Home ›
Entities
› academia
› Super-resolution reconstruction of terahertz images based on a deep-learning network with a residual channel attention mechanism
Super-resolution reconstruction of terahertz images based on a deep-learning network with a residual channel attention mechanism
Research article (Applied Optics, 2022) · cited 26× · AI/ML
Super-resolution reconstruction of terahertz images based on a deep-learning network with a residual channel attention mechanism
Summary
Super-resolution reconstruction of terahertz images based on a deep-learning network with a residual channel attention mechanism is a scholarly article[1].
Key Facts
Super-resolution reconstruction of terahertz images based on a deep-learning network with a residual channel attention mechanism'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). Super-resolution reconstruction of terahertz images based on a deep-learning network with a residual channel attention mechanism. Retrieved May 24, 2026, from https://4ort.xyz/entity/super-resolution-reconstruction-of-terahertz-images-based-on-a-deep-learning-network-with-a-residual-channel-attention-m
MLA“Super-resolution reconstruction of terahertz images based on a deep-learning network with a residual channel attention mechanism.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/super-resolution-reconstruction-of-terahertz-images-based-on-a-deep-learning-network-with-a-residual-channel-attention-m.
BibTeX@misc{4ortxyz_super-resolution-reconstruction-of-terahertz-images-based-on-a-deep-learning-network-with-a-residual-channel-attention-m_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Super-resolution reconstruction of terahertz images based on a deep-learning network with a residual channel attention mechanism}}, year = {2026}, url = {https://4ort.xyz/entity/super-resolution-reconstruction-of-terahertz-images-based-on-a-deep-learning-network-with-a-residual-channel-attention-m}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Super-resolution reconstruction of terahertz images based on a deep-learning network with a residual channel attention mechanism — https://4ort.xyz/entity/super-resolution-reconstruction-of-terahertz-images-based-on-a-deep-learning-network-with-a-residual-channel-attention-m (retrieved 2026-05-24)
