AIMC Topic: Neural Networks, Computer

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Weakly supervised object detection with 2D and 3D regression neural networks.

Medical image analysis
Finding automatically multiple lesions in large images is a common problem in medical image analysis. Solving this problem can be challenging if, during optimization, the automated method cannot access information about the location of the lesions no...

Visual interaction networks: A novel bio-inspired computational model for image classification.

Neural networks : the official journal of the International Neural Network Society
Inspired by biological mechanisms and structures in neuroscience, many biologically inspired visual computational models have been presented to provide new solutions for visual recognition task. For example, convolutional neural network (CNN) was pro...

An artificial neural network approach for predicting hypertension using NHANES data.

Scientific reports
This paper focus on a neural network classification model to estimate the association among gender, race, BMI, age, smoking, kidney disease and diabetes in hypertensive patients. It also shows that artificial neural network techniques applied to larg...

Parallel ensemble learning of convolutional neural networks and local binary patterns for face recognition.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Face recognition success rate is influenced by illumination, expression, posture change, and other factors, which is due to the low generalization ability of a single convolutional neural network. A new face recognition meth...

RNN-Aided Human Velocity Estimation from a Single IMU.

Sensors (Basel, Switzerland)
Pedestrian Dead Reckoning (PDR) uses inertial measurement units (IMUs) and combines velocity and orientation estimates to determine a position. The estimation of the velocity is still challenging, as the integration of noisy acceleration and angular ...

CellCountCV-A Web-Application for Accurate Cell Counting and Automated Batch Processing of Microscopic Images Using Fully Convolutional Neural Networks.

Sensors (Basel, Switzerland)
In vitro cellular models are promising tools for studying normal and pathological conditions. One of their important applications is the development of genetically engineered biosensor systems to investigate, in real time, the processes occurring in ...

Multitemporal time series analysis using machine learning models for ground deformation in the Erhai region, China.

Environmental monitoring and assessment
Ground deformation (GD) has been widely reported as a global issue and is now an ongoing problem that will profoundly endanger the public safety. GD is a complex and dynamic problem with many contributing factors that occur over time. In the literatu...

The effect of sensory feedback topology on the entrainment of a neural oscillator with a compliant foil for swimming systems.

Bioinspiration & biomimetics
The sensorimotor system of fish endows them with remarkable swimming performance that is unmatched by current underwater robotic vehicles. To close the gap between the capabilities of fish and the capabilities of underwater vehicles engineers are inv...

Hiding a plane with a pixel: examining shape-bias in CNNs and the benefit of building in biological constraints.

Vision research
When deep convolutional neural networks (CNNs) are trained "end-to-end" on raw data, some of the feature detectors they develop in their early layers resemble the representations found in early visual cortex. This result has been used to draw paralle...