An innovative approach to parasite classification in biomedical imaging using neural networks
O Aytac, FF Senol, I Tuncer, S Dogan… - Engineering Applications of …, 2025 - Elsevier
Background and objective In light of the increasing demand for precise and effective
parasite detection in biomedical imaging, current models frequently depend on widely used …
parasite detection in biomedical imaging, current models frequently depend on widely used …
[PDF][PDF] Malaria parasite detection using a quantum-convolutional network
Malaria is a severe illness triggered by parasites that spreads via mosquito bites. In
underdeveloped nations, malaria is one of the top causes of mortality, and it is mainly …
underdeveloped nations, malaria is one of the top causes of mortality, and it is mainly …
[PDF][PDF] Computer-Assisted Disease Diagnosis Application for Malaria Early Diagnosis Based on Modified CNN Algorithm
Since its emergence in the early 20th century, Malaria has been confirmed as a deadly
disease that has spread throughout the world with very high mortality and morbidity. This is …
disease that has spread throughout the world with very high mortality and morbidity. This is …
Distracted driver behavior recognition using modified capsule networks
JA Kadar, MAK Dewi, E Suryawati… - … , Electrical Power, and …, 2023 - mev.brin.go.id
Human activity recognition (HAR) is an increasingly active study field within the computer
vision community. In HAR, driver behavior can be detected to ensure safe travel. Detect …
vision community. In HAR, driver behavior can be detected to ensure safe travel. Detect …
A Proposed Mala-Net CNN Algorithm for Malaria Early Detection Based on Thick Blood Smear
Malaria has spread worldwide since the early 20th century and causes nearly half a million
deaths each year. Malaria is actually not a dangerous disease and can be easily cured if the …
deaths each year. Malaria is actually not a dangerous disease and can be easily cured if the …
A Simple Attention Block Embedded in Standard CNN for Image Classification
The revival of convolution neural networks (CNN) has enhanced feature extraction by
reducing the manual hand-engineered methods. These CNN proved their versatility in …
reducing the manual hand-engineered methods. These CNN proved their versatility in …
Robustness of image classification on imbalanced datasets using capsules networks
S Onana, D Tchuani, C Tinku, L Fippo… - Conference on Research …, 2023 - Springer
The purpose of this study is to assess the robustness of the capsule networks for the image
classification tasks on imbalanced dataset. In fact, in many real-life situations, the distribution …
classification tasks on imbalanced dataset. In fact, in many real-life situations, the distribution …