AI Medical Compendium Topic:
Learning

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Test Strategy Optimization Based on Soft Sensing and Ensemble Belief Measurement.

Sensors (Basel, Switzerland)
Resulting from the short production cycle and rapid design technology development, traditional prognostic and health management (PHM) approaches become impractical and fail to match the requirement of systems with structural and functional complexity...

Lifelong 3D object recognition and grasp synthesis using dual memory recurrent self-organization networks.

Neural networks : the official journal of the International Neural Network Society
Humans learn to recognize and manipulate new objects in lifelong settings without forgetting the previously gained knowledge under non-stationary and sequential conditions. In autonomous systems, the agents also need to mitigate similar behaviour to ...

Learning online visual invariances for novel objects via supervised and self-supervised training.

Neural networks : the official journal of the International Neural Network Society
Humans can identify objects following various spatial transformations such as scale and viewpoint. This extends to novel objects, after a single presentation at a single pose, sometimes referred to as online invariance. CNNs have been proposed as a c...

Effective Transfer Learning with Label-Based Discriminative Feature Learning.

Sensors (Basel, Switzerland)
The performance of natural language processing with a transfer learning methodology has improved by applying pre-training language models to downstream tasks with a large number of general data. However, because the data used in pre-training are irre...

Intelligent virtual case learning system based on real medical records and natural language processing.

BMC medical informatics and decision making
BACKGROUND: Modernizing medical education by using artificial intelligence and other new technologies to improve the clinical thinking ability of medical students is an important research topic in recent years. Prominent medical universities are acti...

Universality of gradient descent neural network training.

Neural networks : the official journal of the International Neural Network Society
It has been observed that design choices of neural networks are often crucial for their successful optimization. In this article, we therefore discuss the question if it is always possible to redesign a neural network so that it trains well with grad...

On the Post Hoc Explainability of Optimized Self-Organizing Reservoir Network for Action Recognition.

Sensors (Basel, Switzerland)
This work proposes a novel unsupervised self-organizing network, called the Self-Organizing Convolutional Echo State Network (SO-ConvESN), for learning node centroids and interconnectivity maps compatible with the deterministic initialization of Echo...

Synaptic Learning With Augmented Spikes.

IEEE transactions on neural networks and learning systems
Traditional neuron models use analog values for information representation and computation, while all-or-nothing spikes are employed in the spiking ones. With a more brain-like processing paradigm, spiking neurons are more promising for improvements ...

SMGEA: A New Ensemble Adversarial Attack Powered by Long-Term Gradient Memories.

IEEE transactions on neural networks and learning systems
Deep neural networks are vulnerable to adversarial attacks. More importantly, some adversarial examples crafted against an ensemble of source models transfer to other target models and, thus, pose a security threat to black-box applications (when att...

A novel convolutional neural network for kidney ultrasound images segmentation.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Ultrasound imaging has been widely used in the screening of kidney diseases. The localization and segmentation of the kidneys in ultrasound images are helpful for the clinical diagnosis of diseases. However, it is a challeng...