AIMC Topic: Pattern Recognition, Automated

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KnowLife: a versatile approach for constructing a large knowledge graph for biomedical sciences.

BMC bioinformatics
BACKGROUND: Biomedical knowledge bases (KB's) have become important assets in life sciences. Prior work on KB construction has three major limitations. First, most biomedical KBs are manually built and curated, and cannot keep up with the rate at whi...

A Projection Neural Network for Constrained Quadratic Minimax Optimization.

IEEE transactions on neural networks and learning systems
This paper presents a projection neural network described by a dynamic system for solving constrained quadratic minimax programming problems. Sufficient conditions based on a linear matrix inequality are provided for global convergence of the propose...

Deep convolutional neural networks for annotating gene expression patterns in the mouse brain.

BMC bioinformatics
BACKGROUND: Profiling gene expression in brain structures at various spatial and temporal scales is essential to understanding how genes regulate the development of brain structures. The Allen Developing Mouse Brain Atlas provides high-resolution 3-D...

A Fuzzy Kernel Motion Classifier for Autonomous Stroke Rehabilitation.

IEEE journal of biomedical and health informatics
Autonomous poststroke rehabilitation systems which can be deployed outside hospital with no or reduced supervision have attracted increasing amount of research attentions due to the high expenditure associated with the current inpatient stroke rehabi...

Log-Spiral Keypoint: A Robust Approach toward Image Patch Matching.

Computational intelligence and neuroscience
Matching of keypoints across image patches forms the basis of computer vision applications, such as object detection, recognition, and tracking in real-world images. Most of keypoint methods are mainly used to match the high-resolution images, which ...

Online kernel slow feature analysis for temporal video segmentation and tracking.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Slow feature analysis (SFA) is a dimensionality reduction technique which has been linked to how visual brain cells work. In recent years, the SFA was adopted for computer vision tasks. In this paper, we propose an exact kernel SFA (KSFA) framework f...

Machine learning methods for the classification of gliomas: Initial results using features extracted from MR spectroscopy.

The neuroradiology journal
CONTEXT: With the advent of new imaging modalities, radiologists are faced with handling increasing volumes of data for diagnosis and treatment planning. The use of automated and intelligent systems is becoming essential in such a scenario. Machine l...

Automatic evidence quality prediction to support evidence-based decision making.

Artificial intelligence in medicine
BACKGROUND: Evidence-based medicine practice requires practitioners to obtain the best available medical evidence, and appraise the quality of the evidence when making clinical decisions. Primarily due to the plethora of electronically available data...

Time-Delay Neural Network for Continuous Emotional Dimension Prediction From Facial Expression Sequences.

IEEE transactions on cybernetics
Automatic continuous affective state prediction from naturalistic facial expression is a very challenging research topic but very important in human-computer interaction. One of the main challenges is modeling the dynamics that characterize naturalis...

On the Relationship between Variational Level Set-Based and SOM-Based Active Contours.

Computational intelligence and neuroscience
Most Active Contour Models (ACMs) deal with the image segmentation problem as a functional optimization problem, as they work on dividing an image into several regions by optimizing a suitable functional. Among ACMs, variational level set methods hav...