Abstract | ||
---|---|---|
•Neural architecture search addressed with Genetic Programming and Backpropagation.•Genetic Programming efficiently provides blueprints for neural network architectures.•Backpropagation significantly improves the performance of candidate blueprints.•Proper fusion of hand-crafted saliency methods can outperform deep learning methods.•Proper fusion of deep learning methods outperforms the state of the art. |
Year | DOI | Venue |
---|---|---|
2020 | 10.1016/j.inffus.2019.12.007 | Information Fusion |
Keywords | Field | DocType |
Saliency fusion,Evolutionary algorithms,Neural architecture search | Open problem,Evolutionary algorithm,Salience (neuroscience),Convolutional neural network,Genetic programming,Exploit,Artificial intelligence,Backpropagation,Artificial neural network,Machine learning,Mathematics | Journal |
Volume | ISSN | Citations |
57 | 1566-2535 | 2 |
PageRank | References | Authors |
0.35 | 0 | 4 |
Name | Order | Citations | PageRank |
---|---|---|---|
Simone Bianco | 1 | 226 | 24.48 |
Marco Buzzelli | 2 | 29 | 4.91 |
Gianluigi Ciocca | 3 | 364 | 33.44 |
Raimondo Schettini | 4 | 1476 | 154.06 |