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A Deep CNN Transformer Hybrid Model for Skin Lesion Classification of Dermoscopic Images Using Focal Loss paper
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Paper

A Deep CNN Transformer Hybrid Model for Skin Lesion Classification of Dermoscopic Images Using Focal Loss

013ceb6f76eb994bcf2701e7b92de9d3a69060fa
Free2AITools Nexus Index
69.7
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 87
P: Popularity 63
R: Recency 100
Q: Quality 65
Tech Context
Vital Performance —

Skin cancers are the most cancers diagnosed worldwide, with an estimated > 1.5 million new cases in 2020. Use of computer-aided diagnosis (CAD) systems for early detection and classification of skin lesions helps reduce skin cancer mortality rates. Inspired by the success of the transformer network in natural language processing (NLP) and the deep convolutional neural network (DCNN) in computer vision, we propose an end-to-end CNN transformer hybrid model with a focal loss (FL) function to cl...

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Semantic Scholar 106 Citations
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Registry ID 013ceb6f76eb994bcf2701e7b92de9d3a69060fa
License ArXiv
Provider semantic_scholar
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Academic & Research Attribution

BibTeX 
@misc{013ceb6f76eb994bcf2701e7b92de9d3a69060fa,
  title = {A Deep CNN Transformer Hybrid Model for Skin Lesion Classification of Dermoscopic Images Using Focal Loss Paper},
  howpublished = {\url{https://api.semanticscholar.org/013ceb6f76eb994bcf2701e7b92de9d3a69060fa}},
  note = {Accessed via Free2AITools.}
}
APA Style
A Deep CNN Transformer Hybrid Model for Skin Lesion Classification of Dermoscopic Images Using Focal Loss [Paper]. Free2AITools. https://api.semanticscholar.org/013ceb6f76eb994bcf2701e7b92de9d3a69060fa

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Methodology How FNI works
Semantic (S) 50

Query-time baseline · scored live at search

Authority (A) 87
Popularity (P) 63
Recency (R) 100
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for A Deep CNN Transformer Hybrid Model for Skin Lesion Classification of Dermoscopic Images Using Focal Loss: Authority (A:87), Popularity (P:63), Recency (R:100), Quality (Q:65). Semantic (S) is a query-time baseline scored live at search.

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πŸ“ Executive Summary

"Skin cancers are the most cancers diagnosed worldwide, with an estimated > 1.5 million new cases in 2020. Use of computer-aided diagnosis (CAD) systems for early detection and classification of skin lesions helps reduce skin cancer mortality rates. Inspired by the success of the transformer network in natural language processing (NLP) and the deep convolutional neural network (DCNN) in computer vision, we propose an end-to-end CNN transformer hybrid model with a focal loss (FL) function to cl..."

❝ Cite Node 

@article{A,
  title={A Deep CNN Transformer Hybrid Model for Skin Lesion Classification of Dermoscopic Images Using Focal Loss},
  note={Indexed by Free2AITools}
}

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πŸ“Š Research Signals

πŸ“ˆ106CitationsSemantic Scholar
πŸ›οΈ87AuthorityFNI pillar
⏱️100RecencyFNI pillar
βœ…65QualityFNI pillar
πŸ—‚οΈtext generationField

🏷️ Research Topics

vision modelstransformer architecture
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