Modular Dynamic Neural Network: A Continual Learning Architecture
Learning to recognize a new object after having learned to recognize other objects may be a simple task for a human, but not for machines. The present go-to approaches for teaching a machine to recognize a set of objects are based on the use of deep neural networks (DNN). So, intuitively, the soluti...
Main Authors: | Daniel Turner, Pedro J. S. Cardoso, João M. F. Rodrigues |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2021-12-01
|
Series: | Applied Sciences |
Subjects: | |
Online Access: | https://www.mdpi.com/2076-3417/11/24/12078 |
Similar Items
-
Task-Similarity Guided Progressive Deep Neural Network and Its Learning
by: WU Chu, WANG Shitong
Published: (2023-05-01) -
Controlled Forgetting: Targeted Stimulation and Dopaminergic Plasticity Modulation for Unsupervised Lifelong Learning in Spiking Neural Networks
by: Jason M. Allred, et al.
Published: (2020-01-01) -
A Continual Learning Algorithm Based on Orthogonal Gradient Descent Beyond Neural Tangent Kernel Regime
by: Da Eun Lee, et al.
Published: (2023-01-01) -
Detecting Changes and Avoiding Catastrophic Forgetting in Dynamic Partially Observable Environments
by: Jeffery Dick, et al.
Published: (2020-12-01) -
Incremental Learning for Dermatological Imaging Modality Classification
by: Ana C. Morgado, et al.
Published: (2021-09-01)