GitHub / sauravmishra1710 / Malaria-Detection-Using-Deep-Learning-Techniques
Malaria Parasite Detection using Efficient Neural Ensembles. Malaria, a life threatening disease caused by the bite of the Anopheles mosquito infected with the parasite, has been a major burden towards healthcare for years leading to approximately 400,000 deaths globally every year. This study aims to build an efficient system by applying ensemble techniques based on deep learning to automate the detection of the parasite using whole slide images of thin blood smears.
Stars: 9
Forks: 5
Open issues: 0
License: cc-by-sa-4.0
Language: Jupyter Notebook
Size: 295 MB
Dependencies parsed at: Pending
Created at: almost 4 years ago
Updated at: over 1 year ago
Pushed at: over 1 year ago
Last synced at: over 1 year ago
Topics: biomedical-image-processing, deep-learning, digitalpathology, explainable-ai, healthcare, interpretable-deep-learning, malaria-detection, neural-network, snapshot-ensemble, whole-slide-image, wholeslide-imaging