Search Publication
Export 249 results:
Author Title Type [ Year
] Filters: First Letter Of Last Name is R [Clear All Filters]
. FuCiTNet: Improving the generalization of deep learning networks by the fusion of learned class-inherent transformations. Information Fusion. 2020;63(195). 
(366.22 KB)
(366.22 KB). Fuji-SfM dataset: A collection of annotated images and point clouds for Fuji apple detection and location using structure-from-motion photogrammetry. 2020;Data in Brief(Vol. 30).
. Fuji-SfM dataset: A collection of annotated images and point clouds for Fuji apple detection and location using structure-from-motion photogrammetry. 2020;Data in Brief(Vol. 30).
. Geometric Model and Calibration Method for a Solid-State LiDAR. Sensors. 2020;20(10):2898. (3.37 MB)
(3.37 MB). Geometric Model and Calibration Method for a Solid-State LiDAR. Sensors. 2020;20(10):2898. (3.37 MB)
(3.37 MB). Learning to extract features for 2D-3D multimodal registration. . Universitat Politècnica de Catalunya (UPC); 2020. (14.22 MB)
(14.22 MB). BCN20000: Dermoscopic Lesions in the Wild. In International Skin Imaging Collaboration (ISIC) Challenge on Dermoscopic Skin Lesion Analysis 2019. 2019.
. BCN20000: Dermoscopic Lesions in the Wild. In International Skin Imaging Collaboration (ISIC) Challenge on Dermoscopic Skin Lesion Analysis 2019. 2019.
. Correspondence matching in unorganized 3D point clouds using Convolutional Neural Networks. Image and Vision Computing. 2019;83-84. (3.95 MB)
(3.95 MB). Differential expression of long non-coding RNAs related to proliferation and histological diversity in follicular lymphomas. British Journal of Haematology. 2019;184(3):373-383. (980.9 KB)
(980.9 KB). Differential expression of long non-coding RNAs related to proliferation and histological diversity in follicular lymphomas. British Journal of Haematology. 2019;184(3):373-383. (980.9 KB)
(980.9 KB). Fruit Detection in an Apple Orchard Using a Mobile Terrestrial Laser Scanner. Biosystems Engineering. 2019;187.
. Fruit Detection in an Apple Orchard Using a Mobile Terrestrial Laser Scanner. Biosystems Engineering. 2019;187.
. A Generative Dialogue System for Reminiscence Therapy. . 2019. (4.89 MB)
(4.89 MB). Hyperparameter-Free Losses for Model-Based Monocular Reconstruction. In ICCV 2019 Workshop on Geometry Meets Deep Learning. Seoul, South Corea: IEEE / Computer Vision Foundation; 2019. (749.7 KB)
(749.7 KB). Hyperparameter-Free Losses for Model-Based Monocular Reconstruction. In ICCV 2019 Workshop on Geometry Meets Deep Learning. Seoul, South Corea: IEEE / Computer Vision Foundation; 2019. (749.7 KB)
(749.7 KB). Inverse Cooking: Recipe Generation from Food Images. In CVPR. Long Beach, CA, USA: OpenCVF / IEEE; 2019.
. KFuji RGB-DS database: Fuji apple multi-modal images for fruit detection with color, depth and range-corrected IR data. Data in Brief. 2019;. (2.43 MB)
(2.43 MB). KFuji RGB-DS database: Fuji apple multi-modal images for fruit detection with color, depth and range-corrected IR data. Data in Brief. 2019;. (2.43 MB)
(2.43 MB). Multi-modal Deep Learning for Fuji Apple Detection Using RGB-D Cameras and their Radiometric Capabilities. Computers and Electronics in Agriculture. 2019;162.
. Multi-modal Deep Learning for Fuji Apple Detection Using RGB-D Cameras and their Radiometric Capabilities. Computers and Electronics in Agriculture. 2019;162.
. Multi-View 3D Face Reconstruction in the Wild using Siamese Networks. In ICCV 2019 Workshop on 3D Face Alignment in the Wild Challenge Workshop (3DFAW). Seoul, South Corea: IEEE/CVF; 2019. (227.12 KB)
(227.12 KB). Plug-and-Train Loss for Model-Based Single View 3D Reconstruction. BMVA Technical Meeting: 3D vision with Deep Learning. London, UK: UPC; 2019. (3.97 MB)
(3.97 MB). Plug-and-Train Loss for Model-Based Single View 3D Reconstruction. BMVA Technical Meeting: 3D vision with Deep Learning. London, UK: UPC; 2019. (3.97 MB)
(3.97 MB)