Concept

Precision agriculture

Related publications (35)

At what spatial scale does natural selection operate? Using multiscale frameworks to calibrate the effects of environmental factors across landscape continuums

Patterns in nature arise from processes interacting across a continuum of spatial scales, where new relationships emerge at each level of investigation. These patterns are nested features encompassing fine-scale local patterns, such as topography and geolo ...

EPFL2024

Using machine learning to generate an open-access cropland map from satellite images time series in the Indian Himalayan region

Danya Li

Crop maps are crucial for agricultural monitoring and food management and can additionally support domain-specific applications, such as setting cold supply chain infrastructure in developing countries. Machine learning (ML) models, combined with freely-av ...

Amsterdam2023

High-precision optical magnetometry using Nitrogen Vacancies in CVD diamond

Hossein Babashah

Sensing weak magnetic fields is a topic of great importance in basic science and technology due to its wide range of applications. In this context, solid-state and nanoscale quantum sensors are poised to revolutionize the sensing platforms due to their ult ...

EPFL2023

Abnormal temperature dependent elastic properties of fused silica irradiated by ultrafast lasers

Yves Bellouard, Pieter Vlugter

Materials with thermal-invariant elastic properties are of interest for resonant device frequency and dimensional stability of precision devices. Here, we demonstrate that the temperature coefficient of elasticity (TCE) of amorphous silica can be locally r ...

2022

Limited role of soil texture in mediating natural vegetation response to rainfall anomalies

Sara Bonetti, Dani Or

Evidence suggests that the response of rainfed crops to dry or wet years is modulated by soil texture. This is a central tenet for certain agronomic operations in water-limited regions that rely on spatial distribution of soil texture for guiding precision ...

2022

Time Dependent Image Generation of Plants from Incomplete Sequences with CNN-Transformer

Marc Conrad Russwurm

Data imputation of incomplete image sequences is an essential prerequisite for analyzing and monitoring all development stages of plants in precision agriculture. For this purpose, we propose a conditional Wasserstein generative adversarial network TransGr ...

SPRINGER INTERNATIONAL PUBLISHING AG2022

Monitoring weekly progress of front crawl swimmers using IMU-based performance evaluation goal metrics

Kamiar Aminian, Farzin Dadashi, Fabien Massé, Mahdi Hamidi Rad, Vincent Gremeaux

Technical evaluation of swimming performance is an essential factor in preparing elite swimmers for their competitions. Inertial measurement units (IMUs) have attracted much attention recently because they can provide coaches with a detailed analysis of sw ...

FRONTIERS MEDIA SA2022

Une approche computationnelle du cadastre napoléonien de Venise

Frédéric Kaplan, Isabella Di Lenardo, Raphaël Barman, Federica Pardini

At the beginning of the 19th century, the Napoleonic administration introduced a new standardised description system to give an objective account of the form and functions of the city of Venice. The cadastre, deployed on a European scale, was offering for ...

2021

Multiscale Very High Resolution Topographic Models in Alpine Ecology: Pros and Cons of Airborne LiDAR and Drone-Based Stereo-Photogrammetry Technologies

Stéphane Joost, Estelle Rochat, Kevin Leempoel, Annie Sandrine Guillaume, Aude Rogivue

The vulnerability of alpine environments to climate change presses an urgent need to accurately model and understand these ecosystems. Popularity in the use of digital elevation models (DEMs) to derive proxy environmental variables has increased over the p ...

2021

Self-Supervised Pretraining and Controlled Augmentation Improve Rare Wildlife Recognition in UAV Images

Devis Tuia, Benjamin Alexander Kellenberger, Xiaochen Zheng, Rui Gong

Automated animal censuses with aerial imagery are a vital ingredient towards wildlife conservation. Recent models are generally based on deep learning and thus require vast amounts of training data. Due to their scarcity and minuscule size, annotating anim ...

IEEE2021

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