Foundation models for generalist medical artificial intelligence
The exceptionally rapid development of highly flexible, reusable artificial intelligence (AI)
models is likely to usher in newfound capabilities in medicine. We propose a new paradigm …
models is likely to usher in newfound capabilities in medicine. We propose a new paradigm …
Deep learning-based semantic segmentation of urban features in satellite images: A review and meta-analysis
Availability of very high-resolution remote sensing images and advancement of deep
learning methods have shifted the paradigm of image classification from pixel-based and …
learning methods have shifted the paradigm of image classification from pixel-based and …
Sustainable crop protection via robotics and artificial intelligence solutions
Agriculture 5.0 refers to the next phase of agricultural development, building upon the
previous digital revolution in the agrarian sector and aiming to transform the agricultural …
previous digital revolution in the agrarian sector and aiming to transform the agricultural …
Sentinel SAR-optical fusion for crop type map** using deep learning and Google Earth Engine
J Adrian, V Sagan, M Maimaitijiang - ISPRS Journal of Photogrammetry and …, 2021 - Elsevier
Accurate crop type map** provides numerous benefits for a deeper understanding of food
systems and yield prediction. Ever-increasing big data, easy access to high-resolution …
systems and yield prediction. Ever-increasing big data, easy access to high-resolution …
Object detection and image segmentation with deep learning on Earth observation data: A review—Part II: Applications
In Earth observation (EO), large-scale land-surface dynamics are traditionally analyzed by
investigating aggregated classes. The increase in data with a very high spatial resolution …
investigating aggregated classes. The increase in data with a very high spatial resolution …
Remote-sensing data and deep-learning techniques in crop map** and yield prediction: A systematic review
Reliable and timely crop-yield prediction and crop map** are crucial for food security and
decision making in the food industry and in agro-environmental management. The global …
decision making in the food industry and in agro-environmental management. The global …
Smart farming becomes even smarter with deep learning—a bibliographical analysis
Z Ünal - IEEE access, 2020 - ieeexplore.ieee.org
Smart farming is a new concept that makes agriculture more efficient and effective by using
advanced information technologies. The latest advancements in connectivity, automation …
advanced information technologies. The latest advancements in connectivity, automation …
Deep learning architectures for semantic segmentation and automatic estimation of severity of foliar symptoms caused by diseases or pests
Colour-thresholding digital imaging methods are generally accurate for measuring the
percentage of foliar area affected by disease or pests (severity), but they perform poorly …
percentage of foliar area affected by disease or pests (severity), but they perform poorly …
UAV-based slope failure detection using deep-learning convolutional neural networks
Slope failures occur when parts of a slope collapse abruptly under the influence of gravity,
often triggered by a rainfall event or earthquake. The resulting slope failures often cause …
often triggered by a rainfall event or earthquake. The resulting slope failures often cause …
Vegetation detection using deep learning and conventional methods
Land cover classification with the focus on chlorophyll-rich vegetation detection plays an
important role in urban growth monitoring and planning, autonomous navigation, drone …
important role in urban growth monitoring and planning, autonomous navigation, drone …