Home › Entities › academia › Hybrid Feature Extraction Approach for Robust Brain Tumor Classification: HOG, GLCM, and Artificial Neural Network

Hybrid Feature Extraction Approach for Robust Brain Tumor Classification: HOG, GLCM, and Artificial Neural Network

Research article (2024 6th International Conference on Electrical Engineering and Information & Communication Technology (ICEEICT), 2024) · cited 18× · AI/ML
academia openalex:W4398546293
Press Enter · cited answer in seconds

Hybrid Feature Extraction Approach for Robust Brain Tumor Classification: HOG, GLCM, and Artificial Neural Network

Summary

Hybrid Feature Extraction Approach for Robust Brain Tumor Classification: HOG, GLCM, and Artificial Neural Network is a scholarly article[1].

Key Facts

  • Hybrid Feature Extraction Approach for Robust Brain Tumor Classification: HOG, GLCM, and Artificial Neural Network's instance of is recorded as scholarly article[2].

References

Programmatic citations — every numbered marker resolves to a verifiable graph row below.

Direct Wikidata claims

  1. [2] ↑ . wikidata.org.

Class ancestry

  1. [1] ↑ . Wikidata. wikidata.org.

📑 Cite this page

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.

APA 4ort.xyz Knowledge Graph. (2026). Hybrid Feature Extraction Approach for Robust Brain Tumor Classification: HOG, GLCM, and Artificial Neural Network. Retrieved May 24, 2026, from https://4ort.xyz/entity/hybrid-feature-extraction-approach-for-robust-brain-tumor-classification-hog-glcm-and-artificial-neural-network
MLA “Hybrid Feature Extraction Approach for Robust Brain Tumor Classification: HOG, GLCM, and Artificial Neural Network.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/hybrid-feature-extraction-approach-for-robust-brain-tumor-classification-hog-glcm-and-artificial-neural-network.
BibTeX @misc{4ortxyz_hybrid-feature-extraction-approach-for-robust-brain-tumor-classification-hog-glcm-and-artificial-neural-network_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Hybrid Feature Extraction Approach for Robust Brain Tumor Classification: HOG, GLCM, and Artificial Neural Network}}, year = {2026}, url = {https://4ort.xyz/entity/hybrid-feature-extraction-approach-for-robust-brain-tumor-classification-hog-glcm-and-artificial-neural-network}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Hybrid Feature Extraction Approach for Robust Brain Tumor Classification: HOG, GLCM, and Artificial Neural Network — https://4ort.xyz/entity/hybrid-feature-extraction-approach-for-robust-brain-tumor-classification-hog-glcm-and-artificial-neural-network (retrieved 2026-05-24)

Canonical URL: https://4ort.xyz/entity/hybrid-feature-extraction-approach-for-robust-brain-tumor-classification-hog-glcm-and-artificial-neural-network · Last refreshed: