AIMC Topic: Pattern Recognition, Automated

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Novel real-time tumor-contouring method using deep learning to prevent mistracking in X-ray fluoroscopy.

Radiological physics and technology
Robustness to obstacles is the most important factor necessary to achieve accurate tumor tracking without fiducial markers. Some high-density structures, such as bone, are enhanced on X-ray fluoroscopic images, which cause tumor mistracking. Tumor tr...

Deep learning reveals Alzheimer's disease onset in MCI subjects: Results from an international challenge.

Journal of neuroscience methods
BACKGROUND: Early diagnosis of Alzheimer's disease (AD) and its onset in subjects affected by mild cognitive impairment (MCI) based on structural MRI features is one of the most important open issues in neuroimaging. Accordingly, a scientific challen...

Neuroanatomical heterogeneity of schizophrenia revealed by semi-supervised machine learning methods.

Schizophrenia research
UNLABELLED: Schizophrenia is associated with heterogeneous clinical symptoms and neuroanatomical alterations. In this work, we aim to disentangle the patterns of neuroanatomical alterations underlying a heterogeneous population of patients using a se...

Clustering Categorical Data Using Community Detection Techniques.

Computational intelligence and neuroscience
With the advent of the -modes algorithm, the toolbox for clustering categorical data has an efficient tool that scales linearly in the number of data items. However, random initialization of cluster centers in -modes makes it hard to reach a good clu...

Label-free sensor for automatic identification of erythrocytes using digital in-line holographic microscopy and machine learning.

Biosensors & bioelectronics
Cell types of erythrocytes should be identified because they are closely related to their functionality and viability. Conventional methods for classifying erythrocytes are time consuming and labor intensive. Therefore, an automatic and accurate eryt...

Optimal projection method determination by Logdet Divergence and perturbed von-Neumann Divergence.

BMC systems biology
BACKGROUND: Positive semi-definiteness is a critical property in kernel methods for Support Vector Machine (SVM) by which efficient solutions can be guaranteed through convex quadratic programming. However, a lot of similarity functions in applicatio...

Ensemble of random forests One vs. Rest classifiers for MCI and AD prediction using ANOVA cortical and subcortical feature selection and partial least squares.

Journal of neuroscience methods
BACKGROUND: Alzheimer's disease (AD) is the most common cause of dementia in the elderly and affects approximately 30 million individuals worldwide. Mild cognitive impairment (MCI) is very frequently a prodromal phase of AD, and existing studies have...

HyperFace: A Deep Multi-Task Learning Framework for Face Detection, Landmark Localization, Pose Estimation, and Gender Recognition.

IEEE transactions on pattern analysis and machine intelligence
We present an algorithm for simultaneous face detection, landmarks localization, pose estimation and gender recognition using deep convolutional neural networks (CNN). The proposed method called, HyperFace, fuses the intermediate layers of a deep CNN...

Spiking Neural Classifier with Lumped Dendritic Nonlinearity and Binary Synapses: A Current Mode VLSI Implementation and Analysis.

Neural computation
We present a neuromorphic current mode implementation of a spiking neural classifier with lumped square law dendritic nonlinearity. It has been shown previously in software simulations that such a system with binary synapses can be trained with struc...