AIMC Topic: Algorithms

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Industrial equipment detection algorithm under complex working conditions based on ROMS R-CNN.

PloS one
In the paper, we proposed a deep learning-based industrial equipment detection algorithm ROMS R-CNN (Rotation Occlusion Multi-Scale Region-CNN). It can solve the problem of inaccurate detection of industrial equipment under complex working conditions...

Improving the quality of predictive models in small data GSDOT: A new algorithm for generating synthetic data.

PloS one
In the age of the data deluge there are still many domains and applications restricted to the use of small datasets. The ability to harness these small datasets to solve problems through the use of supervised learning methods can have a significant i...

Interpretation of ensemble learning to predict water quality using explainable artificial intelligence.

The Science of the total environment
Algal bloom is a significant issue when managing water quality in freshwater; specifically, predicting the concentration of algae is essential to maintaining the safety of the drinking water supply system. The chlorophyll-a (Chl-a) concentration is a...

FM-Net: Deep Learning Network for the Fundamental Matrix Estimation from Biplanar Radiographs.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The fundamental matrix estimation is a classic problem in computer vision. The traditional algorithms require high-precision correspondences. However, correspondences in biplanar radiographs are difficult to match accurately...

Zero-Day Malware Detection and Effective Malware Analysis Using Shapley Ensemble Boosting and Bagging Approach.

Sensors (Basel, Switzerland)
Software products from all vendors have vulnerabilities that can cause a security concern. Malware is used as a prime exploitation tool to exploit these vulnerabilities. Machine learning (ML) methods are efficient in detecting malware and are state-o...

A Neural Network-Based Model for Predicting Saybolt Color of Petroleum Products.

Sensors (Basel, Switzerland)
Saybolt color is a standard measurement scale used to determine the quality of petroleum products and the appropriate refinement process. However, the current color measurement methods are mostly laboratory-based, thereby consuming much time and bein...

Deep learning to enable color vision in the dark.

PloS one
Humans perceive light in the visible spectrum (400-700 nm). Some night vision systems use infrared light that is not perceptible to humans and the images rendered are transposed to a digital display presenting a monochromatic image in the visible spe...

Machine Learning for the Orthopaedic Surgeon: Uses and Limitations.

The Journal of bone and joint surgery. American volume
➤: Machine learning is a subset of artificial intelligence in which computer algorithms are trained to make classifications and predictions based on patterns in data. The utilization of these techniques is rapidly expanding in the field of orthopaedi...

MFPS_CNN: Multi-filter Pattern Scanning from Position-specific Scoring Matrix with Convolutional Neural Network for Efficient Prediction of Ion Transporters.

Molecular informatics
In cellular transportation mechanisms, the movement of ions across the cell membrane and its proper control are important for cells, especially for life processes. Ion transporters/pumps and ion channel proteins work as border guards controlling the ...

A Challenge for Emphysema Quantification Using a Deep Learning Algorithm With Low-dose Chest Computed Tomography.

Journal of thoracic imaging
PURPOSE: We aimed to identify clinically relevant deep learning algorithms for emphysema quantification using low-dose chest computed tomography (LDCT) through an invitation-based competition.