Francesca Bovolo
Media Technology · 2005–2019
A researcher in the Science corpus: 10 papers; trusts 132 researchers and is trusted by 55 researchers here, as inferred from the citation graph.
Subfields
- Media Technology — 108 citations into it; #194 of 3,621 by trust here, #470 by citations
- Computer Vision and Pattern Recognition — 74 citations into it; #14,927 of 21,575 by trust here, #19,310 by citations
- Ecology — 47 citations into it; #792 of 10,717 by trust here, #5,318 by citations
- Atmospheric Science — 34 citations into it; #136 of 4,804 by trust here, #950 by citations
- Artificial Intelligence — 29 citations into it; #11,409 of 35,345 by trust here, #20,377 by citations
- Aerospace Engineering — 21 citations into it; #1,798 of 6,421 by trust here, #4,762 by citations
- Analytical Chemistry — 19 citations into it; #337 of 1,254 by trust here, #498 by citations
- Environmental Engineering — 11 citations into it
Whom Francesca Bovolo trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Lorenzo Bruzzone
- Allan Aasbjerg Nielsen
- Diego Fernández-Prieto
- Turgay Çelik
- Yuhai Wu
- Dustin Boswell
- Arthur P. Dempster
- Dengsheng Lu
- Fabrizio Argenti
- Paul L. Rosin
Who trusts Francesca Bovolo overall
- Lorenzo Bruzzone
- Turgay Çelik
- Sicong Liu
- Sudipan Saha
- A. Tewkesbury
- Lichao Mou
- Daifeng Peng
- Chen Wu
- Rodrigo Caye Daudt
- Bo Du
Papers from Francesca Bovolo's perspective
Ordered by how strongly the researchers Francesca Bovolo trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Going deeper with convolutions
- Distinctive Image Features from Scale-Invariant Keypoints
Their papers
- Fast and Robust Matching for Multimodal Remote Sensing Image Registration (2019) — 310 citations
- A Review of Change Detection in Multitemporal Hyperspectral Images: Current Techniques, Applications, and Challenges (2019) — 351 citations
- Unsupervised Deep Change Vector Analysis for Multiple-Change Detection in VHR Images (2019) — 489 citations
- Multisource and Multitemporal Data Fusion in Remote Sensing: A Comprehensive Review of the State of the Art (2019) — 393 citations
- A Novel Framework for the Design of Change-Detection Systems for Very-High-Resolution Remote Sensing Images (2013) — 319 citations
- A Framework for Automatic and Unsupervised Detection of Multiple Changes in Multitemporal Images (2012) — 310 citations
- A Novel Approach to Unsupervised Change Detection Based on a Semisupervised SVM and a Similarity Measure (2008) — 300 citations
- A Split-Based Approach to Unsupervised Change Detection in Large-Size Multitemporal Images: Application to Tsunami-Damage Assessment (2007) — 298 citations
- A Theoretical Framework for Unsupervised Change Detection Based on Change Vector Analysis in the Polar Domain (2007) — 643 citations
- A detail-preserving scale-driven approach to change detection in multitemporal SAR images (2005) — 422 citations