AIMC Topic: Pattern Recognition, Automated

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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,...

Neural multi-atlas label fusion: Application to cardiac MR images.

Medical image analysis
Multi-atlas segmentation approach is one of the most widely-used image segmentation techniques in biomedical applications. There are two major challenges in this category of methods, i.e., atlas selection and label fusion. In this paper, we propose a...

RETRACTED: Diagnosis labeling with disease-specific characteristics mining.

Artificial intelligence in medicine
This article has been retracted: please see Elsevier Policy on Article Withdrawal (https://www.elsevier.com/about/our-business/policies/article-withdrawal). This article has been retracted at the request of the authors; serious errors had been introd...