Zeitschriftenartikel zum Thema „Modèle voxel“
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Zhao, Lin, Siyuan Xu, Liman Liu, Delie Ming und Wenbing Tao. „SVASeg: Sparse Voxel-Based Attention for 3D LiDAR Point Cloud Semantic Segmentation“. Remote Sensing 14, Nr. 18 (07.09.2022): 4471. http://dx.doi.org/10.3390/rs14184471.
Tang, Jiaxiang, Xiaokang Chen, Jingbo Wang und Gang Zeng. „Not All Voxels Are Equal: Semantic Scene Completion from the Point-Voxel Perspective“. Proceedings of the AAAI Conference on Artificial Intelligence 36, Nr. 2 (28.06.2022): 2352–60. http://dx.doi.org/10.1609/aaai.v36i2.20134.
He, Qingdong, Zhengning Wang, Hao Zeng, Yi Zeng und Yijun Liu. „SVGA-Net: Sparse Voxel-Graph Attention Network for 3D Object Detection from Point Clouds“. Proceedings of the AAAI Conference on Artificial Intelligence 36, Nr. 1 (28.06.2022): 870–78. http://dx.doi.org/10.1609/aaai.v36i1.19969.
Chen, Yuhong, Weilong Peng, Keke Tang, Asad Khan, Guodong Wei und Meie Fang. „PyraPVConv: Efficient 3D Point Cloud Perception with Pyramid Voxel Convolution and Sharable Attention“. Computational Intelligence and Neuroscience 2022 (13.05.2022): 1–9. http://dx.doi.org/10.1155/2022/2286818.
Li, Guangping, Zuanfang Mo und Bingo Wing-Kuen Ling. „AMFF-Net: An Effective 3D Object Detector Based on Attention and Multi-Scale Feature Fusion“. Sensors 23, Nr. 23 (22.11.2023): 9319. http://dx.doi.org/10.3390/s23239319.
Shuang, Feng, Hanzhang Huang, Yong Li, Rui Qu und Pei Li. „AFE-RCNN: Adaptive Feature Enhancement RCNN for 3D Object Detection“. Remote Sensing 14, Nr. 5 (27.02.2022): 1176. http://dx.doi.org/10.3390/rs14051176.
Bourbonne, V., V. Jaouen, M. Rehn, M. Hatt, O. Pradier, D. Visvikis, F. Lucia und U. Schick. „Développement et validation d’un modèle basé sur l’analyse par voxel pour la prédiction de la toxicité pulmonaire aiguë chez les patients pris en charge par arcthérapie volumétrique pour un cancer du poumon localement évolué“. Cancer/Radiothérapie 25, Nr. 6-7 (Oktober 2021): 736. http://dx.doi.org/10.1016/j.canrad.2021.07.020.
Wang, Yu, und Chao Tong. „H2GFormer: Horizontal-to-Global Voxel Transformer for 3D Semantic Scene Completion“. Proceedings of the AAAI Conference on Artificial Intelligence 38, Nr. 6 (24.03.2024): 5722–30. http://dx.doi.org/10.1609/aaai.v38i6.28384.
Guo, Xindong, Yu Sun und Hua Yang. „FF-Net: Feature-Fusion-Based Network for Semantic Segmentation of 3D Plant Point Cloud“. Plants 12, Nr. 9 (01.05.2023): 1867. http://dx.doi.org/10.3390/plants12091867.
Peng, Hao, Guofeng Tong, Zheng Li, Yaqi Wang und Yuyuan Shao. „3D object detection combining semantic and geometric features from point clouds“. Cobot 1 (12.01.2022): 2. http://dx.doi.org/10.12688/cobot.17433.1.
Zhang, Jing, Da Xu, Yunsong Li, Liping Zhao und Rui Su. „FusionPillars: A 3D Object Detection Network with Cross-Fusion and Self-Fusion“. Remote Sensing 15, Nr. 10 (22.05.2023): 2692. http://dx.doi.org/10.3390/rs15102692.
Zhao, Yuekun, Suyun Luo, Xiaoci Huang und Dan Wei. „A Multi-Sensor 3D Detection Method for Small Objects“. World Electric Vehicle Journal 15, Nr. 5 (10.05.2024): 210. http://dx.doi.org/10.3390/wevj15050210.
Jiang, Haobin, Junhao Ren und Aoxue Li. „3D Object Detection under Urban Road Traffic Scenarios Based on Dual-Layer Voxel Features Fusion Augmentation“. Sensors 24, Nr. 11 (21.05.2024): 3267. http://dx.doi.org/10.3390/s24113267.
Topoliński, Tomasz, Artur Cichański, Adam Mazurkiewicz und Krzysztof Nowicki. „The Relationship between Trabecular Bone Structure Modeling Methods and the Elastic Modulus as Calculated by FEM“. Scientific World Journal 2012 (2012): 1–9. http://dx.doi.org/10.1100/2012/827196.
Chen, Hongmei, Haifeng Wang, Zilong Liu, Dongbing Gu und Wen Ye. „HP3D-V2V: High-Precision 3D Object Detection Vehicle-to-Vehicle Cooperative Perception Algorithm“. Sensors 24, Nr. 7 (28.03.2024): 2170. http://dx.doi.org/10.3390/s24072170.
Kim, Taeho, und Joohee Kim. „Voxel Transformer with Density-Aware Deformable Attention for 3D Object Detection“. Sensors 23, Nr. 16 (17.08.2023): 7217. http://dx.doi.org/10.3390/s23167217.
Li, Zheng, Guofeng Tong, Hao Peng und Mingwei Ma. „GAF-RCNN: Grid attention fusion 3D object detection from point cloud“. Cobot 2 (21.02.2023): 3. http://dx.doi.org/10.12688/cobot.17590.1.
Zhu, Yun, Le Hui, Yaqi Shen und Jin Xie. „SPGroup3D: Superpoint Grouping Network for Indoor 3D Object Detection“. Proceedings of the AAAI Conference on Artificial Intelligence 38, Nr. 7 (24.03.2024): 7811–19. http://dx.doi.org/10.1609/aaai.v38i7.28616.
Zhu, Yuan, Ruidong Xu, Chongben Tao, Hao An, Huaide Wang, Zhipeng Sun und Ke Lu. „DS-Trans: A 3D Object Detection Method Based on a Deformable Spatiotemporal Transformer for Autonomous Vehicles“. Remote Sensing 16, Nr. 9 (30.04.2024): 1621. http://dx.doi.org/10.3390/rs16091621.
Yan, Xu, Jiantao Gao, Jie Li, Ruimao Zhang, Zhen Li, Rui Huang und Shuguang Cui. „Sparse Single Sweep LiDAR Point Cloud Segmentation via Learning Contextual Shape Priors from Scene Completion“. Proceedings of the AAAI Conference on Artificial Intelligence 35, Nr. 4 (18.05.2021): 3101–9. http://dx.doi.org/10.1609/aaai.v35i4.16419.
Xu, Jinfeng, Xianzhi Li, Yuan Tang, Qiao Yu, Yixue Hao, Long Hu und Min Chen. „CasFusionNet: A Cascaded Network for Point Cloud Semantic Scene Completion by Dense Feature Fusion“. Proceedings of the AAAI Conference on Artificial Intelligence 37, Nr. 3 (26.06.2023): 3018–26. http://dx.doi.org/10.1609/aaai.v37i3.25405.
Pratt, Sheila R., Anne T. Heintzelman und Susan Ensrud Deming. „The Efficacy of Using the IBM Speech Viewer Vowel Accuracy Module to Treat Young Children With Hearing Impairment“. Journal of Speech, Language, and Hearing Research 36, Nr. 5 (Oktober 1993): 1063–74. http://dx.doi.org/10.1044/jshr.3605.1063.
Chen, Chen, Zhe Chen, Jing Zhang und Dacheng Tao. „SASA: Semantics-Augmented Set Abstraction for Point-Based 3D Object Detection“. Proceedings of the AAAI Conference on Artificial Intelligence 36, Nr. 1 (28.06.2022): 221–29. http://dx.doi.org/10.1609/aaai.v36i1.19897.
Lee, Jinho, Geonkyu Bang, Takaya Shimizu, Masato Iehara und Shunsuke Kamijo. „LiDAR-to-Radar Translation Based on Voxel Feature Extraction Module for Radar Data Augmentation“. Sensors 24, Nr. 2 (16.01.2024): 559. http://dx.doi.org/10.3390/s24020559.
Ning, Yaqian, Jie Cao, Chun Bao und Qun Hao. „DVST: Deformable Voxel Set Transformer for 3D Object Detection from Point Clouds“. Remote Sensing 15, Nr. 23 (03.12.2023): 5612. http://dx.doi.org/10.3390/rs15235612.
Wang, Jiachun, Junkui Song, Yizhe Zhang und Hao Chen. „Design of 3D Display System for Intangible Cultural Heritage Based on Generative Adversarial Network“. Scientific Programming 2022 (21.07.2022): 1–12. http://dx.doi.org/10.1155/2022/2944750.
Xie, Liang, Chao Xiang, Zhengxu Yu, Guodong Xu, Zheng Yang, Deng Cai und Xiaofei He. „PI-RCNN: An Efficient Multi-Sensor 3D Object Detector with Point-Based Attentive Cont-Conv Fusion Module“. Proceedings of the AAAI Conference on Artificial Intelligence 34, Nr. 07 (03.04.2020): 12460–67. http://dx.doi.org/10.1609/aaai.v34i07.6933.
Liu, Huaijin, Jixiang Du, Yong Zhang und Hongbo Zhang. „Enhancing Point Features with Spatial Information for Point-Based 3D Object Detection“. Scientific Programming 2021 (21.12.2021): 1–11. http://dx.doi.org/10.1155/2021/4650660.
Li, Yinhao, Zheng Ge, Guanyi Yu, Jinrong Yang, Zengran Wang, Yukang Shi, Jianjian Sun und Zeming Li. „BEVDepth: Acquisition of Reliable Depth for Multi-View 3D Object Detection“. Proceedings of the AAAI Conference on Artificial Intelligence 37, Nr. 2 (26.06.2023): 1477–85. http://dx.doi.org/10.1609/aaai.v37i2.25233.
Chang, Sungho, und Sang Chul Lee. „A Comparative Study on the Voxel Values in Alveolar Bones Acquired by MDCT and Newly Developed Dental Dual-Energy CBCT“. Sensors 21, Nr. 22 (13.11.2021): 7552. http://dx.doi.org/10.3390/s21227552.
Liu, Xinqi, Jituo Li und Guodong Lu. „A New Volumetric Fusion Strategy with Adaptive Weight Field for RGB-D Reconstruction“. Sensors 20, Nr. 15 (03.08.2020): 4330. http://dx.doi.org/10.3390/s20154330.
Alsadoon, Reem, und Trude Heift. „Textual Input Enhancement for Vowel Blindness: A Study with Arabic ESL Learners“. Modern Language Journal 99, Nr. 1 (März 2015): 57–79. http://dx.doi.org/10.1111/modl.12188.
Wang, Likang, Yue Gong, Qirui Wang, Kaixuan Zhou und Lei Chen. „Flora: Dual-Frequency LOss-Compensated ReAl-Time Monocular 3D Video Reconstruction“. Proceedings of the AAAI Conference on Artificial Intelligence 37, Nr. 2 (26.06.2023): 2599–607. http://dx.doi.org/10.1609/aaai.v37i2.25358.
Ashmawy, Mostafa, Ashraf Abou-Khalaf und Raghdaa Mostafa. „Effect of Voxel Size On The Accuracy of Nerve Tracing Module of Cone Beam Computed Tomography Images“. Egyptian Dental Journal 63, Nr. 3 (01.07.2017): 2403–12. http://dx.doi.org/10.21608/edj.2017.76057.
Liu, Zhe, Xin Zhao, Tengteng Huang, Ruolan Hu, Yu Zhou und Xiang Bai. „TANet: Robust 3D Object Detection from Point Clouds with Triple Attention“. Proceedings of the AAAI Conference on Artificial Intelligence 34, Nr. 07 (03.04.2020): 11677–84. http://dx.doi.org/10.1609/aaai.v34i07.6837.
ABCHIR, H., und C. BLANCHET. „ON THE COMPUTATION OF THE TURAEV-VIRO MODULE OF A KNOT“. Journal of Knot Theory and Its Ramifications 07, Nr. 07 (November 1998): 843–56. http://dx.doi.org/10.1142/s0218216598000437.
Barca, Patrizio, Daniela Marfisi, Chiara Marzi, Sabino Cozza, Stefano Diciotti, Antonio Claudio Traino und Marco Giannelli. „A Voxel-Based Assessment of Noise Properties in Computed Tomography Imaging with the ASiR-V and ASiR Iterative Reconstruction Algorithms“. Applied Sciences 11, Nr. 14 (16.07.2021): 6561. http://dx.doi.org/10.3390/app11146561.
Wu, Lei, Jiewu Leng und Bingfeng Ju. „Digital Twins-Based Smart Design and Control of Ultra-Precision Machining: A Review“. Symmetry 13, Nr. 9 (16.09.2021): 1717. http://dx.doi.org/10.3390/sym13091717.
Jinming, Chen. „Obstacle Detection Based on 3D Lidar Euclidean Clustering“. Applied Science and Innovative Research 5, Nr. 3 (08.11.2021): p39. http://dx.doi.org/10.22158/asir.v5n3p39.
Zhang, Zhikang, Zhongjie Zhu, Yongqiang Bai, Yiwen Jin und Ming Wang. „Multi-Scale Feature Fusion Point Cloud Object Detection Based on Original Point Cloud and Projection“. Electronics 13, Nr. 11 (06.06.2024): 2213. http://dx.doi.org/10.3390/electronics13112213.
Zheng, Wenqi, Han Xie, Yunfan Chen, Jeongjin Roh und Hyunchul Shin. „PIFNet: 3D Object Detection Using Joint Image and Point Cloud Features for Autonomous Driving“. Applied Sciences 12, Nr. 7 (06.04.2022): 3686. http://dx.doi.org/10.3390/app12073686.
Luo, Naisong, Rui Sun, Yuwen Pan, Tianzhu Zhang und Feng Wu. „Electron Microscopy Images as Set of Fragments for Mitochondrial Segmentation“. Proceedings of the AAAI Conference on Artificial Intelligence 38, Nr. 4 (24.03.2024): 3981–89. http://dx.doi.org/10.1609/aaai.v38i4.28191.
Yoshida, Keisuke, Shijun Pan, Junichi Taniguchi, Satoshi Nishiyama, Takashi Kojima und Md Touhidul Islam. „Airborne LiDAR-assisted deep learning methodology for riparian land cover classification using aerial photographs and its application for flood modelling“. Journal of Hydroinformatics 24, Nr. 1 (01.01.2022): 179–201. http://dx.doi.org/10.2166/hydro.2022.134.
Yu, Siyang, Si Sun, Wei Yan, Guangshuai Liu und Xurui Li. „A Method Based on Curvature and Hierarchical Strategy for Dynamic Point Cloud Compression in Augmented and Virtual Reality System“. Sensors 22, Nr. 3 (07.02.2022): 1262. http://dx.doi.org/10.3390/s22031262.
Cui, Mingyue, Junhua Long, Mingjian Feng, Boyang Li und Huang Kai. „OctFormer: Efficient Octree-Based Transformer for Point Cloud Compression with Local Enhancement“. Proceedings of the AAAI Conference on Artificial Intelligence 37, Nr. 1 (26.06.2023): 470–78. http://dx.doi.org/10.1609/aaai.v37i1.25121.
Qimin, Xu, Zhao Xin, Liao Longjie, Li Yameng und Li Na. „Efficient and Accurate Vehicle Localization Based on LiDAR Place Recognition“. Information Technology and Control 52, Nr. 2 (15.07.2023): 562–75. http://dx.doi.org/10.5755/j01.itc.52.2.32690.
Liu, Rongsheng, Xiaowei Liu, Chengfeng Peng, Anping Li und Yong Liao. „Automatic Brain Tumour Subregion Segmentation from Multimodal MRIs Fusing Muti-channel and Spatial Features“. Journal of Physics: Conference Series 2449, Nr. 1 (01.03.2023): 012034. http://dx.doi.org/10.1088/1742-6596/2449/1/012034.
Gan, Xingli, Hao Shi, Shan Yang, Yao Xiao und Lu Sun. „MANet: End-to-End Learning for Point Cloud Based on Robust Pointpillar and Multiattention“. Wireless Communications and Mobile Computing 2022 (14.09.2022): 1–12. http://dx.doi.org/10.1155/2022/6909314.
LUCCONI, GIULIA, CHIARA ROMEO, ROBERTO BONETTI, PATRIZIA CENNI und NICOLETTA SCRITTORI. „DIFFUSION MRI-BASED FIBER TRACKING IN HEALTHY AND BRAIN INJURY PATIENTS: A COMPARISON OF DIFFERENT SOFTWARE TOOLS“. Journal of Mechanics in Medicine and Biology 15, Nr. 02 (April 2015): 1540020. http://dx.doi.org/10.1142/s0219519415400205.
Peng, Zhao, Yu Lu, Yao Xu, Yongzhe Li, Bo Cheng, Ming Ni, Zhi Chen et al. „Development of a GPU-accelerated Monte Carlo dose calculation module for nuclear medicine, ARCHER-NM: demonstration for a PET/CT imaging procedure“. Physics in Medicine & Biology 67, Nr. 6 (17.03.2022): 06NT02. http://dx.doi.org/10.1088/1361-6560/ac58dd.