The DOI matches its Crossref record; 68 of the 69 references it cites were found in a registry or an index.
Eff2Net: An efficient channel attention-based convolutional neural network for skin disease classification
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Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“Karthik et al (2022) utilized a modified attention-based CNN to differentiate acne from psoriasis, actinic keratosis, and melanoma.”
From Artificial intelligence–enabled precision medicine for inflammatory skin diseases (2026) · cites this paper as Karthik et al, 2022
Citations
Cites
ImageNet: A large-scale hierarchical image database
Deng, J., Dong, W., Socher, R., Li, L.-J., Li, K., & Fei-Fei, L. (2009) · 2009 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2009.5206848 · Cited by 65,333
MobileNetV2: Inverted Residuals and Linear Bottlenecks
Sandler, M., Howard, A., Zhu, M., Zhmoginov, A., & Chen, L.-C. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2018.00474 · Cited by 28,755
A survey on Image Data Augmentation for Deep Learning
Shorten, C., & Khoshgoftaar, T. M. (2019) · Journal of Big Data · doi:10.1186/s40537-019-0197-0 · Cited by 13,203
Squeeze-and-Excitation Networks
Hu, J., Shen, L., Albanie, S., Sun, G., & Wu, E. (2020) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2019.2913372 · Cited by 12,157
ECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networks
Wang, Q., Wu, B., Zhu, P., Li, P., Zuo, W., & Hu, Q. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr42600.2020.01155 · Cited by 9,641
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition
(2018) · doi:10.1109/cvpr40276.2018 · Cited by 4,769
2008 IEEE Conference on Computer Vision and Pattern Recognition
(2008) · doi:10.1109/cvpr12618.2008 · Cited by 4,263
2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
(2019) · doi:10.1109/cvpr41558.2019 · Cited by 1,796
Seven-point checklist and skin lesion classification using multitask multimodal neural nets
Kawahara, J., Daneshvar, S., Argenziano, G., & Hamarneh, G. (2019) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2018.2824327 · Cited by 584
2016 23rd International Conference on Pattern Recognition (ICPR)
(2016) · doi:10.1109/icpr40739.2016 · Cited by 476
Flagged first, then by citations
1 of the 69 references couldn’t be matched to a known paper.
Research works printed but not linked: 3
- M. Tan, Q.V. Le, EfficientNet: Rethinking model scaling for convolutional Neural Networks, arXiv [cs.LG], 2019.
- M. Tan, Q.V. Le, EfficientNetV2: Smaller models and faster training, arXiv [cs.CV], 2021.
- P. Ramachandran, B. Zoph, Q.V. Le, Swish: A self-gated activation function, Arxiv.org. [Online]. Available: http://arxiv.org/abs/1710.05941v1. [Accessed: 17-Oct-2021]. · arXiv
Cited by
Sorted by citations
Zhang, J., Zhong, F., He, K., Ji, M., Li, S., & Li, C. (2023) · Diagnostics · doi:10.3390/diagnostics13233506 · Cited by 106
Sünnetci, K. M., Ulukaya, S., & Alkan, A. (2022) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2022.103844 · Cited by 71
A Skin Disease Classification Model Based on DenseNet and ConvNeXt Fusion
Wei, M., Wu, Q., Ji, H., Wang, J., Lyu, T., Liu, J., & Zhao, L. Y. (2023) · Electronics · doi:10.3390/electronics12020438 · Cited by 76
Enhanced Deep Learning Approach for Accurate Eczema and Psoriasis Skin Detection
Hammad, M. A., Pławiak, P., ELAffendi, M. A., El‐Latif, A. A. A., & Latif, A. A. A. (2023) · Sensors · doi:10.3390/s23167295 · Cited by 68
Mohan, J., Sivasubramanian, A., Sowmya, V., & Ravi, V. (2025) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2025.110007 · Cited by 88
“Karthik et al. [16] developed Eff2Net, a CNN that employs a channel attention block called ECA rather than the typical module to identify skin diseases.”
Metadata
- Authors
- Karthik, R., Vaichole, T. S., Kulkarni, S. K., Yadav, O., & Khan, F.
- Affiliations
- Vellore Institute of Technology University (IN)
- Corresponding author
- Karthik, R
- Venue
- Biomedical Signal Processing and Control
- Publisher
- Elsevier BV
- Published
- 2022-03
- Volume
- 73
- Pages
- 103406
- ISSN
- 1746-8094 (ISSN-L)
- OpenAlex
- W4200221062
- Cited by
- 152
- References
- 69
- Citations by year
- 2026: 24 · 2025: 45 · 2024: 41 · 2023: 30 · 2022: 12
- FWCI
- 7.56
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Biomedical Signal Processing and Control (publishedVersion)
- Topics
- Health Sciences › Medicine › Oncology › Cutaneous Melanoma Detection and Management
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Neural Network Applications
- Physical Sciences › Computer Science › Artificial Intelligence › AI in cancer detection
- Keywords
- skin disease classification, EfficientNetV2, efficient channel attention, channel attention, parameter reduction, acne, actinic keratosis, melanoma, psoriasis, dermatological image analysis
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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