AI Medical Compendium Topic:
Pattern Recognition, Automated

Clear Filters Showing 691 to 700 of 1638 articles

Integrating Language Model and Reading Control Gate in BLSTM-CRF for Biomedical Named Entity Recognition.

IEEE/ACM transactions on computational biology and bioinformatics
Biomedical named entity recognition (Bio-NER) is an important preliminary step for many biomedical text mining tasks. The current mainstream methods for NER are based on the neural networks to avoid the complex hand-designed features derived from var...

Representation Learning by Rotating Your Faces.

IEEE transactions on pattern analysis and machine intelligence
The large pose discrepancy between two face images is one of the fundamental challenges in automatic face recognition. Conventional approaches to pose-invariant face recognition either perform face frontalization on, or learn a pose-invariant represe...

Handwritten Bangla Character Recognition Using the State-of-the-Art Deep Convolutional Neural Networks.

Computational intelligence and neuroscience
In spite of advances in object recognition technology, handwritten Bangla character recognition (HBCR) remains largely unsolved due to the presence of many ambiguous handwritten characters and excessively cursive Bangla handwritings. Even many advanc...

A Biologically Inspired Approach for Robot Depth Estimation.

Computational intelligence and neuroscience
Aimed at building autonomous service robots, reasoning, perception, and action should be properly integrated. In this paper, the depth cue has been analysed as an early stage given its importance for robotic tasks. So, from neuroscience findings, a h...

Deep Convolutional Neural Network Used in Single Sample per Person Face Recognition.

Computational intelligence and neuroscience
Face recognition (FR) with single sample per person (SSPP) is a challenge in computer vision. Since there is only one sample to be trained, it makes facial variation such as pose, illumination, and disguise difficult to be predicted. To overcome this...

Low-rank and sparse embedding for dimensionality reduction.

Neural networks : the official journal of the International Neural Network Society
In this paper, we propose a robust subspace learning (SL) framework for dimensionality reduction which further extends the existing SL methods to a low-rank and sparse embedding (LRSE) framework from three aspects: overall optimum, robustness and gen...

Automated dendritic spine detection using convolutional neural networks on maximum intensity projected microscopic volumes.

Journal of neuroscience methods
BACKGROUND: Dendritic spines are structural correlates of excitatory synapses in the brain. Their density and structure are shaped by experience, pointing to their role in memory encoding. Dendritic spine imaging, followed by manual analysis, is a pr...

Slow wave detection in sleeping mice: Comparison of traditional and machine learning methods.

Journal of neuroscience methods
BACKGROUND: During slow-wave sleep the electroencephalographic (EEG) and local field potential (LFP) recordings reveal the presence of large amplitude slow waves. Systematic extraction of individual slow waves is not trivial.

High-Frequency Oscillations in the Scalp Electroencephalogram: Mission Impossible without Computational Intelligence.

Computational intelligence and neuroscience
High-frequency oscillations (HFOs) in the electroencephalogram (EEG) are thought to be a promising marker for epileptogenicity. A number of automated detection algorithms have been developed for reliable analysis of invasively recorded HFOs. However,...

Cross-Generation Kinship Verification with Sparse Discriminative Metric.

IEEE transactions on pattern analysis and machine intelligence
Kinship verification is a very important technique in many real-world applications, e.g., personal album organization, missing person investigation and forensic analysis. However, it is extremely difficult to verify a family pair with generation gap,...