TY - GEN
T1 - A Survey on Few-Shot Techniques in the Context of Computer Vision Applications Based on Deep Learning
AU - San-Emeterio, Miguel G.
N1 - Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2022
Y1 - 2022
N2 - This review article about Few-Shot Learning techniques is focused on Computer Vision Applications based on Deep Convolutional Neural Networks. A general discussion about Few-Shot Learning is given, featuring a context-constrained description, a short list of applications, a description of a couple of commonly used techniques and a discussion of the most used benchmarks for FSL computer vision applications. In addition, the paper features a few examples of recent publications in which FSL techniques are used for training models in the context of Human Behaviour Analysis and Smart City Environment Safety. These examples give some insight about the performance of state-of-the-art FSL algorithms, what metrics do they achieve, and how many samples are needed for accomplishing that.
AB - This review article about Few-Shot Learning techniques is focused on Computer Vision Applications based on Deep Convolutional Neural Networks. A general discussion about Few-Shot Learning is given, featuring a context-constrained description, a short list of applications, a description of a couple of commonly used techniques and a discussion of the most used benchmarks for FSL computer vision applications. In addition, the paper features a few examples of recent publications in which FSL techniques are used for training models in the context of Human Behaviour Analysis and Smart City Environment Safety. These examples give some insight about the performance of state-of-the-art FSL algorithms, what metrics do they achieve, and how many samples are needed for accomplishing that.
KW - Computer Vision
KW - Deep Learning
KW - Few-Shot Learning
KW - Human Behaviour Analysis
KW - Smart City Environment Safety
UR - https://www.scopus.com/pages/publications/85136140906
U2 - 10.1007/978-3-031-13324-4_2
DO - 10.1007/978-3-031-13324-4_2
M3 - Conference contribution
AN - SCOPUS:85136140906
SN - 9783031133237
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 14
EP - 25
BT - Image Analysis and Processing. ICIAP 2022 Workshops - ICIAP International Workshops, Revised Selected Papers
A2 - Mazzeo, Pier Luigi
A2 - Distante, Cosimo
A2 - Frontoni, Emanuele
A2 - Sclaroff, Stan
PB - Springer Science and Business Media Deutschland GmbH
T2 - 21st International Conference on Image Analysis and Processing , ICIAP 2022
Y2 - 23 May 2022 through 27 May 2022
ER -
