Home ›
Entities
› academia
› Anomaly Detection for Skin Lesion Images Using Convolutional Neural Network and Injection of Handcrafted Features: A Method That Bypasses the Preprocessing of Dermoscopic Images
Anomaly Detection for Skin Lesion Images Using Convolutional Neural Network and Injection of Handcrafted Features: A Method That Bypasses the Preprocessing of Dermoscopic Images
Research article (Algorithms, 2023) · cited 11× · AI/ML
Anomaly Detection for Skin Lesion Images Using Convolutional Neural Network and Injection of Handcrafted Features: A Method That Bypasses the Preprocessing of Dermoscopic Images
Summary
Anomaly Detection for Skin Lesion Images Using Convolutional Neural Network and Injection of Handcrafted Features: A Method That Bypasses the Preprocessing of Dermoscopic Images is a scholarly article[1].
Key Facts
Anomaly Detection for Skin Lesion Images Using Convolutional Neural Network and Injection of Handcrafted Features: A Method That Bypasses the Preprocessing of Dermoscopic Images's instance of is recorded as scholarly article[2].
References
Programmatic citations — every numbered marker resolves to a verifiable graph row below.
Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.
APA4ort.xyz Knowledge Graph. (2026). Anomaly Detection for Skin Lesion Images Using Convolutional Neural Network and Injection of Handcrafted Features: A Method That Bypasses the Preprocessing of Dermoscopic Images. Retrieved May 24, 2026, from https://4ort.xyz/entity/anomaly-detection-for-skin-lesion-images-using-convolutional-neural-network-and-injection-of-handcrafted-features-a-meth
MLA“Anomaly Detection for Skin Lesion Images Using Convolutional Neural Network and Injection of Handcrafted Features: A Method That Bypasses the Preprocessing of Dermoscopic Images.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/anomaly-detection-for-skin-lesion-images-using-convolutional-neural-network-and-injection-of-handcrafted-features-a-meth.
BibTeX@misc{4ortxyz_anomaly-detection-for-skin-lesion-images-using-convolutional-neural-network-and-injection-of-handcrafted-features-a-meth_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Anomaly Detection for Skin Lesion Images Using Convolutional Neural Network and Injection of Handcrafted Features: A Method That Bypasses the Preprocessing of Dermoscopic Images}}, year = {2026}, url = {https://4ort.xyz/entity/anomaly-detection-for-skin-lesion-images-using-convolutional-neural-network-and-injection-of-handcrafted-features-a-meth}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Anomaly Detection for Skin Lesion Images Using Convolutional Neural Network and Injection of Handcrafted Features: A Method That Bypasses the Preprocessing of Dermoscopic Images — https://4ort.xyz/entity/anomaly-detection-for-skin-lesion-images-using-convolutional-neural-network-and-injection-of-handcrafted-features-a-meth (retrieved 2026-05-24)
