[HTML][HTML] A comprehensive survey of deep learning algorithms and applications in dental radiograph analysis
The Integration of machine learning and traditional image processing in dentistry has
resulted in many applications like automatic teeth identification and numbering, caries …
resulted in many applications like automatic teeth identification and numbering, caries …
Revolutionizing Healthcare: How Machine Learning is Transforming Patient Diagnoses-a Comprehensive Review of AI's Impact on Medical Diagnosis
The integration of machine learning into healthcare heralds a new era where the
convergence of technology and human compassion reshapes the very essence of healing …
convergence of technology and human compassion reshapes the very essence of healing …
Graph convolution networks for social media trolls detection use deep feature extraction
M Asif, M Al-Razgan, YA Ali, L Yunrong - Journal of Cloud Computing, 2024 - Springer
This study presents a novel approach to identifying trolls and toxic content on social media
using deep learning. We developed a machine-learning model capable of detecting toxic …
using deep learning. We developed a machine-learning model capable of detecting toxic …
Novel transfer learning based deep features for diagnosis of down syndrome in children using facial images
Down syndrome is a chromosomal condition characterized by the existence of an additional
copy of chromosome 21. This genetic anomaly leads to a range of developmental …
copy of chromosome 21. This genetic anomaly leads to a range of developmental …
A novel hybrid model in the diagnosis and classification of Alzheimer's disease using EEG signals: Deep ensemble learning (DEL) approach
Recent years have witnessed a surge of sophisticated computer-aided diagnosis techniques
involving Artificial Intelligence (AI) to accurately diagnose and classify Alzheimer's disease …
involving Artificial Intelligence (AI) to accurately diagnose and classify Alzheimer's disease …
[HTML][HTML] A triplanar ensemble model for brain tumor segmentation with volumetric multiparametric magnetic resonance images
Automated segmentation methods can produce faster segmentation of tumors in medical
images, aiding medical professionals in diagnosis and treatment plans. A 3D U-Net method …
images, aiding medical professionals in diagnosis and treatment plans. A 3D U-Net method …
Evaluating Retinal Disease Diagnosis with an Interpretable Lightweight CNN Model Resistant to Adversarial Attacks
Optical Coherence Tomography (OCT) is an imperative symptomatic tool empowering the
diagnosis of retinal diseases and anomalies. The manual decision towards those anomalies …
diagnosis of retinal diseases and anomalies. The manual decision towards those anomalies …
Intelligent ultrasound imaging for enhanced breast cancer diagnosis: Ensemble transfer learning strategies
According to WHO statistics for 2018, there are 1.2 million cases and 700,000 deaths from
breast cancer (BC) each year, making it the second-highest cause of mortality for women …
breast cancer (BC) each year, making it the second-highest cause of mortality for women …
Comparative Analysis Of AI Regression And Classification Models For Predicting House Damages İn Nepal: Proposed Architectures And Techniques
This paper proposes a machine-learning model for earthquake prediction. Earthquakes are
complex and unpredictable natural phenomena, making it challenging to predict them …
complex and unpredictable natural phenomena, making it challenging to predict them …
Model compression of deep neural network architectures for visual pattern recognition: Current status and future directions
S Bhalgaonkar, M Munot - Computers and Electrical Engineering, 2024 - Elsevier
Abstract Visual Pattern Recognition Networks (VPRNs) are widely used in various visual
data based applications such as computer vision and edge AI. VPRNs help to enhance a …
data based applications such as computer vision and edge AI. VPRNs help to enhance a …