AIMC Topic: Pattern Recognition, Automated

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The effect of structure on image classification using signatures.

Biological cybernetics
Humans recognize transformed images from a very small number of samples. Inspired by this idea, we evaluate a classification method that requires only one sample per class, while providing invariance to image transformations generated by a compact gr...

Epigenetic machine learning: utilizing DNA methylation patterns to predict spastic cerebral palsy.

BMC bioinformatics
BACKGROUND: Spastic cerebral palsy (CP) is a leading cause of physical disability. Most people with spastic CP are born with it, but early diagnosis is challenging, and no current biomarker platform readily identifies affected individuals. The aim of...

Survey and experimental study on metric learning methods.

Neural networks : the official journal of the International Neural Network Society
Distance metric learning has been a hot research spot recently due to its high effectiveness and efficiency in improving the performance of distance related methods, such as k nearest neighbors (kNN). Metric learning aims to learn a data-dependent me...

A distance measure between intuitionistic fuzzy sets and its application in medical diagnosis.

Artificial intelligence in medicine
The intuitionistic fuzzy set, as a generation of fuzzy set, can express and process uncertainty much better. Distance measures between intuitionistic fuzzy sets are used to indicate the difference degree between the information carried by intuitionis...

Impact of Sliding Window Length in Indoor Human Motion Modes and Pose Pattern Recognition Based on Smartphone Sensors.

Sensors (Basel, Switzerland)
Human activity recognition (HAR) is essential for understanding people’s habits and behaviors, providing an important data source for precise marketing and research in psychology and sociology. Different approaches have been proposed and applie...

Rough sets and Laplacian score based cost-sensitive feature selection.

PloS one
Cost-sensitive feature selection learning is an important preprocessing step in machine learning and data mining. Recently, most existing cost-sensitive feature selection algorithms are heuristic algorithms, which evaluate the importance of each feat...

A sparsity-based stochastic pooling mechanism for deep convolutional neural networks.

Neural networks : the official journal of the International Neural Network Society
A novel sparsity-based stochastic pooling which integrates the advantages of max-pooling, average-pooling and stochastic pooling is introduced. The proposed pooling is designed to balance the advantages and disadvantages of max-pooling and average-po...

From lexical regularities to axiomatic patterns for the quality assurance of biomedical terminologies and ontologies.

Journal of biomedical informatics
Ontologies and terminologies have been identified as key resources for the achievement of semantic interoperability in biomedical domains. The development of ontologies is performed as a joint work by domain experts and knowledge engineers. The maint...

Fine-Tuning CNN Image Retrieval with No Human Annotation.

IEEE transactions on pattern analysis and machine intelligence
Image descriptors based on activations of Convolutional Neural Networks (CNNs) have become dominant in image retrieval due to their discriminative power, compactness of representation, and search efficiency. Training of CNNs, either from scratch or f...

Fight Recognition in video using Hough Forests and 2D Convolutional Neural Network.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
While action recognition has become an important line of research in computer vision, the recognition of particular events such as aggressive behaviors, or fights, has been relatively less studied. These tasks may be extremely useful in several video...