Results 71 to 80 of about 107,458 (327)

Point Cloud Semantic Segmentation using Multi Scale Sparse Convolution Neural Network [PDF]

, 2022
Yunzheng Su, Jiang, Lei, Cao, Jie
openalex   +1 more source

Bio‐Inspired Molecular Events in Poly(Ionic Liquids)

Advanced Functional Materials, EarlyView.
Originating from dipolar and polar inter‐ and intra‐chain interactions of the building blocks, the topologies and morphologies of poly(ionic liquids) (PIL) govern their nano‐ and micro‐processibility. Modulating the interactions of cation‐anion pairs with aliphatic dipolar components enables the tunability of properties, facilitated by “bottom‐up ...
Jiahui Liu, Marek W. Urban
wiley   +1 more source

PointGeo: Geometry Transformer for Point Cloud Analysis

CAAI Transactions on Intelligence Technology
Point cloud processing plays a crucial role in tasks such as point cloud classification, partial segmentation and semantic segmentation. However, existing processing frameworks are constrained by several challenges, such as recognising features in ...
Li An, Pengbo Zhou, Mingquan Zhou, Yong Wang, Guohua Geng, Yangyang Liu   +5 more
doaj   +1 more source

SegICP: Integrated Deep Semantic Segmentation and Pose Estimation

, 2017
Recent robotic manipulation competitions have highlighted that sophisticated robots still struggle to achieve fast and reliable perception of task-relevant objects in complex, realistic scenarios. To improve these systems' perceptive speed and robustness,
Chipalkatty, Rahul, Hamilton, Lei, Hebert, Mitchell, Johnson, David M. S., Kee, Vincent, Le, Tiffany, Mariottini, Gian-Luca, Schneider, Abraham, Torralba, Antonio, Wagner, Syler, Wong, Jay M., Wu, Jimmy, Zhou, Bolei   +12 more
core   +1 more source

From Wafers to Electrodes: Transferring Automatic Optical Inspection (AOI) for Multiscale Characterization of Smart Battery Manufacturing

Advanced Functional Materials, EarlyView.
Automat optical inspection (AOI) techniques in semiconductor fabrication can be leveraged in battery manufacturing, enabling scalable detection and analysis of electrode‐ and cell‐level imperfections through AI‐driven analytics and a digital‐twin framework.
Jianyu Li, Ertao Hu, Wei Wei, Feifei Shi
wiley   +1 more source

Point Cloud Segmentation Algorithm Based on Improved Euclidean Clustering

IEEE Access
Point cloud segmentation is a crucial technique for object recognition and localization, widely employed in various applications such as point cloud registration, 3D reconstruction, object recognition, and robotic grasping.
Fangrui Chen, Feifei Xie, Lin Sun, Yuchao Gu, Zhipeng Zhang, Jinpeng Chen, Jinrui Zhang, Mingzhe Yi   +7 more
doaj   +1 more source

Engineering Strategies for Stable and Long‐Life Alkaline Zinc‐Based Flow Batteries

Advanced Functional Materials, EarlyView.
Alkaline zinc‐based flow batteries face persistent challenges from unstable zinc deposition, including dendrite growth, passivation, corrosion, and hydrogen evolution, which severely limit cycling stability. Current research addresses these issues through coordinated electrode structuring, electrolyte regulation, and membrane design to control zinc ...
Yuran Bai, Xiaoyu Huo, Xin Long, Enkang Fu, Xusong Gong, Lei Wei, Liang An   +6 more
wiley   +1 more source

Weld Seam ROI Detection and Segmentation Method Based on Active–Passive Vision Fusion

Sensors
Rapid detection and precise segmentation of the weld seam region of interest (ROI) remain a core challenge in robotic intelligent grinding. To address this issue, this paper proposes a method for weld seam ROI detection and segmentation based on the ...
Ming Hu, Xiangtao Hu, Jiuzhou Zhao, Honghui Zhan   +3 more
doaj   +1 more source

SemAffiNet: Semantic-Affine Transformation for Point Cloud Segmentation [PDF]

, 2022
Ziyi Wang, Yongming Rao, Xumin Yu, Jie Zhou, Jiwen Lu   +4 more
openalex   +1 more source

Dynamic Convolution for 3D Point Cloud Instance Segmentation

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022
We propose an approach to instance segmentation from 3D point clouds based on dynamic convolution. This enables it to adapt, at inference, to varying feature and object scales. Doing so avoids some pitfalls of bottom up approaches, including a dependence on hyper-parameter tuning and heuristic post-processing pipelines to compensate for the inevitable ...
Tong He, Chunhua Shen, Anton van den Hengel   +2 more
openaire   +4 more sources