Challenges for the repeatability of deep learning models
Deep learning training typically starts with a random sampling initialization approach to set
the weights of trainable layers. Therefore, different and/or uncontrolled weight initialization …
the weights of trainable layers. Therefore, different and/or uncontrolled weight initialization …
Delta radiomics improves pulmonary nodule malignancy prediction in lung cancer screening
Low-dose computed tomography (LDCT) plays a critical role in the early detection of lung
cancer. Despite the life-saving benefit of early detection by LDCT, there are many limitations of …
cancer. Despite the life-saving benefit of early detection by LDCT, there are many limitations of …
Hydrothermal synthesis of ZnO@ MoTe2 nanocomposite as excellent electrocatalyst for hydrogen evolution reaction (HER)
The comprehension of novel fundamental inquiries about the design of electrocatalysts is of
paramount importance in enhancing the availability of renewable energy resources and …
paramount importance in enhancing the availability of renewable energy resources and …
Hydrothermal development of bimetallic sulfide nanostructures as an electrode material for supercapacitor application
Supercapacitors (SCs) possess specialized capabilities and exhibit rapid charging and
discharging rates, making them highly suitable for integration into portable energy storage and …
discharging rates, making them highly suitable for integration into portable energy storage and …
A comprehensive review of deep learning-based methods for COVID-19 detection using chest X-ray images
SS Alahmari, B Altazi, J Hwang, S Hawkins… - Ieee …, 2022 - ieeexplore.ieee.org
The novel coronavirus disease 2019 (COVID-19) added tremendous pressure on healthcare
services worldwide. COVID-19 early detection is of the utmost importance to control the …
services worldwide. COVID-19 early detection is of the utmost importance to control the …
Automated cell counts on tissue sections by deep learning and unbiased stereology
In recent decades stereology-based studies have played a significant role in understanding
brain aging and developing novel drug discovery strategies for treatment of neurological …
brain aging and developing novel drug discovery strategies for treatment of neurological …
Food state recognition using deep learning
SS Alahmari, T Salem - IEEE Access, 2022 - ieeexplore.ieee.org
Automated food detection and recognition methods have been studied to enhance end-user
life. However, most existing research focused on food ingredient type recognition, with little …
life. However, most existing research focused on food ingredient type recognition, with little …
Facile synthesis of SnSe–MnTe nanocomposite as a promising electrode for supercapacitor applications
The biggest problems encountered by the world right now are energy demand and environmental
damage because of the exploitation of fossil fuels. Producing and storing energy in an …
damage because of the exploitation of fossil fuels. Producing and storing energy in an …
Hydrothermal synthesis of the NiS@ g-C3N4 nanohybrid electrode material for supercapacitor applications
Recent research on sustainable, efficient energy supply and storage systems has increased
due to worries about energy constraints, pollution, and fossil fuel depletion. However, …
due to worries about energy constraints, pollution, and fossil fuel depletion. However, …
Visible-light-driven 2D carbonaceous-based SnSe nanohybrid soft materials: A photocatalyst for efficient photo reduction of malachite green dye
Preserving a healthy environment of air, land, and water requires the treatment of dangerous
organic effluents. Efficiently degrading hazardous pollutants requires low-cost, high-…
organic effluents. Efficiently degrading hazardous pollutants requires low-cost, high-…
