1,720,965 research outputs found
Machine learning and Unmanned Aerial Systems for crop monitoring and agrochemicals distribution optimization in orchard and horticultural systems
Full text linkThe work aims at discovering the potential and the efficiency of Unmanned Aerial Systems (UAS) and Machine Learning (ML) in agriculture scenario, focusing on crop management and agrochemicals distribution optimization in orchard and horticultural cropping systems. The dissertation includes a general introduction, three experimental chapters and a general conclusion. Chapter 2 illustrates an operational approach to estimate individual and aggregate vineyards’ canopy volume using the manual Tree-Row-Volume (TRV) and the remotely sensed Canopy Height Model (CHM) techniques, processed with MATLAB scripts, and validated through ArcGIS tools. The results confirm how the extensive use of TRV is recommended when supported by remote sensing, to better qualify errors and heterogeneities in field estimates. Chapter 3 presents the development of a grape bunch detector based on a deep convolutional neural network trained to work directly on the field in an uncontrolled environment. The presented results are promising since most of the bunches were correctly detected with a 91% mean average precision, not only on the GrapeCS-ML database used to train the system, but also on an internal dataset, confirming the portability to different scenarios. Chapter 4 reports artichoke plant deep learning-based detection and georeferencing as the first step for an on-the-fly UAS spraying system and uses the gathered information to crop development monitoring in a multi-temporal approach. The Feature Pyramid Network, trained and compared with the YOLOv5 network, showed a high detection level with an average F1 score of around 90%, and satisfactory off-line performances on the Nvidia Jetson Nano board. The multi-temporal approach influenced detection performances, with an inverse response of precision and recall metrics. The growing index trend showed a distinct value in October, peaking at the beginning of December as expectedThe work aims at discovering the potential and the efficiency of Unmanned Aerial Systems (UAS) and Machine Learning (ML) in agriculture scenario, focusing on crop management and agrochemicals distribution optimization in orchard and horticultural cropping systems. The dissertation includes a general introduction, three experimental chapters and a general conclusion. Chapter 2 illustrates an operational approach to estimate individual and aggregate vineyards’ canopy volume using the manual Tree-Row-Volume (TRV) and the remotely sensed Canopy Height Model (CHM) techniques, processed with MATLAB scripts, and validated through ArcGIS tools. The results confirm how the extensive use of TRV is recommended when supported by remote sensing, to better qualify errors and heterogeneities in field estimates. Chapter 3 presents the development of a grape bunch detector based on a deep convolutional neural network trained to work directly on the field in an uncontrolled environment. The presented results are promising since most of the bunches were correctly detected with a 91% mean average precision, not only on the GrapeCS-ML database used to train the system, but also on an internal dataset, confirming the portability to different scenarios. Chapter 4 reports artichoke plant deep learning-based detection and georeferencing as the first step for an on-the-fly UAS spraying system and uses the gathered information to crop development monitoring in a multi-temporal approach. The Feature Pyramid Network, trained and compared with the YOLOv5 network, showed a high detection level with an average F1 score of around 90%, and satisfactory off-line performances on the Nvidia Jetson Nano board. The multi-temporal approach influenced detection performances, with an inverse response of precision and recall metrics. The growing index trend showed a distinct value in October, peaking at the beginning of December as expected
In-Field Automatic Detection of Grape Bunches under a Totally Uncontrolled Environment
Full text linkAn early estimation of the exact number of fruits, flowers, and trees helps farmers to make better decisions on cultivation practices, plant disease prevention, and the size of harvest labor force. The current practice of yield estimation based on manual counting of fruits or flowers by workers is a time consuming and expensive process and it is not feasible for large fields. Automatic yield estimation based on robotic agriculture provides a viable solution in this regard. In a typical image classification process, the task is not only to specify the presence or absence of a given object on a specific location, while counting how many objects are present in the scene. The success of these tasks largely depends on the availability of a large amount of training samples. This paper presents a detector of bunches of one fruit, grape, based on a deep convolutional neural network trained to detect vine bunches directly on the field. Experimental results show a 91% mean Average Precision
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Unmanned aerial system plant protection products spraying performance evaluation on a vineyard
Full text linkIn the context of increasing global food demand and the urgent need for production processes optimization, plant protection products play a key role in safeguarding crops from insects, pests, and fungi, responsible of plant diseases proliferation and yield losses. Despite the inaccurate distribution of conventional aerial spraying performed by airplanes and helicopters, Unmanned Aerial Spraying Systems (UASSs) offer low health risks and operational cost solutions, preserving crops and soil from physical damage. This study explores the impact of UASS flight height (2 m and 2.5 m above ground level), speed (1 m s−1 and 1.5 m s−1), and position (over the canopy and the inter-row) on vineyard aerial spraying efficiency by analysing Water Sensitive Papers droplet coverage, density, and Number Median Diameter using a MATLAB script. Flight position factor, more than others, influenced the application results. The specific configuration of 2 m altitude, 1.5 m s−1 cruising speed, and inter-row positioning yielded the best results in terms of canopy coverage, minimizing off-target and ground dispersion, and represented the best setting to facilitate droplets penetration, reaching the lowest parts generally more affected from disease. Further research is needed to assess UASS aerial PPP distribution effectiveness and environmental impact in agriculture, crucial for technology implementation, especially in countries where aerial treatments are not yet permitted
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
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