Deep learning approach to detect malaria from microscopic images
A Vijayalakshmi - Multimedia Tools and Applications, 2020 - Springer
Malaria is an infectious disease which is caused by plasmodium parasite. Several image
processing and machine learning based techniques have been employed to diagnose …
processing and machine learning based techniques have been employed to diagnose …
Deep malaria parasite detection in thin blood smear microscopic images
Malaria is a disease activated by a type of microscopic parasite transmitted from infected
female mosquito bites to humans. Malaria is a fatal disease that is endemic in many regions …
female mosquito bites to humans. Malaria is a fatal disease that is endemic in many regions …
A novel data augmentation convolutional neural network for detecting malaria parasite in blood smear images
Malaria fever is a potentially fatal disease caused by the Plasmodium parasite. Identifying
Plasmodium parasites in blood smear images can help diagnose malaria fever rapidly and …
Plasmodium parasites in blood smear images can help diagnose malaria fever rapidly and …
A Novel Deep Convolutional Neural Network Model to Monitor People following Guidelines to Avoid COVID‐19
COVID‐19, a deadly disease that originated in Wuhan, China, has resulted in a global
outbreak. Patients infected with the causative virus SARS‐CoV‐2 are placed in quarantine …
outbreak. Patients infected with the causative virus SARS‐CoV‐2 are placed in quarantine …
An efficient model of residual based convolutional neural network with Bayesian optimization for the classification of malarial cell images
A Diker - Computers in Biology and Medicine, 2022 - Elsevier
Background Malaria is a disease caused by the Plasmodium parasite, which results in
millions of deaths in the human population worldwide each year. It is therefore considered a …
millions of deaths in the human population worldwide each year. It is therefore considered a …
Malaria parasite detection in thick blood smear microscopic images using modified YOLOV3 and YOLOV4 models
Background Manual microscopic examination of Leishman/Giemsa stained thin and thick
blood smear is still the “gold standard” for malaria diagnosis. One of the drawbacks of this …
blood smear is still the “gold standard” for malaria diagnosis. One of the drawbacks of this …
[PDF][PDF] A deep learning model for malaria disease detection and analysis using deep convolutional neural networks
Malaria is a very infectious disease that is caused by female anopheles mosquito. This
disease not only harms humans but also animals. If this disease not diagnosed properly in …
disease not only harms humans but also animals. If this disease not diagnosed properly in …
A comparative analysis of deep learning architectures on high variation malaria parasite classification dataset
Malaria, one of the leading causes of death in underdeveloped countries, is primarily
diagnosed using microscopy. Computer-aided diagnosis of malaria is a challenging task …
diagnosed using microscopy. Computer-aided diagnosis of malaria is a challenging task …
Automatic identification of malaria and other red blood cell inclusions using convolutional neural networks
Malaria is a serious disease responsible for thousands of deaths each year. Many efforts
have been made to aid in the diagnosis of malaria using machine learning techniques, but …
have been made to aid in the diagnosis of malaria using machine learning techniques, but …
Automatic detection of Plasmodium parasites from microscopic blood images
Malaria is caused by Plasmodium parasite. It is transmitted by female Anopheles bite. Thick
and thin blood smears of the patient are manually examined by an expert pathologist with …
and thin blood smears of the patient are manually examined by an expert pathologist with …