AIMC Topic: Reproducibility of Results

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Compact artificial neuron based on anti-ferroelectric transistor.

Nature communications
Neuromorphic machines are intriguing for building energy-efficient intelligent systems, where spiking neurons are pivotal components. Recently, memristive neurons with promising bio-plausibility have been developed, but with limited reliability, bulk...

Embedding Weather Simulation in Auto-Labelling Pipelines Improves Vehicle Detection in Adverse Conditions.

Sensors (Basel, Switzerland)
The performance of deep learning-based detection methods has made them an attractive option for robotic perception. However, their training typically requires large volumes of data containing all the various situations the robots may potentially enco...

Numerical performances through artificial neural networks for solving the vector-borne disease with lifelong immunity.

Computer methods in biomechanics and biomedical engineering
The current study is related to solve a nonlinear vector-borne disease with a lifelong immunity model (VDLIM) by designing a computational stochastic framework using the strength of artificial Levenberg-Marquardt backpropagation neural network (ALMBN...

Design exploration and comparative analysis of tail shape of tri-wheel-based stair-climbing robotic platform.

Scientific reports
Stair climbing is one of the most important capabilities of mobile robots. Therefore, stair-climbing mobile robots have become a field of study and diverse stair-climbing mobile robots have been developed. Although tri-wheel-based stair-climbing robo...

Recognition of the Effect of Vocal Exercises by Fuzzy Triangular Naive Bayes, a Machine Learning Classifier: A Preliminary Analysis.

Journal of voice : official journal of the Voice Foundation
OBJECTIVES: Machine learning (ML) methods allow the development of expert systems for pattern recognition and predictive analysis of intervention outcomes. It has been used in Voice Sciences, mainly to discriminate between healthy and dysphonic voice...

Assessment of Thermal Damage from Robot-Drilled Craniotomy for Cranial Window Surgery in Mice.

Journal of visualized experiments : JoVE
Cranial window surgery allows for the imaging of brain tissue in live mice with the use of multiphoton or other intravital imaging techniques. However, when performing any craniotomy by hand, there is often thermal damage to brain tissue, which is in...

Deep learning-based harmonization of CT reconstruction kernels towards improved clinical task performance.

European radiology
OBJECTIVES: To develop a deep learning-based harmonization framework, assessing whether it can improve performance of radiomics models given different kernels in different clinical tasks and additionally generalize to mitigate the effects of new/unob...

Quantifying the Severity of Metopic Craniosynostosis Using Unsupervised Machine Learning.

Plastic and reconstructive surgery
BACKGROUND: Quantifying the severity of head shape deformity and establishing a threshold for operative intervention remains challenging in patients with metopic craniosynostosis (MCS). This study combines three-dimensional skull shape analysis with ...

Automated Detection of Cerebral Aneurysms on TOF-MRA Using a Deep Learning Approach: An External Validation Study.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Cerebral aneurysms yield the risk of rupture, severe disability and death. Thus, early detection of cerebral aneurysms is crucial to ensure timely treatment, if necessary. AI-based software tools are expected to enhance radiol...

Deep learning-based quantification of NAFLD/NASH progression in human liver biopsies.

Scientific reports
Non-alcoholic fatty liver disease (NAFLD) affects about 24% of the world's population. Progression of early stages of NAFLD can lead to the more advanced form non-alcoholic steatohepatitis (NASH), and ultimately to cirrhosis or liver cancer. The curr...