AIMC Topic: Deep Learning

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Unveiling encephalopathy signatures: A deep learning approach with locality-preserving features and hybrid neural network for EEG analysis.

Neuroscience letters
EEG signals exhibit spatio-temporal characteristics due to the neural activity dispersion in space over the brain and the dynamic temporal patterns of electrical activity in neurons. This study tries to effectively utilize the spatio-temporal nature ...

Integrating deep learning algorithms for forecasting evapotranspiration and assessing crop water stress in agricultural water management.

Journal of environmental management
The increasing impacts of climate change on global agriculture necessitate the development of advanced predictive models for efficient water management in crop fields. This study aims to enhance the forecasting of evapotranspiration (ET), potential e...

Predicting survival in malignant glioma using artificial intelligence.

European journal of medical research
Malignant gliomas, including glioblastoma, are amongst the most aggressive primary brain tumours, characterised by rapid progression and a poor prognosis. Survival analysis is an essential aspect of glioma management and research, as most studies use...

Towards unbiased skin cancer classification using deep feature fusion.

BMC medical informatics and decision making
This paper introduces SkinWiseNet (SWNet), a deep convolutional neural network designed for the detection and automatic classification of potentially malignant skin cancer conditions. SWNet optimizes feature extraction through multiple pathways, emph...

A deep learning model for assistive decision-making during robot-aided rehabilitation therapies based on therapists' demonstrations.

Journal of neuroengineering and rehabilitation
BACKGROUND: A promising approach to improving motor recovery during rehabilitation is the use of robotic rehabilitation devices. These robotic devices provide tools to monitor the patient's recovery progress while providing highly standardized and in...

Automated strabismus detection and classification using deep learning analysis of facial images.

Scientific reports
Strabismus, or eye misalignment, is a common condition affecting individuals of all ages. Early detection and accurate classification are essential for proper treatment and avoiding long-term complications. This research presents a new deep-learning-...

Localization and detection of deepfake videos based on self-blending method.

Scientific reports
Deepfake technology, which encompasses various video manipulation techniques implemented through deep learning algorithms-such as face swapping and expression alteration-has advanced to generate fake videos that are increasingly difficult for human o...

Comparison of deep transfer learning models for classification of cervical cancer from pap smear images.

Scientific reports
Cervical cancer is one of the most commonly diagnosed cancers worldwide, and it is particularly prevalent among women living in developing countries. Traditional classification algorithms often require segmentation and feature extraction techniques t...

Self-supervised parametric map estimation for multiplexed PET with a deep image prior.

Physics in medicine and biology
Multiplexed positron emission tomography (mPET) imaging allows simultaneous observation of physiological and pathological information from multiple tracers in a single PET scan. Although supervised deep learning has demonstrated superior performance ...

GGSYOLOv5: Flame recognition method in complex scenes based on deep learning.

PloS one
The continuous development of the field of artificial intelligence, not only makes people's lives more convenient but also plays a role in the supervision and protection of people's lives and property safety. News of the fire is not uncommon, and fir...