Mapping hazelnut orchards can facilitate land planning and utilization policies,supporting the development of cooperative precision farming *** present work faces the detection of hazelnut crops using optical and rada...
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Mapping hazelnut orchards can facilitate land planning and utilization policies,supporting the development of cooperative precision farming *** present work faces the detection of hazelnut crops using optical and radar remote sensing data.A comparative study of Machine Learning techniques is *** system proposed utilizes multi-temporal data from the Sentinel-1 and Sentinel-2 datasets extracted over several years and processed with cloud *** provide a dataset of 62,982 labeled samples,with 16,561 samples belonging to the‘hazelnut’class and 46,421 samples belonging to the‘other’class,collected in 8 heterogeneous geograph-ical areas of the Viterbo *** different comparative tests are conducted:firstly,we use a Nested 5-Fold Cross-Validation methodology to train,optimize,and compare different Machine Learning algorithms on a single *** a second experiment,the algorithms were trained on one area and tested on the remaining seven geo-graphical *** developed study demonstrates how AI analysis applied to Sentinel-1 and Sentinel-2 data is a valid technology for hazelnut *** the results,it emerges that Random Forest is the classifier with the highest generalizability,achieving the best performance in the second test with an accuracy of 96%and an F1 score of 91%for the‘hazelnut’class.
The pervasiveness of artificial intelligence in our daily lives has raised the need to understand and trust the outputs of the learning models, especially when involved in decision processes. As a result, eXplainable ...
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In the era of digital technologies permeating numerous aspects of society, the development of intelligent artificial agents endowed with autonomy, social capabilities, reactivity, and proactivity has become a pivotal ...
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The increasingly inordinate production of productivity-enhancing technologies in today's society has led to an increased risk of damaging the environment from which key resources are derived, if conducted in an un...
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Advancements in generative artificial intelligence (AI) are setting the stage for transformative changes in medical imaging, particularly through the development of the Virtual Scanner. This innovative approach levera...
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In our fast-paced world, timely access to information is essential. This urgency is highlighted in stress detection, where swift actions can mitigate harmful psycho-physiological effects. We introduce an early stress ...
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This paper explores the potential of leveraging electronic health records (EHRs) for personalized health research through the application of artificial intelligence (AI) techniques, specifically Named Entity Recogniti...
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Nowadays, more and more people are working remotely or in professions that require them to sit for long periods of time. Unfortunately, spending too much time in a seated position can lead to a range of physical and m...
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Handling missing values in tabular datasets presents a significant challenge in training and testing artificial intelligence models, an issue usually addressed using imputation techniques. Here we introduce "Not ...
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This abstract discusses the development of a metaverse for intelligent healthcare, which involves creating a virtual environment where healthcare professionals, patients, and researchers can interact and collaborate u...
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