Back to search

Article

Comparative Evaluation of Deep CNN Architectures for Pattern Recognition in Mouse Brain Tissue Section Images

2026-08-25

Abstract excerpt

Accurate pattern recognition in biological tissue section images is critical for advancing biomedical research, particularly in diagnostics and neuroscience. However, variability in cellular morphology, imaging artifacts, and structural heterogeneity poses significant challenges for automated analysis. Conventional image-processing approaches often lack generalizability across datasets, highlighting the need for m...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
dea41df4-e196-570c-b7b0-72c8aae51be6
DOI
10.20944/preprints202608.1738.v1
Open publication

Related research

Semantic proximity does not establish scientific evidence. Graph snapshot: 2026-09-29.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
Comparative Evaluation of Deep CNN Architectures for Pattern Recognition in Mouse Brain Tissue Section ImagesDOI 10.20944/preprints202608.1738.v1
Select a neighboring publication to make it the new centre.