Results 81 to 90 of about 4,123 (220)
SkinSage XAI: An explainable deep learning solution for skin lesion diagnosis
The research was meant to disentangle the difficulties of skin lesion diagnosis using a multimodal approach. Our suggested technique offers unparalleled levels of transparency and interpretability in skin lesion categorization and marks a substantial improvement in the area via methodical methodology and meticulous refining.
Geetika Munjal +4 more
wiley +1 more source
Handle local optimum traps in CBIR systems
Existing CBIR systems, designed around query refinement based on relevance feedback, suffer from local optimum traps. That is, when the user is examining a relevant cluster surrounded by less relevant images, essentially the same set of images will be ...
Danzhou Liu +5 more
core +1 more source
Query-sensitive similarity measure for content-based image retrieval using meta-heuristic algorithm
Content based image retrieval (CBIR) systems retrieve images linked to the query image (QI) from enormous databases. The feature sets extracted by the present CBIR systems are limited. This limits the systems’ effectiveness.
Mutasem K. Alsmadi
doaj +1 more source
The beneficial human gut bacterium Akkermansia muciniphila provides metabolites to other members of the gut microbiota by breaking down host mucin, but most of its other metabolic functions have not been investigated. A.
Kenny C. Mok +6 more
doaj +1 more source
In Vivo Optogenetics Based on Heavy Metal‐Free Photon Upconversion Nanoparticles
In vivo, optogenetics using photon upconversion (TTA‐UC) based on triplet‐triplet annihilation is demonstrated. The modification of a thermally‐activated delayed fluorescence (TADF) sensitizer with a bromo group promotes intersystem crossing and enables high TTA‐UC efficiency at weak excitation light intensities even without using heavy metals.
Masanori Uji +8 more
wiley +1 more source
Relevance feedback has gained much interest from researchers in the discipline of content-based image retrieval (CBIR). However, such approach is rarely used in the content-based medical image retrieval (CBMIR) systems.
Fung, C.C., Chung, K.P.
core
Skin cancer identification utilizing deep learning: A survey
This study provides a survey on skin cancer identification using DL techniques utilized in studies from 2017 to 2024. The authors address the latest related studies covering several public skin cancer image datasets and focusing on segmentation, classification based on Convolutional Neural Networks and vision transformers, and explainability.
Dulani Meedeniya +3 more
wiley +1 more source
Developing a smart pacs: Cbir system using deep learning
With the growing number of digital medical imaging records, the need for an automatic procedure to retrieve only data of interest is of increasing importance.
Moscato V. +4 more
core +1 more source
Content based image retrieval using hybrid features and various distance metric
In last decade, large database of images have grown rapidly and will continue in future. Retrieval and querying of these image in efficient way is needed in order to access the visual content from large database.
Yogita Mistry, D.T. Ingole, M.D. Ingole
doaj +1 more source
Advances in medical image analysis: A comprehensive survey of lung infection detection
This paper reviews state‐of‐the‐art architectural models for lung image analysis for segmentation, classification and multi‐tasks. Abstract This research investigates advanced approaches in medical image analysis, specifically focusing on segmentation and classification techniques, as well as their integration into multi‐task architectures for lung ...
Shirin Kordnoori +3 more
wiley +1 more source

