322,894 research outputs found
Digitized pear and peach trees with fruits
No full textThe dataset contains files with sets of point coordinates derived via manual digitization of entire trees and all fruits on them. Twenty Bartlett pear and twenty cling-peach trees were digitized. Digitization was restricted to rigid, thick branches (> 2.5 cm) that present obstacles to machinery interacting with trees; robotic harvesting simulation and design were the targeted applications. Each branch segment that had small enough curvature was considered linear and was approximated by a conical frustum. Hence, an entire tree is represented geometrically by a set of connected frustums. The tree geometries and topologies were successfully encoded, and position RMS accuracy was better than 1.0 cm.The Matlab files read the branch and fruit data from the Excel files and print the fruit trees for visualization. Each tree segment is represented as a conical frustum. More details are given in the Readme.txt file.
Funding provided by: National Institute of Food and AgricultureCrossref Funder Registry ID: http://dx.doi.org/10.13039/100005825Award Number: 2016-67021-24532The fruit data was collected using Polhemus Digitization equipment in California commercial orchards, in the summer of 2017. The procedure of data collection and tree representation is the same as the one reported in:
Arikapudi, R., Vougioukas, S., Saracoglu, T. 2015. Orchard tree digitization for structural-geometrical modelling.
In Proceedings of the 10th European Conference on Precision Agriculture (ECPA), pp. 329 – 336, Volcani Center, Israel. https://doi.org/10.3920/978-90-8686-814-
Diffusive author(s), cohesive author: Analysis of S/N (1994)
No full textThis study indicates the ways in which various aspects of the author(s) are brought forth in Dumb type’s performance art, the S/N production. Previous research has suggested a non-hierarchical organization of Dumb type and the absence of a “privileged author” in Dumb type’s collaborative work, S/N. However, the results that I have investigated from member’s interviews on the creative process of S/N along with my analysis of the recorded images of S/N, indicate a different aspect of the author(s). First, S/N was created through, so to speak, the collective ideas of the members of Dumb type. Further, S/N has at least nine quotations from previous performances, installations, and printed writings, besides the work-in-progress technique. Explicating one of the “author functions” as given by Michel Foucault, each text has plural subjects of the author. However, it has been revealed from members’ interviews that Teiji Furuhashi had a decision-making role in selecting the members’ ideas within the performance. Since then, S/N has had plural subjects of creation; however, Furuhashi is one of the subjects of creation along with the “privileged author.” S/N has plural authors (diffusive authors) yet at the same time, it has a “privileged author,” Teiji Furuhashi (cohesive author)
Decomposition of agricultural tasks into robotic behaviours:S. Blackmore, S. Fountas, S. Vougioukas, L. Tang, C.G. Sørensen, R. Jørgensen
No full textGoing Beyond Counting First Authors in Author Co-citation Analysis
No full textThe 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
Apple orchard production estimation using deep learning strategies: a comparison of tracking-by-detection algorithms - SensitivityAnalysis
No full textThe dataset "Sensitivity Analysis" consists of image sequences (videos) for apple detection and tracking and its corresponding ground truth. The ground truth is presented in MOT format. This dataset is part of the paper:
Villacrés, J., Viscaino, M., Delpiano, J., Vougioukas, S. & Cheein, F. A. (2022). Apple orchard production estimation using deep learning strategies: a comparison of tracking-by-detection algorithms. Computers and Electronics in Agriculture.
The article is currently accepted. For a better reference format, please refer to the journal's official website.
If you have used the material presented in this data set, please cite the previous article.
For more information regarding the dataset, please refer to the paper mentioned below
Apple orchard production estimation using deep learning strategies: a comparison of tracking-by-detection algorithms - CaseStudy
No full textThe dataset "Case Study" consists of image sequences (videos) for apple detection and tracking and its corresponding ground truth. The ground truth is presented in MOT format. This dataset is part of the paper:
Villacrés, J., Viscaino, M., Delpiano, J., Vougioukas, S. & Cheein, F. A. (2022). Apple orchard production estimation using deep learning strategies: a comparison of tracking-by-detection algorithms. Computers and Electronics in Agriculture.
The article is currently accepted. For a better reference format, please refer to the journal's official website.
If you have used the material presented in this data set, please cite the previous article.
For more information regarding the dataset, please refer to the paper mentioned below
Dispelling the Myths Behind First-author Citation Counts
No full textWe 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
Author's address:
No full textCan archives of audiovisual TV interviews be used to make authors more visible to students, and thereby reduce the learning gap between native and non-native language speakers in college classes? We examined students in a college course who learned about one scholar's ideas through watching an audiovisual TV interview (i.e., visible author format) and about another scholar's ideas through reading a formal text description (i.e., invisible author format). For the invisible author, native language speakers scored significantly higher than the non-native language speakers on a corresponding exam question (i.e., a cognitive measure), generated more words on the exam question (i.e., a motivational measure), and mentioned the author's name more often in answering the exam question (i.e., an affective measure). For the visible author, the groups did not differ on any of these measures. These findings provide evidence for the idea that making the author visible through audiovisual TV interviews can eliminate the learning gap between native and non-native language speakers. 3 Universities around the world serve students who are non-native speakers of th
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