AIMC Topic: Neural Networks, Computer

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Automated Construction of Neural Network Potential Energy Surface: The Enhanced Self-Organizing Incremental Neural Network Deep Potential Method.

Journal of chemical information and modeling
In recent years, the use of deep learning (neural network) potential energy surface (NNPES) in molecular dynamics simulation has experienced explosive growth as it can be as accurate as quantum chemistry methods while being as efficient as classical ...

Adaptive Neural Network Control of Time Delay Teleoperation System Based on Model Approximation.

Sensors (Basel, Switzerland)
A bilateral neural network adaptive controller is designed for a class of teleoperation systems with constant time delay, external disturbance and internal friction. The stability of the teleoperation force feedback system with constant communication...

Towards Automated Analysis of Grain Spikes in Greenhouse Images Using Neural Network Approaches: A Comparative Investigation of Six Methods.

Sensors (Basel, Switzerland)
Automated analysis of small and optically variable plant organs, such as grain spikes, is highly demanded in quantitative plant science and breeding. Previous works primarily focused on the detection of prominently visible spikes emerging on the top ...

Towards Autonomous Drone Racing without GPU Using an OAK-D Smart Camera.

Sensors (Basel, Switzerland)
Recent advances have shown for the first time that it is possible to beat a human with an autonomous drone in a drone race. However, this solution relies heavily on external sensors, specifically on the use of a motion capture system. Thus, a truly a...

DeepFake electrocardiograms using generative adversarial networks are the beginning of the end for privacy issues in medicine.

Scientific reports
Recent global developments underscore the prominent role big data have in modern medical science. But privacy issues constitute a prevalent problem for collecting and sharing data between researchers. However, synthetic data generated to represent re...

Unsupervised deep learning identifies semantic disentanglement in single inferotemporal face patch neurons.

Nature communications
In order to better understand how the brain perceives faces, it is important to know what objective drives learning in the ventral visual stream. To answer this question, we model neural responses to faces in the macaque inferotemporal (IT) cortex wi...

Fully automated segmentation in temporal bone CT with neural network: a preliminary assessment study.

BMC medical imaging
BACKGROUND: Segmentation of important structures in temporal bone CT is the basis of image-guided otologic surgery. Manual segmentation of temporal bone CT is time- consuming and laborious. We assessed the feasibility and generalization ability of a ...

Dynamic stochastic deep learning approaches for predicting geometric changes in head and neck cancer.

Physics in medicine and biology
Modern radiotherapy stands to benefit from the ability to efficiently adapt plans during treatment in response to setup and geometric variations such as those caused by internal organ deformation or tumor shrinkage. A promising strategy is to develop...

Neural network features distinguish chemosensory stimuli in Caenorhabditis elegans.

PLoS computational biology
Nervous systems extract and process information from the environment to alter animal behavior and physiology. Despite progress in understanding how different stimuli are represented by changes in neuronal activity, less is known about how they affect...

Deep Learning Algorithm for COVID-19 Classification Using Chest X-Ray Images.

Computational and mathematical methods in medicine
Early diagnosis of the harmful severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), along with clinical expertise, allows governments to break the transition chain and flatten the epidemic curve. Although reverse transcription-polymerase cha...