AIMC Topic: Neural Networks, Computer

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Tuned inhibition in perceptual decision-making circuits can explain seemingly suboptimal confidence behavior.

PLoS computational biology
Current dominant views hold that perceptual confidence reflects the probability that a decision is correct. Although these views have enjoyed some empirical support, recent behavioral results indicate that confidence and the probability of being corr...

Using the antibody-antigen binding interface to train image-based deep neural networks for antibody-epitope classification.

PLoS computational biology
High-throughput B-cell sequencing has opened up new avenues for investigating complex mechanisms underlying our adaptive immune response. These technological advances drive data generation and the need to mine and analyze the information contained in...

U-net model for brain extraction: Trained on humans for transfer to non-human primates.

NeuroImage
Brain extraction (a.k.a. skull stripping) is a fundamental step in the neuroimaging pipeline as it can affect the accuracy of downstream preprocess such as image registration, tissue classification, etc. Most brain extraction tools have been designed...

Low-Cost and Device-Free Human Activity Recognition Based on Hierarchical Learning Model.

Sensors (Basel, Switzerland)
Human activity recognition (HAR) has been a vital human-computer interaction service in smart homes. It is still a challenging task due to the diversity and similarity of human actions. In this paper, a novel hierarchical deep learning-based methodol...

Transfer learning in deep neural network-based receiver coil sensitivity map estimation.

Magma (New York, N.Y.)
INTRODUCTION: The success of parallel Magnetic Resonance Imaging algorithms like SENSitivity Encoding (SENSE) depends on an accurate estimation of the receiver coil sensitivity maps. Deep learning-based receiver coil sensitivity map estimation depend...

Convolutional neural networks for PET functional volume fully automatic segmentation: development and validation in a multi-center setting.

European journal of nuclear medicine and molecular imaging
PURPOSE: In this work, we addressed fully automatic determination of tumor functional uptake from positron emission tomography (PET) images without relying on other image modalities or additional prior constraints, in the context of multicenter image...

Real-time face & eye tracking and blink detection using event cameras.

Neural networks : the official journal of the International Neural Network Society
Event cameras contain emerging, neuromorphic vision sensors that capture local-light​ intensity changes at each pixel, generating a stream of asynchronous events. This way of acquiring visual information constitutes a departure from traditional frame...

Prediction modeling of potentially toxic elements' hydrogeopollution using an integrated Q-mode HCs and ANNs machine learning approach in SE Nigeria.

Environmental science and pollution research international
Machine learning techniques have proven to be very useful in environmental and engineering assessments, including water quality studies. This is because they have flexible linear and nonlinear forecasting functions that can efficiently and reliably e...

An automated COVID-19 detection based on fused dynamic exemplar pyramid feature extraction and hybrid feature selection using deep learning.

Computers in biology and medicine
The new coronavirus disease known as COVID-19 is currently a pandemic that is spread out the whole world. Several methods have been presented to detect COVID-19 disease. Computer vision methods have been widely utilized to detect COVID-19 by using ch...

Attention-Based Temporal Encoding Network with Background-Independent Motion Mask for Action Recognition.

Computational intelligence and neuroscience
Convolutional neural network (CNN) has been leaping forward in recent years. However, the high dimensionality, rich human dynamic characteristics, and various kinds of background interference increase difficulty for traditional CNNs in capturing comp...