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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Deformable retinal image registration is crucial in clinical diagnosis and longitudinal studies of retinal *** exist-ing deep deformable retinal image registration methods focus on fully convolutional network(FCN)arch...
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Deformable retinal image registration is crucial in clinical diagnosis and longitudinal studies of retinal *** exist-ing deep deformable retinal image registration methods focus on fully convolutional network(FCN)architecture design,which fails to model long-range dependencies among pixels-a significant factor in deformable retinal image *** based on the self-attention mechanism,can capture global context dependencies,complementing local ***,multi-scale spatial fea-ture fusion and pixel-wise position selection are also crucial for the deformable retinal image registration,are often ignored by both FCNs and *** fully leverage the merits of FCNs,multi-scale spatial attention and transformers,we propose a hierarchical hybrid architecture,reparameterized multi-scale transformer(RMFormer),for deformable retinal image *** RMFormer,we specifically develop a reparameterized multi-scale spatial attention to adaptively fuse multi-scale spatial features,with the assistance of the reparameterizing technique,thereby highlighting informative pixel-wise positions in a lightweight *** experimental results on two publicly available datasets demonstrate the superiority of our RMFormer over state-of-the-art methods and show that it is data-efficient in a limited medical image ***,we are the first to provide a visualization analysis to explain how our proposed method affects the deformable retinal image registration *** source code of our work is available at .
The unfolding climate crisis has resulted in a rising interest for increasing sustainability awareness and achieving energy savings worldwide. Several interventions within educational environments have been aimed at m...
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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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