AIMC Topic: Neural Networks, Computer

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Abstract representations emerge naturally in neural networks trained to perform multiple tasks.

Nature communications
Humans and other animals demonstrate a remarkable ability to generalize knowledge across distinct contexts and objects during natural behavior. We posit that this ability to generalize arises from a specific representational geometry, that we call ab...

Increasing transparency in machine learning through bootstrap simulation and shapely additive explanations.

PloS one
Machine learning methods are widely used within the medical field. However, the reliability and efficacy of these models is difficult to assess, making it difficult for researchers to identify which machine-learning model to apply to their dataset. W...

Decoupled neural network training with re-computation and weight prediction.

PloS one
To break the three lockings during backpropagation (BP) process for neural network training, multiple decoupled learning methods have been investigated recently. These methods either lead to significant drop in accuracy performance or suffer from dra...

An artificial neural network-based data filling approach for smart operation of digital wastewater treatment plants.

Environmental research
With the prevalence of digitization, smart operation has become mainstream in future wastewater treatment plants. This requires substantial and complete historical data for model construction. However, the data collected from the front-end sensor con...

Bayesian inference in ring attractor networks.

Proceedings of the National Academy of Sciences of the United States of America
Working memories are thought to be held in attractor networks in the brain. These attractors should keep track of the uncertainty associated with each memory, so as to weigh it properly against conflicting new evidence. However, conventional attracto...

In-Bed Posture Classification Using Deep Neural Network.

Sensors (Basel, Switzerland)
In-bed posture monitoring has become a prevalent area of research to help minimize the risk of pressure sore development and to increase sleep quality. This paper proposed 2D and 3D Convolutional Neural Networks, which are trained on images and video...

Use of Artificial Intelligence in the Classification of Elementary Oral Lesions from Clinical Images.

International journal of environmental research and public health
OBJECTIVES: Artificial intelligence has generated a significant impact in the health field. The aim of this study was to perform the training and validation of a convolutional neural network (CNN)-based model to automatically classify six clinical re...

Pill Box Text Identification Using DBNet-CRNN.

International journal of environmental research and public health
The recognition process of natural scenes is complicated at present, and images themselves may be complex owing to the special features of natural scenes. In this study, we use the detection and recognition of pill box text as an application scenario...

Neural stochastic differential equations network as uncertainty quantification method for EEG source localization.

Biomedical physics & engineering express
EEG source localization remains a challenging problem given the uncertain conductivity values of the volume conductor models (VCMs). As uncertain conductivities vary across people, they may considerably impact the forward and inverse solutions of the...

Classifying aneuploidy in genotype intensity data using deep learning.

Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie
Aneuploidy is the loss or gain of one or more chromosomes. Although it is a rare phenomenon in liveborn individuals, it is observed in livestock breeding populations. These breeding populations are often routinely genotyped and the genotype intensity...