mendeley lbc dataset (Mendeley Ltd)

About

News

Press Release

Team

Advisors

Partners

Contact

Bioz Stars

Bioz vStars

Buy from Supplier

Structured Review

Mendeley Ltd mendeley lbc dataset
Mendeley Lbc Dataset, supplied by Mendeley Ltd, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/mendeley+lbc+dataset/dataset+lbc+mendeley/pm42268916-330-2-2
Average 86 stars, based on 1 article reviews

mendeley lbc dataset - by Bioz Stars, 2026-09

86/100 stars

Images

other:

Article Title: Multi-scale feature integration with enhanced cytomorph for high-accuracy cervical cytology classification.
Article Snippet: Mendeley LBC dataset.

Article Title: Multi-scale feature integration with enhanced cytomorph for high-accuracy cervical cytology classification.
Article Snippet: For the Mendeley LBC dataset (Table 10), our model achieves 98.55% accuracy on the 4-class classification task, which is comparable to the state-of-the-art result of 98.79% by Zhao et al. [50] and superior to Pacal et al. [1] (98.02%).

Diagnostic Assay:

Article Title: Refining cell classification for cervical cancer detection using an improved high dimensional feature fusion approach.
Article Snippet: Introduction: Early and accurate classification of cervical cell images is essential for timely detection and prevention of cervical cancer.. Traditional cytological analysis methods, such as manual interpretation of Pap smears, are often labor-intensive and susceptible to human error.. Recent advances in deep learning offer promising solutions, yet many existing models lack generalization across datasets and struggle with multi-class classification challenges.

Modification:

Biomarker Discovery:

Article Title: Multi-scale feature integration with enhanced cytomorph for high-accuracy cervical cytology classification.
Article Snippet: .. Similarly, for the Mendeley LBC dataset (963 images), 674 images were used for training, 144 for validation, and 145 for testing. ..

Produced:

Imaging:

Article Title: Multi-scale feature integration with enhanced cytomorph for high-accuracy cervical cytology classification.
Article Snippet: .. Similarly, on the Mendeley LBC dataset, our model attained 99.42% accuracy, surpassing the best performing Vision Transformer (ViT-Small-Patch16 at 98.45%) by nearly 1%. https://doi.org/10.1371/journal.pone.0351063.g006 https://doi.org/10.1371/journal.pone.0351063.g007 PLOS One | https://doi.org/10.1371/journal.pone.0351063 June 10, 2026 23 / 32 These results highlight that while transfer learning models and Vision Transformers provide strong baseline performance for cervical cell classification, our specialized architecture effectively captures the unique morphological features of cervical cells, leading to enhanced discriminative capability across multiple datasets and imaging conditions. ..

Review