AIMC Topic: Neural Networks, Computer

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Neural knowledge assembly in humans and neural networks.

Neuron
Human understanding of the world can change rapidly when new information comes to light, such as when a plot twist occurs in a work of fiction. This flexible "knowledge assembly" requires few-shot reorganization of neural codes for relations among ob...

Deep Neural Networks-Based Age Estimation of Cadavers Using CT Imaging of Vertebrae.

International journal of environmental research and public health
Although age estimation upon death is important in the identification of unknown cadavers for forensic scientists, to the best of our knowledge, no study has examined the utility of deep neural network (DNN) models for age estimation among cadavers. ...

RiRPSSP: A unified deep learning method for prediction of regular and irregular protein secondary structures.

Journal of bioinformatics and computational biology
Protein secondary structure prediction (PSSP) is an important and challenging task in protein bioinformatics. Protein secondary structures (SSs) are categorized in regular and irregular structure classes. Regular SSs, representing nearly 50% of amino...

Toward explainable AI-empowered cognitive health assessment.

Frontiers in public health
Explainable artificial intelligence (XAI) is of paramount importance to various domains, including healthcare, fitness, skill assessment, and personal assistants, to understand and explain the decision-making process of the artificial intelligence (A...

Object Detection Based on Swin Deformable Transformer-BiPAFPN-YOLOX.

Computational intelligence and neuroscience
Object detection technology plays a crucial role in people's everyday lives, as well as enterprise production and modern national defense. Most current object detection networks, such as YOLOX, employ convolutional neural networks instead of a Transf...

An analysis of crude oil prices in the last decade (2011-2020): With deep learning approach.

PloS one
Crude Oil is one of the most important commodities in this world. We have studied the effects of Crude Oil inventories on crude oil prices over the last ten years (2011 to 2020). We tried to figure out how the Crude Oil price variance responds to inv...

Not getting in too deep: A practical deep learning approach to routine crystallisation image classification.

PloS one
Using a relatively small training set of ~16 thousand images from macromolecular crystallisation experiments, we compare classification results obtained with four of the most widely-used convolutional deep-learning network architectures that can be i...

Bounded synchronization for uncertain master-slave neural networks: An adaptive impulsive control approach.

Neural networks : the official journal of the International Neural Network Society
This paper investigates the bounded synchronization of the discrete-time master-slave neural networks (MSNNs) with uncertainty. To deal with the unknown parameter in the MSNNs, a parameter adaptive law combined with the impulsive mechanism is propose...

Automatic Detection of Alzheimer's Disease using Deep Learning Models and Neuro-Imaging: Current Trends and Future Perspectives.

Neuroinformatics
Deep learning algorithms have a huge influence on tackling research issues in the field of medical image processing. It acts as a vital aid for the radiologists in producing accurate results toward effective disease diagnosis. The objective of this r...

A Novel IoT-Enabled Healthcare Monitoring Framework and Improved Grey Wolf Optimization Algorithm-Based Deep Convolution Neural Network Model for Early Diagnosis of Lung Cancer.

Sensors (Basel, Switzerland)
Lung cancer is a high-risk disease that causes mortality worldwide; nevertheless, lung nodules are the main manifestation that can help to diagnose lung cancer at an early stage, lowering the workload of radiologists and boosting the rate of diagnosi...