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The following term was not found in PubMed: Kuli-Revesz
Page 1
GAIA-Universe: Everything is Super-Netify.
Peng J, Chang Q, Yin H, Bu X, Sun J, Xie L, Zhang X, Tian Q, Zhang Z. Peng J, et al. IEEE Trans Pattern Anal Mach Intell. 2023 Oct;45(10):11856-11868. doi: 10.1109/TPAMI.2023.3276392. Epub 2023 Sep 5. IEEE Trans Pattern Anal Mach Intell. 2023. PMID: 37192026
With GAIA, we achieve promising results on COCO, Objects365, Open Images, BDD100 k, and UODB which is a collection of datasets including KITTI, VOC, WiderFace, DOTA, Clipart, Comic, and more. Taking COCO as an example, GAIA is able to efficiently produce models covering a …
With GAIA, we achieve promising results on COCO, Objects365, Open Images, BDD100 k, and UODB which is a collection of datasets including …
A Comprehensive Survey of Depth Completion Approaches.
Khan MAU, Nazir D, Pagani A, Mokayed H, Liwicki M, Stricker D, Afzal MZ. Khan MAU, et al. Sensors (Basel). 2022 Sep 14;22(18):6969. doi: 10.3390/s22186969. Sensors (Basel). 2022. PMID: 36146318 Free PMC article. Review.
We present a novel taxonomy of depth completion approaches, review in detail different state-of-the-art techniques within each category for depth completion of LiDAR data, and provide quantitative results for the approaches on KITTI and NYUv2 depth completion benchmark dat …
We present a novel taxonomy of depth completion approaches, review in detail different state-of-the-art techniques within each category for …
Deep Visual Odometry With Adaptive Memory.
Xue F, Wang X, Wang J, Zha H. Xue F, et al. IEEE Trans Pattern Anal Mach Intell. 2022 Feb;44(2):940-954. doi: 10.1109/TPAMI.2020.3014100. Epub 2022 Jan 7. IEEE Trans Pattern Anal Mach Intell. 2022. PMID: 32749962
Specifically, our architecture consisting of Tracking, Remembering and Refining modules works beyond tracking. Experiments on the KITTI and TUM-RGBD datasets demonstrate that our approach outperforms state-of-the-art methods by large margins and produces competitive result …
Specifically, our architecture consisting of Tracking, Remembering and Refining modules works beyond tracking. Experiments on the KITTI …
OSM-SLAM: Aiding SLAM with OpenStreetMaps priors.
Frosi M, Gobbi V, Matteucci M. Frosi M, et al. Front Robot AI. 2023 Mar 29;10:1064934. doi: 10.3389/frobt.2023.1064934. eCollection 2023. Front Robot AI. 2023. PMID: 37064577 Free PMC article.
The comparison is made by evaluating the estimated trajectory displacement using the KITTI odometry dataset. Moreover, the experimental campaign, along with an ablation study on the re-localization capabilities of the proposed system and its accuracy in loop detection-deni …
The comparison is made by evaluating the estimated trajectory displacement using the KITTI odometry dataset. Moreover, the experiment …
SDV-LOAM: Semi-Direct Visual-LiDAR Odometry and Mapping.
Yuan Z, Wang Q, Cheng K, Hao T, Yang X. Yuan Z, et al. IEEE Trans Pattern Anal Mach Intell. 2023 Sep;45(9):11203-11220. doi: 10.1109/TPAMI.2023.3262817. Epub 2023 Aug 7. IEEE Trans Pattern Anal Mach Intell. 2023. PMID: 37030871
Experimental results demonstrate that our SDV-LOAM ranks 8th on the KITTI odometry benchmark which outperforms most LiDAR/visual-LiDAR odometry systems. ...
Experimental results demonstrate that our SDV-LOAM ranks 8th on the KITTI odometry benchmark which outperforms most LiDAR/visual-LiDA …
Requirements for Automotive LiDAR Systems.
Dai Z, Wolf A, Ley PP, Glück T, Sundermeier MC, Lachmayer R. Dai Z, et al. Sensors (Basel). 2022 Oct 4;22(19):7532. doi: 10.3390/s22197532. Sensors (Basel). 2022. PMID: 36236631 Free PMC article.
Furthermore, the angular resolution limits are obtained utilizing the KITTI dataset and exemplary 3D detection algorithms. Finally, the maximum detection ranges for the different radiation patterns are compared under the consideration of derived requirements and laser safe …
Furthermore, the angular resolution limits are obtained utilizing the KITTI dataset and exemplary 3D detection algorithms. Finally, t …
Pedestrian and Vehicle Detection in Autonomous Vehicle Perception Systems-A Review.
Galvao LG, Abbod M, Kalganova T, Palade V, Huda MN. Galvao LG, et al. Sensors (Basel). 2021 Oct 31;21(21):7267. doi: 10.3390/s21217267. Sensors (Basel). 2021. PMID: 34770575 Free PMC article. Review.
Most of the algorithms have been tested on well-recognised datasets such as Caltech and KITTI; however, these datasets have their own limitations. Therefore, this paper recommends that future works should be implemented on more new challenging datasets, such as PIE and BDD …
Most of the algorithms have been tested on well-recognised datasets such as Caltech and KITTI; however, these datasets have their own …
SECOND: Sparsely Embedded Convolutional Detection.
Yan Y, Mao Y, Li B. Yan Y, et al. Sensors (Basel). 2018 Oct 6;18(10):3337. doi: 10.3390/s18103337. Sensors (Basel). 2018. PMID: 30301196 Free PMC article.
The proposed network produces state-of-the-art results on the KITTI 3D object detection benchmarks while maintaining a fast inference speed....
The proposed network produces state-of-the-art results on the KITTI 3D object detection benchmarks while maintaining a fast inference …
Small Object Detection in Traffic Scenes Based on YOLO-MXANet.
He X, Cheng R, Zheng Z, Wang Z. He X, et al. Sensors (Basel). 2021 Nov 8;21(21):7422. doi: 10.3390/s21217422. Sensors (Basel). 2021. PMID: 34770726 Free PMC article.
In addition, the SiLU activation function is utilized to optimize the Convolution-Batchnorm-Leaky ReLU (CBL) module and the SGBlock module to accelerate the convergence of the model. The ablation experiments on the KITTI dataset show that each improved method is effective. …
In addition, the SiLU activation function is utilized to optimize the Convolution-Batchnorm-Leaky ReLU (CBL) module and the SGBlock module t …
EEG source imaging in epilepsy--practicalities and pitfalls.
Kaiboriboon K, Lüders HO, Hamaneh M, Turnbull J, Lhatoo SD. Kaiboriboon K, et al. Nat Rev Neurol. 2012 Sep;8(9):498-507. doi: 10.1038/nrneurol.2012.150. Epub 2012 Aug 7. Nat Rev Neurol. 2012. PMID: 22868868 Review.
414 results