Multi-dimensional machine learning approaches for fruit shape phenotyping in strawberry
نویسندگان
چکیده
منابع مشابه
Multi-Strategy Approaches to Active Learning for Statistical Machine Translation
This paper investigates active learning to improve statistical machine translation (SMT) for low-resource language pairs, i.e., when there is very little pre-existing parallel text. Since generating additional parallel text to train SMT may be costly, active sampling selects the sentences from a monolingual corpus which if translated would have maximal positive impact in training SMT models. We...
متن کاملMachine Learning for High-Throughput Stress Phenotyping in Plants.
Advances in automated and high-throughput imaging technologies have resulted in a deluge of high-resolution images and sensor data of plants. However, extracting patterns and features from this large corpus of data requires the use of machine learning (ML) tools to enable data assimilation and feature identification for stress phenotyping. Four stages of the decision cycle in plant stress pheno...
متن کاملMachine Learning for Plant Phenotyping Needs Image Processing.
Sotirios A. Tsaftaris , Massimo Minervini B and Hanno Scharr C A Institute for Digital Communications, School of Engineering, University of Edinburgh, Edinburgh, EH9 3FG, UK B Pattern Recognition and Image Analysis (PRIAn) IMT School for Advanced Studies, Lucca, 55100, Italy C Institute of Bioand Geosciences: Plant Sciences (IBG-2) Forschungszentrum Jülich GmbH, D-52425, Jülich, Germany * Corre...
متن کاملThree New Systematic Approaches for Computing Heffron-Phillips Multi-Machine Model Coefficients (RESEARCH NOTE)
This paper presents three new systematic approaches for computing coefficient matrices of the Heffron-Phillips multi-machine model (K1, …, K6). The amount of computations needed for conventional and three new approaches are compared by counting number of multiplications and divisions. The advantages of new approaches are: (1) their computation burdens are less than 73 percent of that of convent...
متن کاملApproaches to machine learning
The field of machine learning strives to develop methods and techniques to automate the acquisition of new information, new skills, and new ways of organizing existing information. In this article, we review the major approaches to machine learning in symbolic domains, covering the tasks of learning concepts from examples, learning search methods, conceptual clustering, and language acquisition...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: GigaScience
سال: 2020
ISSN: 2047-217X
DOI: 10.1093/gigascience/giaa030