Deep learning: Applications, architectures, models, tools, and frameworks: A comprehensive survey

M Gheisari, F Ebrahimzadeh, M Rahimi… - CAAI Transactions …, 2023 - Wiley Online Library
Deep Learning (DL) is a subfield of machine learning that significantly impacts extracting
new knowledge. By using DL, the extraction of advanced data representations and …

Artificial intelligence-based hybrid deep learning models for image classification: The first narrative review

B Jena, S Saxena, GK Nayak, L Saba, N Sharma… - Computers in Biology …, 2021 - Elsevier
Background Artificial intelligence (AI) has served humanity in many applications since its
inception. Currently, it dominates the imaging field—in particular, image classification. The …

Deep transfer learning approaches for Monkeypox disease diagnosis

MM Ahsan, MR Uddin, MS Ali, MK Islam… - Expert Systems with …, 2023 - Elsevier
Monkeypox has become a significant global challenge as the number of cases increases
daily. Those infected with the disease often display various skin symptoms and can spread …

Machine learning and deep learning based computational approaches in automatic microorganisms image recognition: methodologies, challenges, and …

P Rani, S Kotwal, J Manhas, V Sharma… - … Methods in Engineering, 2022 - Springer
Microorganisms or microbes comprise majority of the diversity on earth and are extremely
important to human life. They are also integral to processes in the ecosystem. The process of …

Deep transfer with minority data augmentation for imbalanced breast cancer dataset

M Saini, S Susan - Applied Soft Computing, 2020 - Elsevier
Clinical diagnosis of breast cancer is a challenging problem in the biomedical domain. The
BreakHis breast cancer histopathological image dataset consists of two classes: Benign …

Leveraging deep learning techniques for malaria parasite detection using mobile application

M Masud, H Alhumyani, SS Alshamrani… - Wireless …, 2020 - Wiley Online Library
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 …

DFU_QUTNet: diabetic foot ulcer classification using novel deep convolutional neural network

L Alzubaidi, MA Fadhel, SR Oleiwi… - Multimedia Tools and …, 2020 - Springer
Abstract Diabetic Foot Ulcer (DFU) is the main complication of Diabetes, which, if not
properly treated, may lead to amputation. One of the approaches of DFU treatment depends …

Deep malaria parasite detection in thin blood smear microscopic images

A Maqsood, MS Farid, MH Khan, M Grzegorzek - Applied Sciences, 2021 - mdpi.com
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 …

Artificial intelligence techniques for predictive modeling of vector-borne diseases and its pathogens: a systematic review

I Kaur, AK Sandhu, Y Kumar - Archives of Computational Methods in …, 2022 - Springer
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 …

[HTML][HTML] A novel transfer learning-based model for diagnosing malaria from parasitized and uninfected red blood cell images

AM Qadri, A Raza, F Eid, L Abualigah - Decision Analytics Journal, 2023 - Elsevier
Malaria represents a potentially fatal communicable illness triggered by the Plasmodium
parasite. This disease is transmitted to humans through the bites of Anopheles mosquitoes …