[HTML][HTML] Deep learning in optical metrology: a review
With the advances in scientific foundations and technological implementations, optical
metrology has become versatile problem-solving backbones in manufacturing, fundamental …
metrology has become versatile problem-solving backbones in manufacturing, fundamental …
Understanding of machine learning with deep learning: architectures, workflow, applications and future directions
MM Taye - Computers, 2023 - mdpi.com
In recent years, deep learning (DL) has been the most popular computational approach in
the field of machine learning (ML), achieving exceptional results on a variety of complex …
the field of machine learning (ML), achieving exceptional results on a variety of complex …
Machine learning and deep learning
Today, intelligent systems that offer artificial intelligence capabilities often rely on machine
learning. Machine learning describes the capacity of systems to learn from problem-specific …
learning. Machine learning describes the capacity of systems to learn from problem-specific …
Deep neural networks and tabular data: A survey
Heterogeneous tabular data are the most commonly used form of data and are essential for
numerous critical and computationally demanding applications. On homogeneous datasets …
numerous critical and computationally demanding applications. On homogeneous datasets …
Machine learning: new ideas and tools in environmental science and engineering
The rapid increase in both the quantity and complexity of data that are being generated daily
in the field of environmental science and engineering (ESE) demands accompanied …
in the field of environmental science and engineering (ESE) demands accompanied …
Convit: Improving vision transformers with soft convolutional inductive biases
Convolutional architectures have proven extremely successful for vision tasks. Their hard
inductive biases enable sample-efficient learning, but come at the cost of a potentially lower …
inductive biases enable sample-efficient learning, but come at the cost of a potentially lower …
[HTML][HTML] Artificial intelligence in the construction industry: A review of present status, opportunities and future challenges
The growth of the construction industry is severely limited by the myriad complex challenges
it faces such as cost and time overruns, health and safety, productivity and labour shortages …
it faces such as cost and time overruns, health and safety, productivity and labour shortages …
Machine learning force fields
In recent years, the use of machine learning (ML) in computational chemistry has enabled
numerous advances previously out of reach due to the computational complexity of …
numerous advances previously out of reach due to the computational complexity of …
A comprehensive survey on sentiment analysis: Approaches, challenges and trends
Sentiment analysis (SA), also called Opinion Mining (OM) is the task of extracting and
analyzing people's opinions, sentiments, attitudes, perceptions, etc., toward different entities …
analyzing people's opinions, sentiments, attitudes, perceptions, etc., toward different entities …
Artificial intelligence to deep learning: machine intelligence approach for drug discovery
Drug designing and development is an important area of research for pharmaceutical
companies and chemical scientists. However, low efficacy, off-target delivery, time …
companies and chemical scientists. However, low efficacy, off-target delivery, time …