AIMC Topic: Machine Learning

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Evaluation of Open-Source and Pre-Trained Deep Convolutional Neural Networks Suitable for Player Detection and Motion Analysis in Squash.

Sensors (Basel, Switzerland)
In sport science, athlete tracking and motion analysis are essential for monitoring and optimizing training programs, with the goal of increasing success in competition and preventing injury. At present, contact-free, camera-based, multi-athlete dete...

Diagnostic of Operation Conditions and Sensor Faults Using Machine Learning in Sucker-Rod Pumping Wells.

Sensors (Basel, Switzerland)
In sucker-rod pumping wells, due to the lack of an early diagnosis of operating condition or sensor faults, several problems can go unnoticed. These problems can increase downtime and production loss. In these wells, the diagnosis of operation condit...

Systematic Review of Electricity Demand Forecast Using ANN-Based Machine Learning Algorithms.

Sensors (Basel, Switzerland)
The forecast of electricity demand has been a recurrent research topic for decades, due to its economical and strategic relevance. Several Machine Learning (ML) techniques have evolved in parallel with the complexity of the electric grid. This paper ...

Machine learning reveals sequence-function relationships in family 7 glycoside hydrolases.

The Journal of biological chemistry
Family 7 glycoside hydrolases (GH7) are among the principal enzymes for cellulose degradation in nature and industrially. These enzymes are often bimodular, including a catalytic domain and carbohydrate-binding module (CBM) attached via a flexible li...

In silico prediction of chemical-induced hematotoxicity with machine learning and deep learning methods.

Molecular diversity
Chemical-induced hematotoxicity is an important concern in the drug discovery, since it can often be fatal when it happens. It is quite useful for us to give special attention to chemicals which can cause hematotoxicity. In the present study, we focu...

Deep Learning Based Prediction on Greenhouse Crop Yield Combined TCN and RNN.

Sensors (Basel, Switzerland)
Currently, greenhouses are widely applied for plant growth, and environmental parameters can also be controlled in the modern greenhouse to guarantee the maximum crop yield. In order to optimally control greenhouses' environmental parameters, one ind...

Machine Learning Methods for Fear Classification Based on Physiological Features.

Sensors (Basel, Switzerland)
This paper focuses on the binary classification of the emotion of fear, based on the physiological data and subjective responses stored in the DEAP dataset. We performed a mapping between the discrete and dimensional emotional information considering...