AIMC Topic: Bayes Theorem

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Deep learning-based burned forest areas mapping via Sentinel-2 imagery: a comparative study.

Environmental science and pollution research international
In order to evaluate the effects of forest fires on the dynamics of the function and structure of ecosystems, it is necessary to determine burned forest areas with high accuracy, effectively, economically, and practically using satellite images. Extr...

Ridge regression and deep learning models for genome-wide selection of complex traits in New Mexican Chile peppers.

BMC genomic data
BACKGROUND: Genomewide prediction estimates the genomic breeding values of selection candidates which can be utilized for population improvement and cultivar development. Ridge regression and deep learning-based selection models were implemented for ...

Insight into Automatic Image Diagnosis of Ear Conditions Based on Optimized Deep Learning Approach.

Annals of biomedical engineering
Examining otoscopic images for ear diseases is necessary when the clinical diagnosis of ear diseases extracted from the knowledge of otolaryngologists is limited. Improved diagnosis approaches based on otoscopic image processing are urgently needed. ...

Toxicity prediction of nanoparticles using machine learning approaches.

Toxicology
Nanoparticle toxicity analysis is critical for evaluating the safety of nanomaterials due to their potential harm to the biological system. However, traditional experimental methods for evaluating nanoparticle toxicity are expensive and time-consumin...

Neuro-fuzzy modelling of a continuous stirred tank bioreactor with ceramic membrane technology for treating petroleum refinery effluent: a case study from Assam, India.

Bioprocess and biosystems engineering
A continuous stirred tank bioreactor (CSTB) with cell recycling combined with ceramic membrane technology and inoculated with Rhodococcus opacus PD630 was employed to treat petroleum refinery wastewater for simultaneous chemical oxygen demand (COD) r...

Evaluating the influence of road construction on landslide susceptibility in Saudi Arabia's mountainous terrain: a Bayesian-optimised deep learning approach with attention mechanism and sensitivity analysis.

Environmental science and pollution research international
In the mountainous region of Asir region of Saudi Arabia, road construction activities are closely associated with frequent landslides, posing significant risks to both human life and infrastructural development. This highlights an urgent need for a ...

Enhancing forensic investigations: Identifying bloodstains on various substrates through ATR-FTIR spectroscopy combined with machine learning algorithms.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
The forensic analysis of bloodstains on various substrates plays a crucial role in criminal investigations. This study presents a novel approach for analyzing bloodstains using Attenuated Total Reflectance Fourier Transform Infrared spectroscopy (ATR...

A new method for clustered survival data: Estimation of treatment effect heterogeneity and variable selection.

Biometrical journal. Biometrische Zeitschrift
We recently developed a new method random-intercept accelerated failure time model with Bayesian additive regression trees (riAFT-BART) to draw causal inferences about population treatment effect on patient survival from clustered and censored surviv...

Geographical discrimination of Asian red pepper powders using H NMR spectroscopy and deep learning-based convolution neural networks.

Food chemistry
This study investigated an innovative approach to discriminate the geographical origins of Asian red pepper powders by analyzing one-dimensional H NMR spectra through a deep learning-based convolution neural network (CNN). H NMR spectra were collecte...

Optimization of operational parameters using RSM, ANN, and SVM in membrane integrated with rotating biological contactor.

Chemosphere
Membrane fouling is a critical bottleneck to the widespread adoption of membrane separation processes. It diminishes the membrane permeability and results in high operational energy costs. The current study presents optimizing the operating parameter...