AIMC Topic: Pattern Recognition, Automated

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An Automatic Subject-Adaptable Heartbeat Classifier Based on Multiview Learning.

IEEE journal of biomedical and health informatics
In this paper, a novel subject-adaptable heartbeat classification model is presented, in order to address the significant interperson variations in ECG signals. A multiview learning approach is proposed to automate subject adaptation using a small am...

Benchmarking human epithelial type 2 interphase cells classification methods on a very large dataset.

Artificial intelligence in medicine
OBJECTIVE: This paper presents benchmarking results of human epithelial type 2 (HEp-2) interphase cell image classification methods on a very large dataset. The indirect immunofluorescence method applied on HEp-2 cells has been the gold standard to i...

Relevance Metric Learning for Person Re-Identification by Exploiting Listwise Similarities.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Person re-identification aims to match people across non-overlapping camera views, which is an important but challenging task in video surveillance. In order to obtain a robust metric for matching, metric learning has been introduced recently. Most e...

A tool for developing an automatic insect identification system based on wing outlines.

Scientific reports
For some insect groups, wing outline is an important character for species identification. We have constructed a program as the integral part of an automated system to identify insects based on wing outlines (DAIIS). This program includes two main fu...

Pattern recognition for cache management in distributed medical imaging environments.

International journal of computer assisted radiology and surgery
PURPOSE: Traditionally, medical imaging repositories have been supported by indoor infrastructures with huge operational costs. This paradigm is changing thanks to cloud outsourcing which not only brings technological advantages but also facilitates ...

A novel multivariate performance optimization method based on sparse coding and hyper-predictor learning.

Neural networks : the official journal of the International Neural Network Society
In this paper, we investigate the problem of optimization of multivariate performance measures, and propose a novel algorithm for it. Different from traditional machine learning methods which optimize simple loss functions to learn prediction functio...

Fusing Swarm Intelligence and Self-Assembly for Optimizing Echo State Networks.

Computational intelligence and neuroscience
Optimizing a neural network's topology is a difficult problem for at least two reasons: the topology space is discrete, and the quality of any given topology must be assessed by assigning many different sets of weights to its connections. These two c...

An Effective and Novel Neural Network Ensemble for Shift Pattern Detection in Control Charts.

Computational intelligence and neuroscience
Pattern recognition in control charts is critical to make a balance between discovering faults as early as possible and reducing the number of false alarms. This work is devoted to designing a multistage neural network ensemble that achieves this bal...

A systematic comparison of feature space effects on disease classifier performance for phenotype identification of five diseases.

Journal of biomedical informatics
Automated phenotype identification plays a critical role in cohort selection and bioinformatics data mining. Natural Language Processing (NLP)-informed classification techniques can robustly identify phenotypes in unstructured medical notes. In this ...

Rediscovery of Good-Turing estimators via Bayesian nonparametrics.

Biometrics
The problem of estimating discovery probabilities originated in the context of statistical ecology, and in recent years it has become popular due to its frequent appearance in challenging applications arising in genetics, bioinformatics, linguistics,...