms that depend on the meta-data associated with these MS datasets. Furthermore, they require constant influx of resources for maintenance. In this paper, we proposed an alternative novel distributed infrastructure for direct MS/MS spectral search. We designed and developed a simulation testbed using concepts from computer networks, queuing theory, and stochastic simulation methods. Results show that a distributed MS search based on raw MS/MS spectra can scale gracefully for up-to 2000 participating nodes, while simultaneously processing queries using the proposed networked infrastructure on the order of milliseconds to a few seconds for up-to a total of fifty billion MS/MS spectra. © 2021 IEEE.

关键词： Mass spectrometry

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Wideband Conformal Meandered Bowtie Antenna for Capsule Endoscopy systems

Wideband Conformal Meandered Bowtie Antenna for Capsule Endo...

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international Electromagnetic Compatibility conference (EMC Turkiye)

作者： Amir Arayeshnia Majid Rafiee Mohammad Alibakhshikenari Chan Hwang See Ernesto Limiti Faculty of Technical and Engineering Imam Khomeini International University Qazvin Iran Department of Electrical Engineering Ooj Institute of Higher Education Qazvin Iran Department of Signal Theory and Communications Universidad Carlos III de Madrid Madrid Spain School of Computing Engineering and the Built Environment Edinburgh Napier University Edinburgh Scotland Electronic Engineering Department University of Rome “Tor Vergata” Rome Italy

this article presents a wideband conformal meandered bowtie antenna for capsule endoscopy systems for gastrointestinal tract monitoring. the antenna has an operational bandwidth of 0.39-1.06 GHz (92%) and can operate in the frequency band of medical implant communication systems (i.e. 401-406MHz), as well as ISM bands (433.05-434.79 MHz and 902-928MHz). A biocompatible superstrate is also considered to prevent direct contact between radiating elements and biological tissues. the radiation efficiency of the proposed antenna exceeds 90% over the operational spectrum. the proposed antenna also has a stable omnidirectional radiation pattern, enabling a reliable wireless communication connection during the monitoring process.

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A 3D Multi-Scale Multi-Attention UNet for Automatic Hippocampal Segmentation 7

A 3D Multi-Scale Multi-Attention UNet for Automatic Hippocam...

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7th Annual international conference on Network and Information systems for Computers, ICNISC 2021

作者： Lin, Lan Kang, Wenjie Wu, Yuchao Zhao, Yuhan Wang, Sixue Lin, Danyi Gao, Jinlu Beijing University of Technology Intelligent Physiological Measurement and Clinical Translation Beijing International Base for Scientific and Technological Cooperation Beijing China

ISBN: (纸本)9781665402323

Hippocampus is one of the first affected brain regions in Alzheimer's disease (AD). To help AD diagnosis, hippocampal atrophy have been studied extensively, but accurate segmentation of hippocampus has always been a difficult problem. In this study, we propose a 3D multi-scale multi-attention UNet with the use of multi-scale inception module, residual connections and attention modules for automatic hippocampal segmentation. Experimental results on the HarP dataset show that our proposed method can achieve average Dice coefficient of 0.827 for hippocampal segmentation, which outperform classic 3D UNet. the efficiency and accuracy of the proposed methods suggests that it may facilitate the study of the hippocampus for large-scale studies. © 2021 IEEE.

关键词： Convolutional neural networks

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Message from conference Chairs

Proceedings - 2022 IEEE/ACIS 7th International Conference on...

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proceedings - 2022 IEEE/ACIS 7th international conference on Big Data, Cloud computing, and Data Science, BCD 2022 2022年 VIII页

作者： Trong, Van Hung Park, Jongwoo VKU Viet Nam Soongsil University Korea Republic of

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MPICC: Multiple-Precision Inter-Combined MAC Unit with Stochastic Rounding for Ultra-Low-Precision Training 25

MPICC: Multiple-Precision Inter-Combined MAC Unit with Stoch...

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30th Asia and South Pacific Design Automation conference, ASP-DAC 2025

作者： Huang, Leran Liu, Yongpan Lin, Xinyuan Wei, Chenhan Sun, Wenyu Wang, Zengwei Cao, Boran Zhang, Chi Fu, Xiaoxia Zhao, Wentao Zhang, Sheng Tsinghua Shenzhen International Graduate School Key Laboratory of Advanced Sensor and Integrated System Shenzhen China Tsinghua University Department of Electronic Engineering Beijing China

ISBN: (纸本)9798400706356

Recent studies have proved the feasibility of ultra-low-precision (≤ 8-bit) training. However, most of the existing operational circuits support only a few higher precisions (FP16, FP32, etc.) for multiplication, and the bit width for accumulation cannot be reduced, which results in low area and power efficiencies. In this paper, we propose MPICC, a multiple-precision Multiply-Accumulate (MAC) unit designed for ultra-low-precision training. It supports inter-combined computations across 18 different precision combinations, including LOG4 (radix-4 FP4), FP4, FP6, FP8, and INT4. It also reduces the accumulation precision from FP16 to FP12 through an optimized Stochastic Rounding (SR) strategy to further save logic resources. Moreover, a low-cost emulating controller, which time-division multiplexed the low-precision MAC unit, is also designed to accomplish high-precision computations for critical DNN layers. Compared with the existing multiple-precision computing units, the area/energy efficiencies of this design are improved by 1.17×/1.19× at FP8, and 4.69×/3.64× at FP4, respectively. the SR strategy further reduces the area/power consumption by 15.6%/14.9% of the floating-point accumulator. © 2025 Institute of Electrical and Electronics Engineers Inc.. All rights reserved.

关键词： Stochastic systems

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8th international Symposium on Ubiquitous Networking, UNet 2022

8th International Symposium on Ubiquitous Networking, UNet 2...

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8th international Symposium on Ubiquitous Networking, UNet 2022

ISBN: (纸本)9783031294181

the proceedings contain 21 papers. the special focus in this conference is on Ubiquitous Networking. the topics include: Deep Reinforcement Learning to Improve Vehicle-to-Vulnerable Road User Communications in C-V2X;Pervasive computing for Efficient Intra-UAV Connectivity: Based on Context-Awareness;road Accident Analysis of Dhaka City Using Counter Propagation Network;reinforcement Learning for Protocol Synthesis in Resource-Constrained Wireless Sensor and IoT Networks;Distributional Reinforcement Learning for VoLTE Closed Loop Power Control in Indoor Small Cells;reinforcement Learning Aided Routing in Tactical Wireless Sensor Networks;a Green and Scalable Clustering for Massive IoT Sensors with Selective Deactivation;threat Mitigation Model with Low False Alarm Rate Based on Hybrid Deep Belief Network;on Feature Selection algorithms for Effective Botnet Detection;Low Profile CPW Fed Tri-Band Millimeter Wave Antenna Design for Future 5G Application;A Novel Hybrid Deep Learning Model for Crop Disease Detection Using BEGAN;Multivariate Skewness and Kurtosis for Detecting Wormhole Attack in VANETs;trading Off Controlled System Energy and Wireless Communication Energy;statistical Moments of the Temporal Spectrum of Electromagnetic Waves in the Equatorial Ionosphere;Towards Facilitating URLLC in UAV-enabled MEC systems for 6G Networks;resource Allocation and Power Control for Heterogeneous Cellular Network and D2D Communications;optimized Network Coding with Real-Time Loss Prediction for Hybrid 5G Networks;TCP-RTA: Real-time Topology Adaptive Congestion Control Strategy in TCP;Rio_DSA: Redirecting I/O Scheme for Dynamic Storage Allocation on Docker Container.

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