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Pattern Recognition, Automated

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Measuring Biomechanical Risk in Lifting Load Tasks Through Wearable System and Machine-Learning Approach.

Sensors (Basel, Switzerland)
Ergonomics evaluation through measurements of biomechanical parameters in real time has a great potential in reducing non-fatal occupational injuries, such as work-related musculoskeletal disorders. Assuming a correct posture guarantees the avoidance...

Recognition of Common Non-Normal Walking Actions Based on Relief-F Feature Selection and Relief-Bagging-SVM.

Sensors (Basel, Switzerland)
Action recognition algorithms are widely used in the fields of medical health and pedestrian dead reckoning (PDR). The classification and recognition of non-normal walking actions and normal walking actions are very important for improving the accura...

Clinical Tractor: A Framework for Automatic Natural Language Understanding of Clinical Practice Guidelines.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Computational representations of the semantic knowledge embedded within clinical practice guidelines (CPGs) may be a significant aid in creating computer interpretable guidelines (CIGs). Formalizing plain text CPGs into CIGs manually is a laborious a...

Comparing machine and human reviewers to evaluate the risk of bias in randomized controlled trials.

Research synthesis methods
BACKGROUND: Evidence from new health technologies is growing, along with demands for evidence to inform policy decisions, creating challenges in completing health technology assessments (HTAs)/systematic reviews (SRs) in a timely manner. Software can...

Fusing Self-Organized Neural Network and Keypoint Clustering for Localized Real-Time Background Subtraction.

International journal of neural systems
Moving object detection in video streams plays a key role in many computer vision applications. In particular, separation between background and foreground items represents a main prerequisite to carry out more complex tasks, such as object classific...

Multiple Discrimination and Pairwise CNN for view-based 3D object retrieval.

Neural networks : the official journal of the International Neural Network Society
With the rapid development and wide application of computer, camera device, network and hardware technology, 3D object (or model) retrieval has attracted widespread attention and it has become a hot research topic in the computer vision domain. Deep ...

Parametric Deformable Exponential Linear Units for deep neural networks.

Neural networks : the official journal of the International Neural Network Society
Rectified activation units make an important contribution to the success of deep neural networks in many computer vision tasks. In this paper, we propose a Parametric Deformable Exponential Linear Unit (PDELU) and theoretically verify its effectivene...

A neural network for online spike classification that improves decoding accuracy.

Journal of neurophysiology
Separating neural signals from noise can improve brain-computer interface performance and stability. However, most algorithms for separating neural action potentials from noise are not suitable for use in real time and have shown mixed effects on dec...

Causal importance of low-level feature selectivity for generalization in image recognition.

Neural networks : the official journal of the International Neural Network Society
Although our brain and deep neural networks (DNNs) can perform high-level sensory-perception tasks, such as image or speech recognition, the inner mechanism of these hierarchical information-processing systems is poorly understood in both neuroscienc...