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] Type Year Filters: First Letter Of Last Name is G [Clear All Filters]
. Few-shot 3D Reconstruction of Body Parts with Deep Neural Networks. . Signal Theory and Communications. 2022.
. Fine-tuning a Convolutional Network for Cultural Event Recognition. . 2015. 
(11.14 MB)
(11.14 MB). Fine-tuning of CNN models for Instance Search with Pseudo-Relevance Feedback. Long Beach, CA, USA: NIPS 2017 Women in Machine Learning Workshop; 2017. (341.96 KB)
(341.96 KB). Flexible test-bed for unusual behavior detection. In 6th ACM International Conference on Image and Video Retrieval. 2007. pp. 105–108.
. Foreground objects segmentation for moving camera scenarios based on SCGMM. In Computational Intelligence for Multimedia Understanding. Berlin Heidelberg: Springer; 2012. pp. 195-206.
. Fourth-order statistics cost functions: applications to time delay estimation and image motion estimation. In VI SPANISH SYMPOSIUM ON PATTERN RECOGNITION AND IMAGE ANALYSIS. 1995. pp. 543–548.
. A framework for the retrieval of multiple regions using Binary Partition Trees and low level descriptors. In 11th European Signal Processing Conference, EUSIPCO 2002. Toulouse, France; 2002. pp. 512–516. (277.78 KB)
(277.78 KB). From Global Image Annotation to Interactive Object Segmentation. Multimedia Tools and Applications. 2014;70. (1.71 MB)
(1.71 MB). From Partition Trees to Semantic Trees. In International Workshop on Multimedia Content Representation, Classification and Security. 2006. pp. 306–313.
. From Partition Trees to Semantic Trees. In 2ndas Jornades UPC de Investigación en Automática, Visión y Robótica. 2006. pp. 187–194.
. From partition trees to semantic trees. In Multimedia Content Representation, Classification and Security. 2006. pp. 306–313. (966.49 KB)
(966.49 KB). From Pixels to Sentiment: Fine-tuning CNNs for Visual Sentiment Prediction. Image and Vision Computing. 2017;. (1.92 MB)
(1.92 MB). Fruit detection and 3D location using instance segmentation neural networks and structure-from-motion photogrammetry. Computers and Electronics in Agriculture. 2020;169.
. 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.
. Fruit Detection in an Apple Orchard Using a Mobile Terrestrial Laser Scanner. Biosystems Engineering. 2019;187.
. Fruit Detection Using Mobile Terrestrial Laser Scanning. In AgEng 2018,. Wageningen (Netherlands); 2018.
. Fruit Detection Using Mobile Terrestrial Laser Scanning. In AgEng 2018,. Wageningen (Netherlands); 2018.
. Fruit Detection Using Mobile Terrestrial Laser Scanning. In AgEng 2018,. Wageningen (Netherlands); 2018.
. 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).
. Functionalities for mapping 2D images and 3D world objects in a Multicamera Environment. In 6th International Workshop on Image Analysis for Multimedia Interactive Services. 2005. (198.67 KB)
(198.67 KB)