Facial emotion recognition for photo and video surveillance based on machine learning and visual analytics
Featured Application Can be used in video surveillance systems for large groups of people.
Abstract Modern video surveillance systems mainly rely on human operators to monitor and …
Abstract Modern video surveillance systems mainly rely on human operators to monitor and …
An Adaptation of the Input Doubling Method for Solving Classification Tasks in Case of Small Data Processing
In the era of big data processing, numerous techniques prove valuable for analyzing large-
scale datasets. However, the efficient processing of small data is equally crucial, particularly …
scale datasets. However, the efficient processing of small data is equally crucial, particularly …
Multi-stage segmentation and cascade classification methods for improving cardiac MRI analysis
The segmentation and classification of cardiac magnetic resonance imaging are critical for
diagnosing heart conditions, yet current approaches face challenges in accuracy and …
diagnosing heart conditions, yet current approaches face challenges in accuracy and …
[HTML][HTML] Towards Transparent AI in Medicine: ECG-Based Arrhythmia Detection with Explainable Deep Learning
Cardiovascular diseases are the leading cause of death globally, highlighting the need for
accurate diagnostic tools. To address this issue, we introduce a novel approach for …
accurate diagnostic tools. To address this issue, we introduce a novel approach for …
A novel feature vector for ECG classification using deep learning
Анотація In the past decade, deep learning techniques have been widely used in the
healthcare industry to detect heartbeats and diagnose heart conditions. However, these …
healthcare industry to detect heartbeats and diagnose heart conditions. However, these …
Explainable Deep Learning for Interpretable Brain Tumor Diagnosis from MRI Images
This paper presents a new method for analyzing medical images using neural networks to
improve the interpretation and explainability of diagnostic decisions. The method combines …
improve the interpretation and explainability of diagnostic decisions. The method combines …
An Approach Towards Reducing Training Time of the Input Doubling Method via Clustering for Middle-Sized Data Analysis
Intellectual analysis of small and middle-sized datasets through machine learning tools
presents challenges in various application domains. Existing methods fail to provide …
presents challenges in various application domains. Existing methods fail to provide …
[PDF][PDF] Explainable Deep Learning for Cardiac MRI: Multi-Stage Segmentation, Cascade Classification, and Visual Interpretation
Cardiac MRI images are vital in diagnosing a range of heart diseases, yet standard solutions
frequently struggle with inadequate region delineation, confusion among similar …
frequently struggle with inadequate region delineation, confusion among similar …
[PDF][PDF] Enhancing medical NLI with integrated domain knowledge and sentiment analysis
O Chaban, E Manziuk - 2024 - ceur-ws.org
Recent advancements in biomedical embeddings derived from language models, such as
BioELMo, have demonstrated superior performance in textual inference tasks within the …
BioELMo, have demonstrated superior performance in textual inference tasks within the …
Explainable Deep Learning
This paper presents a new method for analyzing medical images using neural networks to
improve the interpretation and explainability of diagnostic decisions. The method combines …
improve the interpretation and explainability of diagnostic decisions. The method combines …