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Found 12 papers, 2 papers with code
Spatial-aware Transformer-GRU Framework for Enhanced Glaucoma Diagnosis from 3D OCT Imaging
Glaucoma, a leading cause of irreversible blindness, necessitates early detection for accurate and timely intervention to prevent irreversible vision loss.
BEE-NET: A deep neural network to identify in-the-wild Bodily Expression of Emotions
In this study, we investigate how environmental factors, specifically the scenes and objects involved, can affect the expression of emotions through body language.
Deep Learning and Computer Vision for Glaucoma Detection: A Review
Glaucoma is the leading cause of irreversible blindness worldwide and poses significant diagnostic challenges due to its reliance on subjective evaluation.
Pain level and pain-related behaviour classification using GRU-based sparsely-connected RNNs
Because there is no dedicated benchmark database to analyse this correlation, we considered one of the specific circumstances that potentially influence a person's biometrics during daily activities in this study and classified pain level and pain-related behaviour in the EmoPain database.
A multi-stream convolutional neural network for classification of progressive MCI in Alzheimer's disease using structural MRI images
We propose a multi-stream deep convolutional neural network fed with patch-based imaging data to classify stable MCI and progressive MCI.
ADVISE: ADaptive Feature Relevance and VISual Explanations for Convolutional Neural Networks
To this end, we propose using adaptive bandwidth kernel density estimation to assign a relevance score to each unit of the feature map with respect to the predicted class.
A deep convolutional neural network for classification of Aedes albopictus mosquitoes
Monitoring the spread of disease-carrying mosquitoes is a first and necessary step to control severe diseases such as dengue, chikungunya, Zika or yellow fever.
On the use of uncertainty in classifying Aedes Albopictus mosquitoes
The estimated uncertainty was also used in an active learning framework, where just a portion of the data from large training sets was manually labelled.
Electrical activity of fungi: Spikes detection and complexity analysis
Oyster fungi \emph{Pleurotus djamor} generate actin potential like spikes of electrical potential.
A supervised active learning method for identifying critical nodes in Wireless Sensor Network
Energy Efficiency of a wireless sensor network (WSN) relies on its main characteristics, including hop-number, user's location, allocated power, and relay.
VICSOM: VIsual Clues from SOcial Media for psychological assessment
The contribution is two-fold: (i) we provide a large multimodal database from Instagram public profiles (more than 30, 000 images and text captions) annotated by expert Psychologists on each perceived behavior according to Glasser's theory, and (ii) we propose to automate the recognition of the (unconsciously) perceived needs by the users.
On complexity of branching droplets in electrical field
Decanol droplets in a thin layer of sodium decanoate with sodium chloride exhibit bifurcation branching growth due to interplay between osmotic pressure, diffusion and surface tension.
