AI Medical Compendium Topic

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Pattern Recognition, Automated

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Multi-label zero-shot learning with graph convolutional networks.

Neural networks : the official journal of the International Neural Network Society
The goal of zero-shot learning (ZSL) is to build a classifier that recognizes novel categories with no corresponding annotated training data. The typical routine is to transfer knowledge from seen classes to unseen ones by learning a visual-semantic ...

Real-time gun detection in CCTV: An open problem.

Neural networks : the official journal of the International Neural Network Society
Object detectors have improved in recent years, obtaining better results and faster inference time. However, small object detection is still a problem that has not yet a definitive solution. The autonomous weapons detection on Closed-circuit televisi...

Group-based local adaptive deep multiple kernel learning with lp norm.

PloS one
The deep multiple kernel Learning (DMKL) method has attracted wide attention due to its better classification performance than shallow multiple kernel learning. However, the existing DMKL methods are hard to find suitable global model parameters to i...

Pattern Recognition of Cognitive Load Using EEG and ECG Signals.

Sensors (Basel, Switzerland)
The matching of cognitive load and working memory is the key for effective learning, and cognitive effort in the learning process has nervous responses which can be quantified in various physiological parameters. Therefore, it is meaningful to explor...

Detecting face presentation attacks in mobile devices with a patch-based CNN and a sensor-aware loss function.

PloS one
With the widespread use of biometric authentication comes the exploitation of presentation attacks, possibly undermining the effectiveness of these technologies in real-world setups. One example takes place when an impostor, aiming at unlocking someo...

Are open set classification methods effective on large-scale datasets?

PloS one
Supervised classification methods often assume the train and test data distributions are the same and that all classes in the test set are present in the training set. However, deployed classifiers often require the ability to recognize inputs from o...

Shape-to-graph mapping method for efficient characterization and classification of complex geometries in biological images.

PLoS computational biology
With the ever-increasing quality and quantity of imaging data in biomedical research comes the demand for computational methodologies that enable efficient and reliable automated extraction of the quantitative information contained within these image...

Neural Network-Based Study about Correlation Model between TCM Constitution and Physical Examination Indexes Based on 950 Physical Examinees.

Journal of healthcare engineering
PURPOSE: To establish the correlation model between Traditional Chinese Medicine (TCM) constitution and physical examination indexes by backpropagation neural network (BPNN) technology. A new method for the identification of TCM constitution in clini...

Unsupervised spectral mapping and feature selection for hyperspectral anomaly detection.

Neural networks : the official journal of the International Neural Network Society
Exploring techniques that breakthrough the unknown space or material species is of considerable significance to military and civilian fields, and it is a challenging task without any prior information. Nowadays, the use of material-specific spectral ...

An Acoustic Sensing Gesture Recognition System Design Based on a Hidden Markov Model.

Sensors (Basel, Switzerland)
Many human activities are tactile. Recognizing how a person touches an object or a surface surrounding them is an active area of research and it has generated keen interest within the interactive surface community. In this paper, we compare two machi...