AIMC Topic: Pattern Recognition, Automated

Clear Filters Showing 641 to 650 of 1671 articles

Two-stage CNNs for computerized BI-RADS categorization in breast ultrasound images.

Biomedical engineering online
BACKGROUND: Quantizing the Breast Imaging Reporting and Data System (BI-RADS) criteria into different categories with the single ultrasound modality has always been a challenge. To achieve this, we proposed a two-stage grading system to automatically...

KeratoDetect: Keratoconus Detection Algorithm Using Convolutional Neural Networks.

Computational intelligence and neuroscience
Keratoconus (KTC) is a noninflammatory disorder characterized by progressive thinning, corneal deformation, and scarring of the cornea. The pathological mechanisms of this condition have been investigated for a long time. In recent years, this diseas...

Cellular cartography of the organ of Corti based on optical tissue clearing and machine learning.

eLife
The highly organized spatial arrangement of sensory hair cells in the organ of Corti is essential for inner ear function. Here, we report a new analytical pipeline, based on optical clearing of tissue, for the construction of a single-cell resolution...

Adapting myoelectric control in real-time using a virtual environment.

Journal of neuroengineering and rehabilitation
BACKGROUND: Pattern recognition technology allows for more intuitive control of myoelectric prostheses. However, the need to collect electromyographic data to initially train the pattern recognition system, and to re-train it during prosthesis use, a...

Unsupervised robust discriminative manifold embedding with self-expressiveness.

Neural networks : the official journal of the International Neural Network Society
Dimensionality reduction has obtained increasing attention in the machine learning and computer vision communities due to the curse of dimensionality. Many manifold embedding methods have been proposed for dimensionality reduction. Many of them are s...

A proposal of prior probability-oriented clustering in feature encoding strategies.

PloS one
Codebook-based feature encodings are a standard framework for image recognition issues. A codebook is usually constructed by clusterings, such as the k-means and the Gaussian Mixture Model (GMM). A codebook size is an important factor to decide the t...

Deep learning for image analysis: Personalizing medicine closer to the point of care.

Critical reviews in clinical laboratory sciences
The precision-based revolution in medicine continues to demand stratification of patients into smaller and more personalized subgroups. While genomic technologies have largely led this movement, diagnostic results can take days to weeks to generate. ...

Robust Single-Sample Face Recognition by Sparsity-Driven Sub-Dictionary Learning Using Deep Features.

Sensors (Basel, Switzerland)
Face recognition using a single reference image per subject is challenging, above all when referring to a large gallery of subjects. Furthermore, the problem hardness seriously increases when the images are acquired in unconstrained conditions. In th...

A Two-Timescale Duplex Neurodynamic Approach to Biconvex Optimization.

IEEE transactions on neural networks and learning systems
This paper presents a two-timescale duplex neurodynamic system for constrained biconvex optimization. The two-timescale duplex neurodynamic system consists of two recurrent neural networks (RNNs) operating collaboratively at two timescales. By operat...

An Attention-Based Spiking Neural Network for Unsupervised Spike-Sorting.

International journal of neural systems
Bio-inspired computing using artificial spiking neural networks promises performances outperforming currently available computational approaches. Yet, the number of applications of such networks remains limited due to the absence of generic training ...