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2021

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Articles 1951 - 1980 of 9983

Full-Text Articles in Engineering

Reusability Analysis And Application For Complex System Simulation Model, Zhu Feng, Yiping Yao, Wenjie Tang, Li Jin Oct 2021

Reusability Analysis And Application For Complex System Simulation Model, Zhu Feng, Yiping Yao, Wenjie Tang, Li Jin

Journal of System Simulation

Abstract: Model reuse is an important way to improve the development efficiency of complex system simulation application. At present, there are few researches on the reusability of simulation model and its impact on the development efficiency of complex system simulation application integration by using qualitative/quantitative methods. A simulation model reusability analysis method is proposed. By introducing the simulation application integration development speedup ratio, the simulation model reusability analysis mathematical model is constructed, and the requirements of model interface, model testing and information description for improving model reusability are analyzed qualitatively. Through two typical case studies, the influence of reusable simulation …

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Scheduling Optimization Research Based On Tabu Algorithm For Uncertainty Carrier Aircraft Support, Yangkai Meng, Wang Zheng, Jiali Fan Oct 2021

Scheduling Optimization Research Based On Tabu Algorithm For Uncertainty Carrier Aircraft Support, Yangkai Meng, Wang Zheng, Jiali Fan

Journal of System Simulation

Abstract: In order to improve the scheduling stability of ship-borne and reduce the uncertainty risk during the operation, the deck scheduling mathematical model is designed. For the refueling uncertainty, the equipment failure distribution function is established, and the research method of guarantee operation risk factor value and fault opportunity influence factor is proposed. The uncertainty target function calculation model is derived and solved using the improved taboo algorithm to obtain the scheduling optimization scheme. Simulation experimental results verify the effectiveness and feasibility of the proposed research method.

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Research On Assocoation Information Mining Of Space Reconnaissance Equipment System Index, Han Chi, Xiong Wei Oct 2021

Research On Assocoation Information Mining Of Space Reconnaissance Equipment System Index, Han Chi, Xiong Wei

Journal of System Simulation

Abstract: The system effectiveness and system contribution rate of the Space Reconnaissance Equipment System (SRES) has a large number of mutally associated indicators. How to identify relationships the association, select the key indicators and clarify the assocition between core indicators and system contribution rate are the key of the evaluation of system effectiveness and contribution rate. Through the joint simulation of MATLAB and STK, the underlying index data of SRES is obtained. Based on the Frequent Pattern-Tree (FP-Tree) algorithm, the assocition information is discovered, the redundancy is removed and the type of indicator assocition is determined, and an optimization model …

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Research On The Network Of 3d Smoke Flow Super-Resolution Data Generation, Jinlian Du, Shufei Li, Xueyun Jin Oct 2021

Research On The Network Of 3d Smoke Flow Super-Resolution Data Generation, Jinlian Du, Shufei Li, Xueyun Jin

Journal of System Simulation

Abstract: Aiming at the problem of low data generation efficiency due to the high complexity of solving the N-S equation of smoke flow field, a deep learning model which can generate high-resolution smoke flow data based on low-resolution smoke flow data solved by N-S equation is explored and designed. Based on the Generative Adversarial Network, the smoke data reconstruction network based on the sub voxel convolution layer is constructed. Considering the fluidity of smoke, time loss based on advection step is introduced into the loss function to realize high-precision smoke simulation. By extending the image super-resolution quality evaluation index, the …

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Modeling And Simulation Of Car Following In Fog Based On Cellular Automata, Zhanhong Liu, Xiujian Yang, Xiangji Wu, Huang Zhen Oct 2021

Modeling And Simulation Of Car Following In Fog Based On Cellular Automata, Zhanhong Liu, Xiujian Yang, Xiangji Wu, Huang Zhen

Journal of System Simulation

Abstract: In order to ensure the safety of driving in foggy weather, a microscopic model of car following and lane changing traffic flow is established based on cellular automata. In view of the instability of car following state in foggy weather, dynamic random acceleration is introduced to segment modeling. The simulation accuracy is improved by refining cell size and cell step size and adding position update allowance. The relationship curves of speed and vehicle dispersion with time and the speed density diagram are obtained. The results show that: the vehicle speed fluctuates greatly in medium fog; the dispersion …

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Three-Dimensional Visual Dynamic Simulation Of Rice Leaf Cells, Deheng Zhao, Yingding Zhao, Hongyun Yang, Wenlong Yi Oct 2021

Three-Dimensional Visual Dynamic Simulation Of Rice Leaf Cells, Deheng Zhao, Yingding Zhao, Hongyun Yang, Wenlong Yi

Journal of System Simulation

Abstract: To explore the evolution process of rice leaf cell morphology with the help of computer visualization technology, it is necessary to establish the biomechanical relationship between the cell geometry model and its deformation. A dynamic simulation method is proposed for the 3D visualization of leaf cells based on the physical-mechanical properties, in which the cytoskeleton topology is represented by a "half-edge" data structure, and the surface geometries are constructed using a bicubic Bézier surface. The control parameters of a deformed surface are determined through "vertex", "edge" or "face" topological unit query algorithms of the cytoskeleton, and the cell stress-strain …

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Research On Simulation Data Mapping For Production Performance Digital Twin, Junfeng Wang, Yufan Zhang, Yaoqi Shao, Shiqi Li Oct 2021

Research On Simulation Data Mapping For Production Performance Digital Twin, Junfeng Wang, Yufan Zhang, Yaoqi Shao, Shiqi Li

Journal of System Simulation

Abstract: To fully use the real-time data of the physical workshop to realize the accurate mapping of the data to the virtual workshop and drive the simulation and optimization of the manufacturing system, a data mapping method for the digital twin simulation of production performance is proposed. The fusion process of simulation data and production logic model is analyzed from the aspects of simulation data modeling, storage and updating. Focusing on the production performance simulation requirements, the redundancy analysis, outlier analysis and elimination, statistics and fitting of the original production site sample data is preprocessed. The real-time mapping update process …

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Modeling And Simulation Of Channel Passage Capacity Based On Cellular Automata, Zongyang Liu, Chunhui Zhou, Junnan Zhao, Jinli Xiao, Langxiong Gan Oct 2021

Modeling And Simulation Of Channel Passage Capacity Based On Cellular Automata, Zongyang Liu, Chunhui Zhou, Junnan Zhao, Jinli Xiao, Langxiong Gan

Journal of System Simulation

Abstract: In order to study the passage capacity of the seaport and explore the service level of the channel, the cellular automata theory is used to discretize and model the main channel of the seaport, and the movement rules of the cell in the channel are processed in sections. In addition, this study focuses on the existence of a traffic "warning zone" in the curved channel section. The ship motion rules of the straight channel section and the curved channel section are respectively constrained, through simulation experiments, the vessel traffic flow of the channel and the maximum ship passing …

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Virtual And Real Fusion Experiment Simulation Technology Based On Gesture Interaction, Xuyan Zou, Hanwu He, Yueming Wu, Jingwei Deng Oct 2021

Virtual And Real Fusion Experiment Simulation Technology Based On Gesture Interaction, Xuyan Zou, Hanwu He, Yueming Wu, Jingwei Deng

Journal of System Simulation

Abstract: In experimental teaching, some traditional experiments cannot be carried out due to limitations of experimental environment, experimental equipment, and faculty. In order to solve the above problems, the method of constructing virtual and real fusion simulation experiment using depth cameras is explored.. The Aruco labeling algorithm is used to achieve one-to-one registration of the virtual scene and the real scene, and the experimental environment of virtual and real fusion is constructed combining the colour images and depth images collected by the depth camera in real time. In order to achieve the purpose of operating virtual equipment, a gesture interaction …

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Occurrence And Removal Of Engineered Nanoparticles In Drinking Water Treatment And Wastewater Treatment A Review, Cheng Yu, Sewoon Kim, Min Jang, Chang Min Park, Yeomin Yoon Oct 2021

Occurrence And Removal Of Engineered Nanoparticles In Drinking Water Treatment And Wastewater Treatment A Review, Cheng Yu, Sewoon Kim, Min Jang, Chang Min Park, Yeomin Yoon

Faculty Publications

Engineered nanoparticles (ENPs) are widely used in various industrial products and consumer goods, resulting in their widespread existence, particularly in natural water systems and water and wastewater treatment plants. Their presence in surface water for human consumption may severely harm human health. Therefore, this review examines new findings and developments in the removal technology of ENPs in drinking water and wastewater treatment processes since the publication of the literature by Park et al. [1]. By evaluating recent articles, this review investigates the occurrence of ENPs, discusses the transport of nanoparticles (NPs) in various drinking water and wastewater treatment …

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The Winter Adverse Driving Dataset (Wads) - Sequence 14, Akhil Kurup, Jeremy Bos Oct 2021

The Winter Adverse Driving Dataset (Wads) - Sequence 14, Akhil Kurup, Jeremy Bos

Michigan Tech Research Data

Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of moderate to …

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Recent Advances In Silver Nanoparticle-Based Electrochemical Sensors For Determining Organic Pollutants In Water, Ziad Khalifa, Moustafa Zahran, Magdy Zahran, Magdi Abdelazzem Oct 2021

Recent Advances In Silver Nanoparticle-Based Electrochemical Sensors For Determining Organic Pollutants In Water, Ziad Khalifa, Moustafa Zahran, Magdy Zahran, Magdi Abdelazzem

Chemical Engineering

Water pollutants have attracted great attention because of their negative effect on human health. Accordingly, various analytical techniques have been investigated to detect water pollutants as a preliminary step for their control. This review highlights silver nanoparticles (AgNPs) as promising electrochemical probes studied for detecting organic pollutants. Electrochemical sensors can be fabricated by modifying electrode surfaces using AgNPs via different techniques, such as electrochemical deposition, drop casting, spin coating, sticking, and transfer sticking, as well as carbon paste-based modification. AgNPs at electrode surfaces can be identified by their stripping to form Ag+ with a particular oxidation peak. Additionally, they can …

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The Winter Adverse Driving Dataset (Wads) - Sequence 17, Akhil Kurup, Jeremy Bos Oct 2021

The Winter Adverse Driving Dataset (Wads) - Sequence 17, Akhil Kurup, Jeremy Bos

Michigan Tech Research Data

Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of moderate to …

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The Winter Adverse Driving Dataset (Wads) - Sequence 20, Akhil Kurup, Jeremy Bos Oct 2021

The Winter Adverse Driving Dataset (Wads) - Sequence 20, Akhil Kurup, Jeremy Bos

Michigan Tech Research Data

Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of moderate to …

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High-Order Deterministic Sensitivity Analysis And Uncertainty Quantification: Review And New Developments, Dan Gabriel Cacuci Oct 2021

High-Order Deterministic Sensitivity Analysis And Uncertainty Quantification: Review And New Developments, Dan Gabriel Cacuci

Faculty Publications

This work reviews the state-of-the-art methodologies for the deterministic sensitivity analysis of nonlinear systems and deterministic quantification of uncertainties induced in model responses by uncertainties in the model parameters. The need for computing high-order sensitivities is underscored by presenting an analytically solvable model of neutron scattering in a hydrogenous medium, for which all of the response’s relative sensitivities have the same absolute value of unity. It is shown that the wider the distribution of model parameters, the higher the order of sensitivities needed to achieve a desired level of accuracy in representing the response and in computing the response’s expectation, …

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A High-Pressure Shear Testing Approach To Measure Flow Stresses Near A Friction Stir Welding Tool, David Prymak, Michael Miles, Tracy W. Nelson, Fredrick Michael Oct 2021

A High-Pressure Shear Testing Approach To Measure Flow Stresses Near A Friction Stir Welding Tool, David Prymak, Michael Miles, Tracy W. Nelson, Fredrick Michael

Faculty Publications

A new approach for measuring flow stresses near a spinning friction stir welding (FSW) tool is evaluated on AA 6061-T6 plate. The test consists of plunging a cylindrical tool with a flat face into the plate at different rotational speeds, using a variety of constant vertical loads. A viscosity-based model of the shear layer created under the tool is employed to estimate local flow stresses. The flow stresses measured by this approach exhibited an inverse relationship with temperature and a positive dependence on the pressure imposed by the spinning flat-faced tool. Compared to hot compression and hot torsion results, estimated …

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The Winter Adverse Driving Dataset (Wads) - Sequence 11, Akhil Kurup, Jeremy Bos Oct 2021

The Winter Adverse Driving Dataset (Wads) - Sequence 11, Akhil Kurup, Jeremy Bos

Michigan Tech Research Data

Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of moderate to …

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The Winter Adverse Driving Dataset (Wads) - Sequence 12, Akhil Kurup, Jeremy Bos Oct 2021

The Winter Adverse Driving Dataset (Wads) - Sequence 12, Akhil Kurup, Jeremy Bos

Michigan Tech Research Data

Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of moderate to …

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The Winter Adverse Driving Dataset (Wads) - Sequence 13, Akhil Kurup, Jeremy Bos Oct 2021

The Winter Adverse Driving Dataset (Wads) - Sequence 13, Akhil Kurup, Jeremy Bos

Michigan Tech Research Data

Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of moderate to …

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The Winter Adverse Driving Dataset (Wads) - Sequence 15, Akhil Kurup, Jeremy Bos Oct 2021

The Winter Adverse Driving Dataset (Wads) - Sequence 15, Akhil Kurup, Jeremy Bos

Michigan Tech Research Data

Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of moderate to …

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The Winter Adverse Driving Dataset (Wads) - Sequence 16, Akhil Kurup, Jeremy Bos Oct 2021

The Winter Adverse Driving Dataset (Wads) - Sequence 16, Akhil Kurup, Jeremy Bos

Michigan Tech Research Data

Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of moderate to …

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The Winter Adverse Driving Dataset (Wads) - Sequence 18, Akhil Kurup, Jeremy Bos Oct 2021

The Winter Adverse Driving Dataset (Wads) - Sequence 18, Akhil Kurup, Jeremy Bos

Michigan Tech Research Data

Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of moderate to …

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The Winter Adverse Driving Dataset (Wads) - Sequence 22, Akhil Kurup, Jeremy Bos Oct 2021

The Winter Adverse Driving Dataset (Wads) - Sequence 22, Akhil Kurup, Jeremy Bos

Michigan Tech Research Data

Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of moderate to …

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The Winter Adverse Driving Dataset (Wads) - Sequence 23, Akhil Kurup, Jeremy Bos Oct 2021

The Winter Adverse Driving Dataset (Wads) - Sequence 23, Akhil Kurup, Jeremy Bos

Michigan Tech Research Data

Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of moderate to …

Go to article

The Winter Adverse Driving Dataset (Wads) - Sequence 24, Akhil Kurup, Jeremy Bos Oct 2021

The Winter Adverse Driving Dataset (Wads) - Sequence 24, Akhil Kurup, Jeremy Bos

Michigan Tech Research Data

Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of moderate to …

Go to article

The Winter Adverse Driving Dataset (Wads) - Sequence 26, Akhil Kurup, Jeremy Bos Oct 2021

The Winter Adverse Driving Dataset (Wads) - Sequence 26, Akhil Kurup, Jeremy Bos

Michigan Tech Research Data

Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of moderate to …

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The Winter Adverse Driving Dataset (Wads) - Sequence 28, Akhil Kurup, Jeremy Bos Oct 2021

The Winter Adverse Driving Dataset (Wads) - Sequence 28, Akhil Kurup, Jeremy Bos

Michigan Tech Research Data

Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of moderate to …

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The Winter Adverse Driving Dataset (Wads) - Sequence 30, Akhil Kurup, Jeremy Bos Oct 2021

The Winter Adverse Driving Dataset (Wads) - Sequence 30, Akhil Kurup, Jeremy Bos

Michigan Tech Research Data

Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of moderate to …

Go to article

The Winter Adverse Driving Dataset (Wads) - Sequence 34, Akhil Kurup, Jeremy Bos Oct 2021

The Winter Adverse Driving Dataset (Wads) - Sequence 34, Akhil Kurup, Jeremy Bos

Michigan Tech Research Data

Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of moderate to …

Go to article

The Winter Adverse Driving Dataset (Wads) - Sequence 35, Akhil Kurup, Jeremy Bos Oct 2021

The Winter Adverse Driving Dataset (Wads) - Sequence 35, Akhil Kurup, Jeremy Bos

Michigan Tech Research Data

Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of moderate to …

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