42,658 research outputs found
Fine-Grained Object Recognition and Zero-Shot Learning in Remote Sensing Imagery
Fine-grained object recognition that aims to identify the type of an object
among a large number of subcategories is an emerging application with the
increasing resolution that exposes new details in image data. Traditional fully
supervised algorithms fail to handle this problem where there is low
between-class variance and high within-class variance for the classes of
interest with small sample sizes. We study an even more extreme scenario named
zero-shot learning (ZSL) in which no training example exists for some of the
classes. ZSL aims to build a recognition model for new unseen categories by
relating them to seen classes that were previously learned. We establish this
relation by learning a compatibility function between image features extracted
via a convolutional neural network and auxiliary information that describes the
semantics of the classes of interest by using training samples from the seen
classes. Then, we show how knowledge transfer can be performed for the unseen
classes by maximizing this function during inference. We introduce a new data
set that contains 40 different types of street trees in 1-ft spatial resolution
aerial data, and evaluate the performance of this model with manually annotated
attributes, a natural language model, and a scientific taxonomy as auxiliary
information. The experiments show that the proposed model achieves 14.3%
recognition accuracy for the classes with no training examples, which is
significantly better than a random guess accuracy of 6.3% for 16 test classes,
and three other ZSL algorithms.Comment: G. Sumbul, R. G. Cinbis, S. Aksoy, "Fine-Grained Object Recognition
and Zero-Shot Learning in Remote Sensing Imagery", IEEE Transactions on
Geoscience and Remote Sensing (TGRS), in press, 201
Simple identification tools in FishBase
Simple identification tools for fish species were included in the FishBase information system from its inception. Early tools made use of the relational model and characters like fin ray meristics. Soon pictures and drawings were added as a further help, similar to a field guide. Later came the computerization of existing dichotomous keys, again in combination with pictures and other information, and the ability to restrict possible species by country, area, or taxonomic group. Today, www.FishBase.org offers four different ways to identify species. This paper describes these tools with their advantages and disadvantages, and suggests various options for further
development. It explores the possibility of a holistic and integrated computeraided strategy
Genes Suggest Ancestral Colour Polymorphisms Are Shared across Morphologically Cryptic Species in Arctic Bumblebees
email Suzanne orcd idCopyright: © 2015 Williams et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
Share and share alike: Encouraging the reuse of academic resources through the Scottish electronic staff development library
This paper reports on the findings of a consultancy procedure conducted within the Scottish Higher Education staff development community and focusing on the reuse and sharing of communications and information technology resources for teaching and learning. While this consultancy was conducted primarily to inform the development of the Scottish electronic Staff Development Library (SeSDL), its findings, will be of relevance to colleagues working in the fields of staff development and C&IT and all those involved in the creation of shared teaching and learning resources. The consultancy identified general staff development demands, specific pedagogical requirements, and concerns relating to the provision, reuse and sharing of staff development resources. The SeSDL Project will attempt to address these demands through the development of a Web‐based resource centre, which will facilitate the reuse and sharing of high‐quality staff development resources. Library materials are stored in the form of granules which are branded with IMS compatible metadata and which are classified using a controlled educational taxonomy. Staff developers will be able to assemble these granular components to build customized lessons tailored to meet the needs of their own departments and institutions
Incorporating molecular data in fungal systematics: a guide for aspiring researchers
The last twenty years have witnessed molecular data emerge as a primary
research instrument in most branches of mycology. Fungal systematics, taxonomy,
and ecology have all seen tremendous progress and have undergone rapid,
far-reaching changes as disciplines in the wake of continual improvement in DNA
sequencing technology. A taxonomic study that draws from molecular data
involves a long series of steps, ranging from taxon sampling through the
various laboratory procedures and data analysis to the publication process. All
steps are important and influence the results and the way they are perceived by
the scientific community. The present paper provides a reflective overview of
all major steps in such a project with the purpose to assist research students
about to begin their first study using DNA-based methods. We also take the
opportunity to discuss the role of taxonomy in biology and the life sciences in
general in the light of molecular data. While the best way to learn molecular
methods is to work side by side with someone experienced, we hope that the
present paper will serve to lower the learning threshold for the reader.Comment: Submitted to Current Research in Environmental and Applied Mycology -
comments most welcom
- …