Deep architectures for image compression: a critical review
Deep learning architectures are now pervasive and filled almost all applications under
image processing, computer vision, and biometrics. The attractive property of feature …
image processing, computer vision, and biometrics. The attractive property of feature …
Artificial intelligence techniques for predictive modeling of vector-borne diseases and its pathogens: a systematic review
Vector-borne diseases (VBDs) have a significant impact on human and animal health. VBD
has been emerging or re-emerging in a variety of geographic regions, raising alarming new …
has been emerging or re-emerging in a variety of geographic regions, raising alarming new …
Leveraging deep learning techniques for malaria parasite detection using mobile application
Malaria is a contagious disease that affects millions of lives every year. Traditional diagnosis
of malaria in laboratory requires an experienced person and careful inspection to …
of malaria in laboratory requires an experienced person and careful inspection to …
A novel stacked CNN for malarial parasite detection in thin blood smear images
Malaria refers to a contagious mosquito-borne disease caused by parasite genus
plasmodium transmitted by mosquito female Anopheles. As infected mosquito bites a …
plasmodium transmitted by mosquito female Anopheles. As infected mosquito bites a …
Unsupervised deep learning cad scheme for the detection of malaria in blood smear microscopic images
Recent advances in deep learning, coupled with the onslaught of unlabelled medical data
have drawn ever-increasing research interests by discovering multiple levels of distributed …
have drawn ever-increasing research interests by discovering multiple levels of distributed …
Improving malaria parasite detection from red blood cell using deep convolutional neural networks
Malaria is a female anopheles mosquito-bite inflicted life-threatening disease which is
considered endemic in many parts of the world. This article focuses on improving malaria …
considered endemic in many parts of the world. This article focuses on improving malaria …
[PDF][PDF] Imperative dynamic routing between capsules network for malaria classification
Malaria is a severe epidemic disease caused by Plasmodium falciparum. The parasite
causes critical illness if persisted for longer durations and delay in precise treatment can …
causes critical illness if persisted for longer durations and delay in precise treatment can …
Classification accuracies of malaria infected cells using deep convolutional neural networks based on decompressed images
In many biomedical applications, images are stored and transmitted in the form of
compressed images. However, typical pattern classifiers are trained using original images …
compressed images. However, typical pattern classifiers are trained using original images …
A novel implicit neural representation for volume data
The storage of medical images is one of the challenges in the medical imaging field. There
are variable works that use implicit neural representation (INR) to compress volumetric …
are variable works that use implicit neural representation (INR) to compress volumetric …
Automatic detection of malaria parasites using unsupervised techniques
The focus of this paper is towards comparing the computational paradigms of two
unsupervised data reduction techniques, namely Auto encoder and Self-organizing Maps …
unsupervised data reduction techniques, namely Auto encoder and Self-organizing Maps …