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by IQAC KIITKIIT Deemed to be University — Internal Quality Assurance Cell

Publication2022

Deep Convolutional Neural Network (Falcon) and transfer learning‐based approach to detect malarial parasite

The record

Type
Publication
Date
1 April 2022
Level
National
Journal
Multimedia Tools and Applications
Volume
81
Issue
10
Pages
13237-13251
Published
1 April 2022
DOI
10.1007/s11042-021-10946-5
Scopus ID
85105383178
ISSN
13807501
Authors
6
Open access
No
Citations
34
International co-authorship
No
Co-author countries
IN

Classification

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UN Sustainable Development Goals

  1. 3 Ensure healthy lives and promote well-being for all at all ages

    GoalPrimaryHigh confidenceJudged

    Deep convolutional neural network Falcon detects malarial parasites from blood smeared slide images with 95.2% accuracy

    High confidence
    The subject matter is a strong and direct inference from the record type, the funding or organising body, or the programme context, even where the title alone is thin. Example: an ICMR-funded project against SDG 3, on the strength of the agency.
    Judged
    Judged against the published classification rubric, under the rubric and prompt versions recorded with the run that produced it.
    Produced by
    claude-haiku-4-5-20251001, under kortex-publication-v1

Viksit Bharat @2047

  1. vb-3.2 Digital technology and artificial intelligence

    Sub-themePrimaryHigh confidenceJudged

    AI-powered malaria diagnostics advances digital technology for disease detection and public health

    Produced by
    claude-haiku-4-5-20251001, under kortex-publication-v1

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KIIT Deemed to be University. “Deep Convolutional Neural Network (Falcon) and transfer learning‐based approach to detect malarial parasite”. Kortex.

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