Deep Convolutional Neural Network Model for Optical Microscopic Automated Diagnosis of Plasmodium Falciparum Parasites in Sub-Saharan Africa.

Domain:

healthcare

Record type:

paperposter

Deep Convolutional Neural Network Model for Optical Microscopic Automated Diagnosis of Plasmodium Falciparum Parasites in Sub-Saharan Africa.

Poster presented at the Deep Learning Indaba 2023 by Chikodili Ugwuishiwu

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Tasks

computer vision image classification

Light-Weight Deep Convolutional Neural Network Model for Classification of Potato Leaf Diseases

Potato leaf diseases pose a significant threat to global food security by reducing crop yields and e

Development and Validation of a MobileNetV2 Convolutional Neural Network for Automated Diagnosis of Tomato Fungal Diseases in Northern Nigeria

Accurate, field-deployable diagnostic tools are needed to close the diagnostic gap that limits fungi

Major subpopulations of Plasmodium falciparum in sub-Saharan Africa

Understanding genomic variation and population structure of Plasmodium falciparum across Africa is n

Convolutional neural network-based deep learning model for air quality prediction in October city of Egypt

Purpose Modern human society has continuous advancements that have a negative impact on the qualit

Automated stomata detection in oil palm with convolutional neural network

Abstract Stomatal density is an important trait for breeding selection of drought tolerant oil palm

Enhanced deep convolutional neural network for SARS-CoV-2 classification

Enhanced deep convolutional neural network for SARS-CoV-2 classification

Poster presented at the Deep Learning Indaba 2022 by Mike Mwanga