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Deep Learning: A Critical Appraisal

Gary Marcus • arXiv (Cornell University) (2018)

Although deep learning has historical roots going back decades, neither the term "deep learning" nor the approach was popular just over five years ago, when the field was reignited by papers such as Krizhevsky, Sutskever and Hinton's now cl...

OPENALEX Open Access DOI: https://doi.org/10.48550/arxiv.1801.00631

Machine learning and data-driven prediction of pore pressure from geophysical logs: A case study for the Mangahewa gas field, New Zealand

Ahmed E. Radwan, David A. Wood, Ahmed A. Radwan • Journal of Rock Mechanics and Geotechnical Engineering (2022)

Pore pressure is an essential parameter for establishing reservoir conditions, geological interpretation and drilling programs. Pore pressure prediction depends on information from various geophysical logs, seismic, and direct down-hole pre...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.jrmge.2022.01.012

Machine Learning and Deep Learning

Ayushi Chahal, Preeti Gulia • International Journal of Innovative Technology and Exploring Engineering (2019)

Now-a-days artificial intelligence has become an asset for engineering and experimental studies, just like statistics and calculus. Data science is a growing field for researchers and artificial intelligence, machine learning and deep learn...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.35940/ijitee.l3550.1081219

Satellite Retrieval of Air Pollution Changes in Central and Eastern China during COVID-19 Lockdown Based on a Machine Learning Model

Zigeng Song, Yan Bai, Difeng Wang, Teng Li et al. • Remote Sensing (2021)

With the implementation of the 2018–2020 Clean Air Action Plan (CAAP) the and impact from COVID-19 lockdowns in 2020, air pollution emissions in central and eastern China have decreased markedly. Here, by combining satellite remote sensing,...

DOAJ Open Access (DOAJ) DOI: 10.3390/rs13132525

Simulation of Flow-Induced Vibration and Dynamic Performance of Circular-Arc Helical Gear Pump under Background of Machine Learning

Xiaoling Wei, Yongbao Feng, Xiaoxia Han, Zhenxin He • International Transactions on Electrical Energy Systems (2022)

At present, with the continuous development and great improvement of mechanical manufacturing, processing, and assembly technology, mechanical flow-induced vibration (FIV) with a relatively concentrated frequency domain can be controlled by...

DOAJ Open Access (DOAJ) DOI: 10.1155/2022/9513357

Development of Machine Learning Models to Predict Compressed Sward Height in Walloon Pastures Based on Sentinel-1, Sentinel-2 and Meteorological Data Using Multiple Data Transformations

Charles Nickmilder, Anthony Tedde, Isabelle Dufrasne, Françoise Lessire et al. • Remote Sensing (2021)

Accurate information about the available standing biomass on pastures is critical for the adequate management of grazing and its promotion to farmers. In this paper, machine learning models are developed to predict available biomass express...

DOAJ Open Access (DOAJ) DOI: 10.3390/rs13030408

Synergistic multi-altimeter for estimating water level in the coastal zone of Beibu Gulf using SEL, ALES + and BFAST algorithms

Jiaoling Qin, Jiaoling Qin, Sunzhe Li, Sunzhe Li et al. • Frontiers in Marine Science (2023)

Accurately monitoring and predicting the large-scale dynamic changes of water levels in coastal zones is essential for its protection, restoration and sustainable development. However, there has been a challenge for achieving this goal usin...

DOAJ Open Access (DOAJ) DOI: 10.3389/fmars.2022.1113387

Artificial Intelligence as a Service

Sebastian Lins, Konstantin D. Pandl, Heiner Teigeler, Scott Thiebes et al. • Business & Information Systems Engineering (2021)

Artificial intelligence Á Cloud computing Á Machine learning as a service 1 The Roots of Artificial Intelligence as a Service 1.1 The Emergence of Artificial Intelligence Services Artificial Intelligence (AI) is undoubtedly one of the most ...

OPENALEX cc-by DOI: https://doi.org/10.1007/s12599-021-00708-w

Artificial intelligence

Akshar Joshi, Gautam Mishra • International Conference & Workshop on Emerging Trends in Technology (2010)

In this paper, we will explore the magic of giving the power of thinking to man--made machines, i.e. Artificial Intelligence which is involved in many fields of electronics and computers. In 1956, John McCarthy who coined the term of Artifi...

OPENALEX DOI: https://doi.org/10.1145/1741906.1742236

SSMSFuse: A Spectral and Spatial Multiscale Coupling Fusion Model for Hyperspectral and Multispectral Image

Siyuan Liu, Yingchao Fan, Qi Hu, Bing Li et al. • IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2025)

Hyperspectral image (HSI) has more spectral information than conventional images, which helps to distinguish targets in a complex scene more accurately. However, HSI typically has a low spatial resolution, which limits their application sce...

DOAJ Open Access (DOAJ) DOI: 10.1109/JSTARS.2025.3586076

Prediction of Seven Artificial Intelligence-Based Intraocular Lens Power Calculation Formulas in Medium-Long Caucasian Eyes

Wiktor Stopyra, Oleksiy Voytsekhivskyy, Andrzej Grzybowski • Life (2025)

Purpose: To compare the accuracy of seven artificial intelligence (AI)-based intraocular lens (IOL) power calculation formulas in medium-long Caucasian eyes regarding the root-mean-square absolute error (RMSAE), the median absolute error (M...

DOAJ Open Access (DOAJ) DOI: 10.3390/life15010045