Testing deep neural networks
Deep neural networks (DNNs) have a wide range of applications, and software employing
them must be thoroughly tested, especially in safety-critical domains. However, traditional …
them must be thoroughly tested, especially in safety-critical domains. However, traditional …
An efficient multi-level convolutional neural network approach for white blood cells classification
The evaluation of white blood cells is essential to assess the quality of the human immune
system; however, the assessment of the blood smear depends on the pathologist's …
system; however, the assessment of the blood smear depends on the pathologist's …
Catastrophic forgetting in deep learning: A comprehensive taxonomy
Deep Learning models have achieved remarkable performance in tasks such as image
classification or generation, often surpassing human accuracy. However, they can struggle …
classification or generation, often surpassing human accuracy. However, they can struggle …
Incremental learning using generative-rehearsal strategy for fault detection and classification
S Lee, K Chang, JG Baek - Expert Systems with Applications, 2021 - Elsevier
In this study, we propose a novel pseudorehearsal method for modeling fault detection and
classification. As manufacturing processes become increasingly advanced, it is often …
classification. As manufacturing processes become increasingly advanced, it is often …
Self-improving generative artificial neural network for pseudorehearsal incremental class learning
Deep learning models are part of the family of artificial neural networks and, as such, they
suffer catastrophic interference when learning sequentially. In addition, the greater number …
suffer catastrophic interference when learning sequentially. In addition, the greater number …
Human-inspired Perspectives: A Survey on AI Long-term Memory
With the rapid advancement of AI systems, their abilities to store, retrieve, and utilize
information over the long term-referred to as long-term memory-have become increasingly …
information over the long term-referred to as long-term memory-have become increasingly …
Locally weighted regression pseudo-rehearsal for online learning of vehicle dynamics
We consider the problem of online adaptation of a neural network designed to represent
vehicle dynamics. The neural network model is intended to be used by an MPC control law …
vehicle dynamics. The neural network model is intended to be used by an MPC control law …
Locally weighted regression pseudo-rehearsal for adaptive model predictive control
We consider the problem of online adaptation of a neural network designed to represent
system dynamics. The neural network model is intended to be used by an MPC control law …
system dynamics. The neural network model is intended to be used by an MPC control law …
Catastrophic Forgetting in Deep Learning: A Comprehensive Taxonomy
Deep Learning models have achieved remarkable performance in tasks such as image
classification or generation, often surpassing human accuracy. However, they can struggle …
classification or generation, often surpassing human accuracy. However, they can struggle …
Generative pseudorehearsal strategy for fault classification under an incremental learning
S Lee, JG Baek - … Science and Engineering (CSE) and IEEE …, 2019 - ieeexplore.ieee.org
As fault classification becomes more important in manufacturing industry, the state-of-art
machine learning methods have been utilized. However, owing to the problem called …
machine learning methods have been utilized. However, owing to the problem called …