AIMC Topic: Pattern Recognition, Automated

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Adaptable texture-based segmentation by variance and intensity for automatic detection of semitranslucent and pink blush areas in basal cell carcinoma.

Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI)
BACKGROUND: Pink blush is a common feature in basal cell carcinoma (BCC). A related feature, semitranslucency, appears as smooth pink or orange regions resembling skin color. We introduce an automatic method for detection of these features based on s...

A Human Activity Recognition System Using Skeleton Data from RGBD Sensors.

Computational intelligence and neuroscience
The aim of Active and Assisted Living is to develop tools to promote the ageing in place of elderly people, and human activity recognition algorithms can help to monitor aged people in home environments. Different types of sensors can be used to addr...

High-Performance Personalized Heartbeat Classification Model for Long-Term ECG Signal.

IEEE transactions on bio-medical engineering
Long-term electrocardiogram (ECG) has become one of the important diagnostic assist methods in clinical cardiovascular domain. Long-term ECG is primarily used for the detection of various cardiovascular diseases that are caused by various cardiac arr...

Marginal Space Deep Learning: Efficient Architecture for Volumetric Image Parsing.

IEEE transactions on medical imaging
Robust and fast solutions for anatomical object detection and segmentation support the entire clinical workflow from diagnosis, patient stratification, therapy planning, intervention and follow-up. Current state-of-the-art techniques for parsing volu...

Hierarchical Clustering Multi-Task Learning for Joint Human Action Grouping and Recognition.

IEEE transactions on pattern analysis and machine intelligence
This paper proposes a hierarchical clustering multi-task learning (HC-MTL) method for joint human action grouping and recognition. Specifically, we formulate the objective function into the group-wise least square loss regularized by low rank and spa...

Deep Dynamic Neural Networks for Multimodal Gesture Segmentation and Recognition.

IEEE transactions on pattern analysis and machine intelligence
This paper describes a novel method called Deep Dynamic Neural Networks (DDNN) for multimodal gesture recognition. A semi-supervised hierarchical dynamic framework based on a Hidden Markov Model (HMM) is proposed for simultaneous gesture segmentation...

Bio-SCoRes: A Smorgasbord Architecture for Coreference Resolution in Biomedical Text.

PloS one
Coreference resolution is one of the fundamental and challenging tasks in natural language processing. Resolving coreference successfully can have a significant positive effect on downstream natural language processing tasks, such as information extr...

A categorical analysis of coreference resolution errors in biomedical texts.

Journal of biomedical informatics
BACKGROUND: Coreference resolution is an essential task in information extraction from the published biomedical literature. It supports the discovery of complex information by linking referring expressions such as pronouns and appositives to their re...

A Discriminatively Trained Fully Connected Conditional Random Field Model for Blood Vessel Segmentation in Fundus Images.

IEEE transactions on bio-medical engineering
GOAL: In this work, we present an extensive description and evaluation of our method for blood vessel segmentation in fundus images based on a discriminatively trained fully connected conditional random field model.

HYDRA: Revealing heterogeneity of imaging and genetic patterns through a multiple max-margin discriminative analysis framework.

NeuroImage
Multivariate pattern analysis techniques have been increasingly used over the past decade to derive highly sensitive and specific biomarkers of diseases on an individual basis. The driving assumption behind the vast majority of the existing methodolo...