Daniele Palossi
Computer Vision and Pattern Recognition · 2016–2018
A researcher in the Science corpus: 5 papers; trusts 7 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 34 citations into it
- Aerospace Engineering — 29 citations into it
- Electrical and Electronic Engineering — 18 citations into it
- Hardware and Architecture — 11 citations into it
- Artificial Intelligence — 8 citations into it
Whom Daniele Palossi trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Adrien Briod
- Francesco Conti
- Luca Benini
- Kimberly N. McGuire
- Davide Scaramuzza
- Jean-Christophe Zufferey
- Dario Floreano
- Davide Falanga
- Andrea Marongiu
- Chih-Jen Lin
Who trusts Daniele Palossi overall
Papers from Daniele Palossi's perspective
Ordered by how strongly the researchers Daniele Palossi 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
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
- Attention is All you Need (Neural Information Processing Systems)
- Learning Multiple Layers of Features from Tiny Images
Their papers
- Enabling the heterogeneous accelerator model on ultra-low power microcontroller platforms (2016) — 24 citations
- Extending the Lifetime of Nano-Blimps via Dynamic Motor Control (2018) — 21 citations
- A 64-mW DNN-Based Visual Navigation Engine for Autonomous Nano-Drones (2018) — 173 citations
- Target following on nano-scale Unmanned Aerial Vehicles (2017) — 21 citations
- Ultra low-power visual odometry for nano-scale unmanned aerial vehicles (2017) — 16 citations