Home ›
Entities
› academia
› DT2F-TLNet: A novel text-independent writer identification and verification model using a combination of deep type-2 fuzzy architecture and Transfer Learning networks based on handwriting data
DT2F-TLNet: A novel text-independent writer identification and verification model using a combination of deep type-2 fuzzy architecture and Transfer Learning networks based on handwriting data
Research article (Expert Systems with Applications, 2023) · cited 21× · AI/ML
DT2F-TLNet: A novel text-independent writer identification and verification model using a combination of deep type-2 fuzzy architecture and Transfer Learning networks based on handwriting data
Summary
DT2F-TLNet: A novel text-independent writer identification and verification model using a combination of deep type-2 fuzzy architecture and Transfer Learning networks based on handwriting data is a scholarly article[1].
Key Facts
DT2F-TLNet: A novel text-independent writer identification and verification model using a combination of deep type-2 fuzzy architecture and Transfer Learning networks based on handwriting data'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). DT2F-TLNet: A novel text-independent writer identification and verification model using a combination of deep type-2 fuzzy architecture and Transfer Learning networks based on handwriting data. Retrieved May 24, 2026, from https://4ort.xyz/entity/dt2f-tlnet-a-novel-text-independent-writer-identification-and-verification-model-using-a-combination-of-deep-type-2-fuzz
MLA“DT2F-TLNet: A novel text-independent writer identification and verification model using a combination of deep type-2 fuzzy architecture and Transfer Learning networks based on handwriting data.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/dt2f-tlnet-a-novel-text-independent-writer-identification-and-verification-model-using-a-combination-of-deep-type-2-fuzz.
BibTeX@misc{4ortxyz_dt2f-tlnet-a-novel-text-independent-writer-identification-and-verification-model-using-a-combination-of-deep-type-2-fuzz_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{DT2F-TLNet: A novel text-independent writer identification and verification model using a combination of deep type-2 fuzzy architecture and Transfer Learning networks based on handwriting data}}, year = {2026}, url = {https://4ort.xyz/entity/dt2f-tlnet-a-novel-text-independent-writer-identification-and-verification-model-using-a-combination-of-deep-type-2-fuzz}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): DT2F-TLNet: A novel text-independent writer identification and verification model using a combination of deep type-2 fuzzy architecture and Transfer Learning networks based on handwriting data — https://4ort.xyz/entity/dt2f-tlnet-a-novel-text-independent-writer-identification-and-verification-model-using-a-combination-of-deep-type-2-fuzz (retrieved 2026-05-24)
