Gemine Vivone
Media Technology · 2014–2023
A researcher in the Science corpus: 6 papers; trusts 47 researchers and is trusted by 4 researchers here, as inferred from the citation graph.
Subfields
- Media Technology — 127 citations into it; #2,103 of 3,621 by trust here, #809 by citations
- Computer Vision and Pattern Recognition — 121 citations into it; #14,015 of 21,575 by trust here, #8,831 by citations
- Artificial Intelligence — 14 citations into it
- Numerical Methods & Scientific Computing — 5 citations into it
Whom Gemine Vivone trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Luciano Alparone
- Andrea Garzelli
- Bruno Aiazzi
- Lucien Wald
- Thierry Ranchin
- Xavier Otazu
- Stéphane Mallat
- Stefano Baronti
- Filippo Nencini
- Jaewan Choi
Who trusts Gemine Vivone overall
- Liang-Jian Deng
- Giuseppe Masi
- Jiaxin Li
- Hassan Ghassemian
- Giuseppe Scarpa
- Jocelyn Chanussot
- Davide Cozzolino
- Xiao Qian
- Frosti Palsson
- Danfeng Hong
Papers from Gemine Vivone's perspective
Ordered by how strongly the researchers Gemine Vivone trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- ImageNet: A large-scale hierarchical image database
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Going deeper with convolutions
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Long Short-Term Memory
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Detail Injection-Based Deep Convolutional Neural Networks for Pansharpening (2021) — 311 citations
- A continual learning-guided training framework for pansharpening (2023)
- A New Benchmark Based on Recent Advances in Multispectral Pansharpening: Revisiting Pansharpening With Classical and Emerging Pansharpening Methods (2021) — 298 citations
- A Critical Comparison Among Pansharpening Algorithms (2015) — 1,223 citations
- Hyperspectral Pansharpening: A Review (2015) — 778 citations
- Contrast and Error-Based Fusion Schemes for Multispectral Image Pansharpening (2014) — 365 citations