AIMC Topic: Algorithms

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Standing-Posture Recognition in Human-Robot Collaboration Based on Deep Learning and the Dempster-Shafer Evidence Theory.

Sensors (Basel, Switzerland)
During human-robot collaborations (HRC), robot systems must accurately perceive the actions and intentions of humans. The present study proposes the classification of standing postures from standing-pressure images, by which a robot system can predic...

A Classification Method of Oracle Materials Based on Local Convolutional Neural Network Framework.

IEEE computer graphics and applications
The classification of materials of oracle bone is one of the most basic aspects for oracle bone morphology. However, the classification method depending on experts' experience requires long-term learning and accumulation for professional knowledge. T...

Separation of HCM and LQT Cardiac Diseases with Machine Learning of Ca2+ Transient Profiles.

Methods of information in medicine
BACKGROUND:  Modeling human cardiac diseases with induced pluripotent stem cells not only enables to study disease pathophysiology and develop therapies but also, as we have previously showed, it can offer a tool for disease diagnostics. We previousl...

Computer Aided Diagnosis for atrial fibrillation based on new artificial adaptive systems.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Atrial fibrillation (AF) is the most common cardiac arrhythmia in clinical practice, having been recognized as a true cardiovascular epidemic. In this paper, a new methodology for Computer Aided Diagnosis of AF based on a sp...

Machine learning algorithms applied to a prediction of personal overall thermal comfort using skin temperatures and occupants' heating behavior.

Applied ergonomics
Thermal comfort modeling has been of interest in built environment research for decades. Mostly the modeling approaches focused on an average response of a large group of building occupants. Recently, the focus has been shifted towards personal comfo...

A new feature selection algorithm based on relevance, redundancy and complementarity.

Computers in biology and medicine
Defining important information from biological data is critical for the study of disease diagnosis, drug efficacy and individualized treatment. Hence, the feature selection technique is widely applied. Many feature selection methods measure features ...

Convolutional and recurrent neural network for human activity recognition: Application on American sign language.

PloS one
Human activity recognition is an important and difficult topic to study because of the important variability between tasks repeated several times by a subject and between subjects. This work is motivated by providing time-series signal classification...

Numerosity discrimination in deep neural networks: Initial competence, developmental refinement and experience statistics.

Developmental science
Both humans and non-human animals exhibit sensitivity to the approximate number of items in a visual array, as indexed by their performance in numerosity discrimination tasks, and even neonates can detect changes in numerosity. These findings are oft...

Feature Extraction of Surface Electromyography Based on Improved Small-World Leaky Echo State Network.

Neural computation
Surface electromyography (sEMG) is an electrophysiological reflection of skeletal muscle contractile activity that can directly reflect neuromuscular activity. It has been a matter of research to investigate feature extraction methods of sEMG signals...