AIMC Topic: Algorithms

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A novel approach exploiting properties of convolutional neural networks for vessel movement anomaly detection and classification.

ISA transactions
The article concerns the automation of vessel movement anomaly detection for maritime and coastal traffic safety services. Deep Learning techniques, specifically Convolutional Neural Networks (CNNs), were used to solve this problem. Three variants of...

On kernel machine learning for propensity score estimation under complex confounding structures.

Pharmaceutical statistics
Post marketing data offer rich information and cost-effective resources for physicians and policy-makers to address some critical scientific questions in clinical practice. However, the complex confounding structures (e.g., nonlinear and nonadditive ...

Application of Deep Learning for Diagnosing, Classifying, and Treating Age-Related Macular Degeneration.

Seminars in ophthalmology
Age-related macular degeneration (AMD) affects nearly 200 million people and is the third leading cause of irreversible vision loss worldwide. Deep learning, a branch of artificial intelligence that can learn image recognition based on pre-existing d...

ScatT-LOOP: scattering tetrolet-LOOP descriptor and optimized NN for iris recognition at-a-distance.

Biomedizinische Technik. Biomedical engineering
Iris Recognition at-a Distance (IAAD) is a major challenge for researchers due to the defects associated with the visual imaging and poor image quality in dynamic environments, which imposed bad impacts on the accuracy of recognition. Thus, in order ...

A Machine Learning Processing Pipeline for Reliable Hand Gesture Classification of FMG Signals with Stochastic Variance.

Sensors (Basel, Switzerland)
ForceMyography (FMG) is an emerging competitor to surface ElectroMyography (sEMG) for hand gesture recognition. Most of the state-of-the-art research in this area explores different machine learning algorithms or feature engineering to improve hand g...

Rapid 3D phenotypic analysis of neurons and organoids using data-driven cell segmentation-free machine learning.

PLoS computational biology
Phenotypic profiling of large three-dimensional microscopy data sets has not been widely adopted due to the challenges posed by cell segmentation and feature selection. The computational demands of automated processing further limit analysis of hard-...

An evaluation of machine learning methods for speed-bump detection on a GoPro dataset.

Anais da Academia Brasileira de Ciencias
Every day, new applications arise relying on the use of high-resolution road maps in both academic and industrial environments. Autonomous vehicles rely on digital maps to navigate when optical sensors cannot be trusted, such as heavy rainfalls, snow...

Practices and Applications of Convolutional Neural Network-Based Computer Vision Systems in Animal Farming: A Review.

Sensors (Basel, Switzerland)
Convolutional neural network (CNN)-based computer vision systems have been increasingly applied in animal farming to improve animal management, but current knowledge, practices, limitations, and solutions of the applications remain to be expanded and...