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Author Title [ Type] Year Filters: First Letter Of Last Name is R [Clear All Filters]
Fruit detection and 3D location using instance segmentation neural networks and structure-from-motion photogrammetry. Computers and Electronics in Agriculture. 2020;169.
. 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.
. FuCiTNet: Improving the generalization of deep learning networks by the fusion of learned class-inherent transformations. Information Fusion. 2020;63(195). (366.22 KB)
. FuCiTNet: Improving the generalization of deep learning networks by the fusion of learned class-inherent transformations. Information Fusion. 2020;63(195). (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.
. Geometric Model and Calibration Method for a Solid-State LiDAR. Sensors. 2020;20(10):2898.
. Gesture Control Interface for immersive panoramic displays. Multimedia Tools and Applications. 2013;:1-27.
. Gradient-Based Metrics for the Evaluation of Image Defogging. World Electric Vehicle Journal. 2023;14(9). (4.92 MB)
. Integration of audiovisual sensors and technologies in a smart room. Personal and ubiquitous computing. 2009;13:15–23. (477.45 KB)
. Introduction to the special issue: Egocentric Vision and Lifelogging. Journal of Visual Communication and Image Representation. 2018;. (116.21 KB)
. 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)
. 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)
. Looking behind occlusions: A study on amodal segmentation for robust on-tree apple fruit size estimation. Computers and Electronics in Agriculture. 2023;209. (9.02 MB)
. Looking behind occlusions: A study on amodal segmentation for robust on-tree apple fruit size estimation. Computers and Electronics in Agriculture. 2023;209. (9.02 MB)
. Morphological tools for robust key-region extraction and video shot modeling. Lecture notes in computer science. 2001;:407–416. (1.08 MB)
. Motion estimation using higher-order statistics. IEEE transactions on image processing. 1996;5:1077–1084.
. 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.
. Multiview depth coding based on combined color/depth segmentation. Journal of visual communication and image representation. 2012;23(1):42–52. (1.81 MB)
. New interaction modes for rich panoramic live video experiences. Behaviour & Information Technology. 2014;33(8).
. A Preliminary Study of Deep Learning Sensor Fusion for Pedestrian Detection. Sensors. 2023;23(8).
. Quantitative Ultrasound Texture Analysis of Fetal Lungs To Predict Neonatal Respiratory Morbidity. Ultrasound in Obstetrics and Gynecology, Wiley. 2015;45(4):427–433.
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