Methods for image denoising using convolutional neural network: a review
AE Ilesanmi, TO Ilesanmi - Complex & Intelligent Systems, 2021 - Springer
Image denoising faces significant challenges, arising from the sources of noise. Specifically,
Gaussian, impulse, salt, pepper, and speckle noise are complicated sources of noise in …
Gaussian, impulse, salt, pepper, and speckle noise are complicated sources of noise in …
State-of-the-art review on energy and load forecasting in microgrids using artificial neural networks, machine learning, and deep learning techniques
Forecasting renewable energy efficiency significantly impacts system management and
operation because more precise forecasts mean reduced risk and improved stability and …
operation because more precise forecasts mean reduced risk and improved stability and …
Neurbf: A neural fields representation with adaptive radial basis functions
We present a novel type of neural fields that uses general radial bases for signal
representation. State-of-the-art neural fields typically rely on grid-based representations for …
representation. State-of-the-art neural fields typically rely on grid-based representations for …
[BOOK][B] Statistical pattern recognition
AR Webb - 2003 - books.google.com
Statistical pattern recognition is a very active area of study andresearch, which has seen
many advances in recent years. New andemerging applications-such as data mining, web …
many advances in recent years. New andemerging applications-such as data mining, web …
Machine learning methods for turbulence modeling in subsonic flows around airfoils
In recent years, the data-driven turbulence model has attracted widespread concern in fluid
mechanics. The existing approaches modify or supplement the original turbulence model by …
mechanics. The existing approaches modify or supplement the original turbulence model by …
Exploring the power of machine learning to predict carbon dioxide trap** efficiency in saline aquifers for carbon geological storage project
Carbon geological sequestration (CGS) in saline aquifers is an effective carbon utilization
approach to decrease the effect of greenhouse gases on the atmosphere. However, the …
approach to decrease the effect of greenhouse gases on the atmosphere. However, the …
Leukemia diagnosis in blood slides using transfer learning in CNNs and SVM for classification
Leukemia is a pathology that affects young people and adults, causing premature death and
several other symptoms. Computer-aided systems can be used to reduce the possibility of …
several other symptoms. Computer-aided systems can be used to reduce the possibility of …
A comparative study among machine learning and numerical models for simulating groundwater dynamics in the Heihe River Basin, northwestern China
C Chen, W He, H Zhou, Y Xue, M Zhu - Scientific reports, 2020 - nature.com
Groundwater is unique resource for agriculture, domestic use, industry and environment in
the Heihe River Basin, northwestern China. Numerical models are effective approaches to …
the Heihe River Basin, northwestern China. Numerical models are effective approaches to …
High-energy nuclear physics meets machine learning
Although seemingly disparate, high-energy nuclear physics (HENP) and machine learning
(ML) have begun to merge in the last few years, yielding interesting results. It is worthy to …
(ML) have begun to merge in the last few years, yielding interesting results. It is worthy to …
Application of robust intelligent schemes for accurate modelling interfacial tension of CO2 brine systems: Implications for structural CO2 trap**
Given the current global climate change, renewable energy sources, carbon capture,
utilization, and storage (CCUS) are being considered as a potential solutions to this critical …
utilization, and storage (CCUS) are being considered as a potential solutions to this critical …