AIMC Topic: Humans

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Real-time multiple spatiotemporal action localization and prediction approach using deep learning.

Neural networks : the official journal of the International Neural Network Society
Detecting the locations of multiple actions in videos and classifying them in real-time are challenging problems termed "action localization and prediction" problem. Convolutional neural networks (ConvNets) have achieved great success for action loca...

Graph transform learning.

Neural networks : the official journal of the International Neural Network Society
Transform learning is a new representation learning framework where we learn an operator/transform that analyses the data to generate the coefficient/representation. We propose a variant of it called the graph transform learning; in this we explicitl...

T-Net: Nested encoder-decoder architecture for the main vessel segmentation in coronary angiography.

Neural networks : the official journal of the International Neural Network Society
In this paper, we proposed nested encoder-decoder architecture named T-Net. T-Net consists of several small encoder-decoders for each block constituting convolutional network. T-Net overcomes the limitation that U-Net can only have a single set of th...

Deep-Hipo: Multi-scale receptive field deep learning for histopathological image analysis.

Methods (San Diego, Calif.)
Digitizing whole-slide imaging in digital pathology has led to the advancement of computer-aided tissue examination using machine learning techniques, especially convolutional neural networks. A number of convolutional neural network-based methodolog...

A deep metric learning approach for histopathological image retrieval.

Methods (San Diego, Calif.)
To distinguish ambiguous images during specimen slides viewing, pathologists usually spend lots of time to seek guidance from confirmed similar images or cases, which is inefficient. Therefore, several histopathological image retrieval methods have b...

Supervised machine learning for coronary artery lumen segmentation in intravascular ultrasound images.

International journal for numerical methods in biomedical engineering
Intravascular ultrasound (IVUS) has been widely used to capture cross sectional lumen frames of inner wall of coronary arteries. This kind of medical imaging modalities is capable of providing detailed and significant information of lumen contour sha...

Early Prediction of Single-Cell Derived Sphere Formation Rate Using Convolutional Neural Network Image Analysis.

Analytical chemistry
Functional identification of cancer stem-like cells (CSCs) is an established method to identify and study this cancer subpopulation critical for cancer progression and metastasis. The method is based on the unique capability of single CSCs to survive...

Artificial Intelligence for Natural Hazards Risk Analysis: Potential, Challenges, and Research Needs.

Risk analysis : an official publication of the Society for Risk Analysis
Artificial intelligence (AI) methods have seen increasingly widespread use in everything from consumer products and driverless cars to fraud detection and weather forecasting. The use of AI has transformed many of these application domains. There are...

Machine Learning Systems Applied to Health Data and System.

European journal of health law
The use of machine learning (ML) in medicine is becoming increasingly fundamental to analyse complex problems by discovering associations among different types of information and to generate knowledge for medical decision support. Many regulatory and...

Real-Time Human Action Recognition with a Low-Cost RGB Camera and Mobile Robot Platform.

Sensors (Basel, Switzerland)
Human action recognition is an important research area in the field of computer vision that can be applied in surveillance, assisted living, and robotic systems interacting with people. Although various approaches have been widely used, recent studie...