Back to search

Article

A Lightweight Hybrid CNN–CBAM Model for Multistage Acute Lymphoblastic Leukemia Classification from Peripheral Blood Smear Images

2026-02-26

Abstract excerpt

Accurate and efficient classification of hematological malignancies from peripheral blood smear (PBS) images remains challenging due to the scarcity of annotated datasets, staining variability, and subtle morphological differences among blood cancer sub-types. To address these limitations, this study proposes an Advanced Lightweight Deep Learning (ALDL) framework for the multi-class classification of Acute Lymphob...

Topics

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

Identifiers and source

Literature Corpus work
af8edf46-7b54-5526-b422-4c007261b611
DOI
10.20944/preprints202602.1601.v1
Open publication

Related research

Semantic proximity does not establish scientific evidence.

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.
A Lightweight Hybrid CNN–CBAM Model for Multistage Acute Lymphoblastic Leukemia Classification from Peripheral Blood Smear ImagesDOI 10.20944/preprints202602.1601.v1
Select a neighboring publication to make it the new centre.