TumorSageNet CNN hybrid architecture enables accurate detection of mango leaf pathologies.
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| Title: | TumorSageNet CNN hybrid architecture enables accurate detection of mango leaf pathologies. |
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| Authors: | Ghosh H; School of Computer Science and Engineering (SCOPE), VIT-AP University, Amaravati, Andhra Pradesh, India., Rahat IS; School of Computer Science and Engineering (SCOPE), VIT-AP University, Amaravati, Andhra Pradesh, India., Hossain MZ; Grand Canyon University, Phoenix, USA., Emon MMR; Department of Computer Science and Engineering, American International University, Dhaka, Bangladesh., Kant S; Department of Management, College of Business and Economics, Bule Hora University, Bule Hora, Ethiopia. skant317@gmail.com., Maniruzzaman M; Department of Electrical and Computer Engineering, School of Engineering, San Francisco Bay University, Fremont, CA, 94539, USA. |
| Source: | Scientific reports [Sci Rep] 2026 Feb 25; Vol. 16 (1). Date of Electronic Publication: 2026 Feb 25. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
| ISSN: | 2045-2322 |
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| DOI: | 10.1038/s41598-026-40944-2 |
