Deep learning: a comprehensive overview on techniques, taxonomy, applications and research directions

IH Sarker - SN computer science, 2021 - Springer
Deep learning (DL), a branch of machine learning (ML) and artificial intelligence (AI) is
nowadays considered as a core technology of today's Fourth Industrial Revolution (4IR or …

[HTML][HTML] Adoption of artificial intelligence in smart cities: A comprehensive review

H Herath, M Mittal - International Journal of Information Management Data …, 2022 - Elsevier
Recently, the population density in cities has increased at a higher pace. According to the
United Nations Population Fund, cities accommodated 3.3 billion people (54%) of the global …

Rodin: A generative model for sculpting 3d digital avatars using diffusion

T Wang, B Zhang, T Zhang, S Gu… - Proceedings of the …, 2023 - openaccess.thecvf.com
This paper presents a 3D diffusion model that automatically generates 3D digital avatars
represented as neural radiance fields (NeRFs). A significant challenge for 3D diffusion is …

Deep learning in drug discovery: an integrative review and future challenges

H Askr, E Elgeldawi, H Aboul Ella… - Artificial Intelligence …, 2023 - Springer
Recently, using artificial intelligence (AI) in drug discovery has received much attention
since it significantly shortens the time and cost of develo** new drugs. Deep learning (DL) …

[HTML][HTML] Applications of text mining in services management: A systematic literature review

S Kumar, AK Kar, PV Ilavarasan - International Journal of Information …, 2021 - Elsevier
The importance of text mining is increasing in services management as the access to big
data is increasing across digital platforms enabling such services. This study adopts a …

The power of generative ai: A review of requirements, models, input–output formats, evaluation metrics, and challenges

A Bandi, PVSR Adapa, YEVPK Kuchi - Future Internet, 2023 - mdpi.com
Generative artificial intelligence (AI) has emerged as a powerful technology with numerous
applications in various domains. There is a need to identify the requirements and evaluation …

[HTML][HTML] A systematic review of data fusion techniques for optimized structural health monitoring

S Hassani, U Dackermann, M Mousavi, J Li - Information Fusion, 2024 - Elsevier
Advancements in structural health monitoring (SHM) techniques have spiked in the past few
decades due to the rapid evolution of novel sensing and data transfer technologies. This …

Generative adversarial networks for face generation: A survey

A Kammoun, R Slama, H Tabia, T Ouni… - ACM Computing …, 2022 - dl.acm.org
Recently, generative adversarial networks (GANs) have progressed enormously, which
makes them able to learn complex data distributions in particular faces. More and more …

On the analyses of medical images using traditional machine learning techniques and convolutional neural networks

S Iqbal, A N. Qureshi, J Li, T Mahmood - Archives of Computational …, 2023 - Springer
Convolutional neural network (CNN) has shown dissuasive accomplishment on different
areas especially Object Detection, Segmentation, Reconstruction (2D and 3D), Information …

The state of the art in deep learning applications, challenges, and future prospects: A comprehensive review of flood forecasting and management

V Kumar, HM Azamathulla, KV Sharma, DJ Mehta… - Sustainability, 2023 - mdpi.com
Floods are a devastating natural calamity that may seriously harm both infrastructure and
people. Accurate flood forecasts and control are essential to lessen these effects and …