AIMC Topic: Pattern Recognition, Automated

Clear Filters Showing 841 to 850 of 1689 articles

A Novel Adaptive Deformable Model for Automated Optic Disc and Cup Segmentation to Aid Glaucoma Diagnosis.

Journal of medical systems
This paper proposes a novel Adaptive Region-based Edge Smoothing Model (ARESM) for automatic boundary detection of optic disc and cup to aid automatic glaucoma diagnosis. The novelty of our approach consists of two aspects: 1) automatic detection of ...

Tensor Decomposition of Gait Dynamics in Parkinson's Disease.

IEEE transactions on bio-medical engineering
OBJECTIVE: The study of gait in Parkinson's disease is important because it can provide insights into the complex neural system and physiological behaviors of the disease, of which understanding can help improve treatment and lead to effective develo...

Automatic Target Recognition Strategy for Synthetic Aperture Radar Images Based on Combined Discrimination Trees.

Computational intelligence and neuroscience
A strategy is introduced for achieving high accuracy in synthetic aperture radar (SAR) automatic target recognition (ATR) tasks. Initially, a novel pose rectification process and an image normalization process are sequentially introduced to produce i...

Efficient Active Sensing with Categorized Further Explorations for a Home Behavior-Monitoring Robot.

Journal of healthcare engineering
Mobile robotics is a potential solution to home behavior monitoring for the elderly. For a mobile robot in the real world, there are several types of uncertainties for its perceptions, such as the ambiguity between a target object and the surrounding...

Derivation of simple rules for complex flow vector fields on the lower part of the human face for robot face design.

Bioinspiration & biomimetics
It is quite difficult for android robots to replicate the numerous and various types of human facial expressions owing to limitations in terms of space, mechanisms, and materials. This situation could be improved with greater knowledge regarding thes...

Cross Euclidean-to-Riemannian Metric Learning with Application to Face Recognition from Video.

IEEE transactions on pattern analysis and machine intelligence
Riemannian manifolds have been widely employed for video representations in visual classification tasks including video-based face recognition. The success mainly derives from learning a discriminant Riemannian metric which encodes the non-linear geo...

Looking for Alzheimer's Disease morphometric signatures using machine learning techniques.

Journal of neuroscience methods
BACKGROUND: We present our results in the International challenge for automated prediction of MCI from MRI data. We evaluate the performance of MRI-based neuromorphometrics features (nMF) in the classification of Healthy Controls (HC), Mild Cognitive...

Statistics of Visual Responses to Image Object Stimuli from Primate AIT Neurons to DNN Neurons.

Neural computation
Under the goal-driven paradigm, Yamins et al. ( 2014 ; Yamins & DiCarlo, 2016 ) have shown that by optimizing only the final eight-way categorization performance of a four-layer hierarchical network, not only can its top output layer quantitatively p...

Machine Learning in Radiology: Applications Beyond Image Interpretation.

Journal of the American College of Radiology : JACR
Much attention has been given to machine learning and its perceived impact in radiology, particularly in light of recent success with image classification in international competitions. However, machine learning is likely to impact radiology outside ...

Support vector machine with Dirichlet feature mapping.

Neural networks : the official journal of the International Neural Network Society
The Support Vector Machine (SVM) is a supervised learning algorithm to analyze data and recognize patterns. The standard SVM suffers from some limitations in nonlinear classification problems. To tackle these limitations, the nonlinear form of the SV...