Explainable Artificial Intelligence: Importance, Use Domains, Stages, Output Shapes, and Challenges
There is an urgent need in many application areas for eXplainable ArtificiaI Intelligence
(XAI) approaches to boost people's confidence and trust in Artificial Intelligence methods …
(XAI) approaches to boost people's confidence and trust in Artificial Intelligence methods …
A lightweight deep learning-based model for tomato leaf disease classification
Tomato leaf diseases significantly impact crop production, necessitating early detection for
sustainable farming. Deep Learning (DL) has recently shown excellent results in identifying …
sustainable farming. Deep Learning (DL) has recently shown excellent results in identifying …
Automated brain tumor recognition using equilibrium optimizer with deep learning approach on MRI images
Brain tumours (BT) affect human health owing to their location. Artificial intelligence (AI) is
intended to assist in diagnosing and treating complex diseases by combining technologies …
intended to assist in diagnosing and treating complex diseases by combining technologies …
UMSSNet: a unified multi-scale segmentation network for heterogeneous medical images
Medical image analysis plays a pivotal role in diagnosis and treatment. However, the
diverse characteristics of various imaging modalities often demand distinct processing …
diverse characteristics of various imaging modalities often demand distinct processing …
Contrastive Deep Learning Reveals Age Biomarkers in Histopathological Skin Biopsies
As global life expectancy increases, so does the burden of chronic diseases, yet individuals
exhibit considerable variability in the rate at which they age. Identifying biomarkers that …
exhibit considerable variability in the rate at which they age. Identifying biomarkers that …
TLEABLCNN: Brain and Alzheimer's Disease Detection using Attention based Explainable Deep Learning and SMOTE using Imbalanced Brain MRI
Alzheimer's disease (AD) is one of the primary causes of dementia. It degenerates the brain
and reduces the activity of individuals by disrupting their memory and physiological …
and reduces the activity of individuals by disrupting their memory and physiological …
Brain Tumor Segmentation Using Semi-supervised Learning
Accurate segmentation of brain tumors is crucial for diagnosis and treatment planning in
neuroimaging. Using labeled and unlabeled data and leveraging semi-supervised learning …
neuroimaging. Using labeled and unlabeled data and leveraging semi-supervised learning …
Deep-Learning and Geometric Mean Optimizer Combined Scheme for Brain MRI Classification
Disease in brain is one of the medical emergencies and appropriate diagnoses and
treatment is necessary. Medical imaging-assisted Brain Condition Monitoring (BCM) is one …
treatment is necessary. Medical imaging-assisted Brain Condition Monitoring (BCM) is one …