AIMC Topic: Neural Networks, Computer

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DeepA-RBPBS: A hybrid convolution and recurrent neural network combined with attention mechanism for predicting RBP binding site.

Journal of biomolecular structure & dynamics
It's important to infer the binding site of RNA-binding proteins (RBP) for understanding the interaction between RBP and its RNA targets and decipher the mechanisms of transcriptional regulation. However, experimental detection of RBP binding sites i...

Coronary angiography image segmentation based on PSPNet.

Computer methods and programs in biomedicine
PURPOSE: Coronary artery disease (CAD) is known to have high prevalence, high disability and mortality. The incidence and mortality of cardiovascular disease are also gradually increasing worldwide. Therefore, our paper proposes to use a more efficie...

An end-to-end breast tumour classification model using context-based patch modelling - A BiLSTM approach for image classification.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Researchers working on computational analysis of Whole Slide Images (WSIs) in histopathology have primarily resorted to patch-based modelling due to large resolution of each WSI. The large resolution makes WSIs infeasible to be fed directly into the ...

Iterative Training of Neural Networks for Intra Prediction.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
This paper presents an iterative training of neural networks for intra prediction in a block-based image and video codec. First, the neural networks are trained on blocks arising from the codec partitioning of images, each paired with its context. Th...

Joint Person Objectness and Repulsion for Person Search.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Person search targets to search the probe person from the unconstrainted scene images, which can be treated as the combination of person detection and person matching. However, the existing methods based on the Detection-Matching framework ignore the...

Using Convolutional Neural Networks with Multiple Thermal Sensors for Unobtrusive Pose Recognition.

Sensors (Basel, Switzerland)
The desire to remain living in one's own home rather than a care home by those in need of 24/7 care is one that requires a level of understanding for the actions of an environment's inhabitants. This can potentially be accomplished with the ability t...

Continuous and automatic mortality risk prediction using vital signs in the intensive care unit: a hybrid neural network approach.

Scientific reports
Mortality risk prediction can greatly improve the utilization of resources in intensive care units (ICUs). Existing schemes in ICUs today require laborious manual input of many complex parameters. In this work, we present a scheme that uses variation...

StackNet-DenVIS: a multi-layer perceptron stacked ensembling approach for COVID-19 detection using X-ray images.

Physical and engineering sciences in medicine
The highly contagious nature of Coronavirus disease 2019 (Covid-19) resulted in a global pandemic. Due to the relatively slow and taxing nature of conventional testing for Covid-19, a faster method needs to be in place. The current researches have su...

How to Extract More Information With Less Burden: Fundus Image Classification and Retinal Disease Localization With Ophthalmologist Intervention.

IEEE journal of biomedical and health informatics
Image classification using convolutional neural networks (CNNs) outperforms other state-of-the-art methods. Moreover, attention can be visualized as a heatmap to improve the explainability of results of a CNN. We designed a framework that can generat...

Attention-Guided 3D-CNN Framework for Glaucoma Detection and Structural-Functional Association Using Volumetric Images.

IEEE journal of biomedical and health informatics
The direct analysis of 3D Optical Coherence Tomography (OCT) volumes enables deep learning models (DL) to learn spatial structural information and discover new bio-markers that are relevant to glaucoma. Downsampling 3D input volumes is the state-of-a...