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Algorithms in low-code-no-code for research applications: A practical review
F Sufi - Algorithms, 2023 - mdpi.com
Algorithms have evolved from machine code to low-code-no-code (LCNC) in the past 20
years. Observing the growth of LCNC-based algorithm development, the CEO of GitHub …
years. Observing the growth of LCNC-based algorithm development, the CEO of GitHub …
AI-enabled strategies for climate change adaptation: protecting communities, infrastructure, and businesses from the impacts of climate change
Climate change is one of the most pressing global challenges we face today. The impacts of
rising temperatures, sea levels, and extreme weather events are already being felt around …
rising temperatures, sea levels, and extreme weather events are already being felt around …
A novel method using explainable artificial intelligence (XAI)-based Shapley Additive Explanations for spatial landslide prediction using Time-Series SAR dataset
As artificial intelligence (AI) techniques are becoming more popular in landslide modeling, it
is important to understand how decisions are made. Fairness, and transparency becomes …
is important to understand how decisions are made. Fairness, and transparency becomes …
Landslide susceptibility map** using CNN-1D and 2D deep learning algorithms: comparison of their performance at Asir Region, KSA
To be proactive in mountain hazard mitigation, landslide disaster assessments are
becoming increasingly urgent. In this study, three modeling techniques, namely, support …
becoming increasingly urgent. In this study, three modeling techniques, namely, support …
CAS landslide dataset: a large-scale and multisensor dataset for deep learning-based landslide detection
In this work, we present the CAS Landslide Dataset, a large-scale and multisensor dataset
for deep learning-based landslide detection, developed by the Artificial Intelligence Group at …
for deep learning-based landslide detection, developed by the Artificial Intelligence Group at …
Handling data imbalance in machine learning based landslide susceptibility map**: a case study of Mandakini River Basin, North-Western Himalayas
Abstract Machine learning methods require a vast amount of data to train a model. The data
necessary for landslide susceptibility map** is a collection of landslide causative factors …
necessary for landslide susceptibility map** is a collection of landslide causative factors …
Exploring the uncertainty of landslide susceptibility assessment caused by the number of non–landslides
Q Liu, A Tang, D Huang - Catena, 2023 - Elsevier
Identifying the uncertainty caused by the number of non-landslides is necessary to obtain a
precise landslide susceptibility map. Hence, the objective of this study is to investigate the …
precise landslide susceptibility map. Hence, the objective of this study is to investigate the …