Search results for "pattern"
showing 10 items of 4203 documents
Evaluation of image processing technique as an expert system in mulberry fruit grading based on ripeness level using artificial neural networks (ANNs…
2020
Abstract Image processing and artificial intelligence (AI) techniques have been applied to analyze, evaluate and classify mulberry fruit according to their ripeness (unripe, ripe, and overripe). A total of 577 mulberries were graded by an expert and the images were captured by an imaging system. Then, the geometrical properties, color, and texture characteristics of each segmented mulberry was extracted using two feature reduction methods: Correlation-based Feature Selection subset (CFS) and Consistency subset (CONS). Artificial Neural Networks (ANN) and Support Vector Machine (SVM) were applied to classify mulberry fruit. ANN classification with the CFS subset feature extraction method res…
Interspecific comparison of the performance of soaring migrants in relation to morphology, meteorological conditions and migration strategies.
2012
This is an open-access article distributed under the terms of the Creative Commons Attribution License.-- et al.
Traits mediate niches and co‐occurrences of forest beetles in ways that differ among bioclimatic regions
2021
Aim The aim of this study was to investigate the role of traits in beetle community assembly and test for consistency in these effects among several bioclimatic regions. We asked (1) whether traits predicted species’ responses to environmental gradients (i.e. their niches), (2) whether these same traits could predict co-occurrence patterns and (3) how consistent were niches and the role of traits among study regions. Location Boreal forests in Norway and Finland, temperate forests in Germany. Taxon Wood-living (saproxylic) beetles. Methods We compiled capture records of 468 wood-living beetle species from the three regions, along with nine morphological and ecological species traits. Eight …
Seasonality of spatial patterns of abundance, biomass and biodiversity in a demersal community of the NW Mediterranean Sea
2020
14 pages, 5 figures, 4 tables
GrassPlot – a database of multi-scale plant diversity in Palaearctic grasslands
2018
GrassPlot is a collaborative vegetation-plot database organised by the Eurasian Dry Grassland Group (EDGG) and listed in the Global Index of Vegetation-Plot Databases (GIVD ID EU-00-003). GrassPlot collects plot records (relevés) from grasslands and other open habitats of the Palaearctic biogeographic realm. It focuses on precisely delimited plots of eight standard grain sizes (0.0001; 0.001; ... 1,000 m²) and on nested-plot series with at least four different grain sizes. The usage of GrassPlot is regulated through Bylaws that intend to balance the interests of data contributors and data users. The current version (v. 1.00) contains data for approximately 170,000 plots of different sizes a…
Beta diversity of stream insects differs between boreal and subtropical regions, but land use does not generally cause biotic homogenization
2021
Made available in DSpace on 2021-06-25T10:17:36Z (GMT). No. of bitstreams: 0 Previous issue date: 2021-03-01 Previous studies have found mixed results regarding the relationship between beta diversity and latitude. In addition, by influencing local environmental heterogeneity, land use maymodify spatial taxonomic and functional variability among communities causing biotic differentiation or homogenization. We tested 1) whether taxonomic and functional beta diversities among streams within watersheds differ between subtropical and boreal regions and 2) whether land use is related to taxonomic and functional beta diversities in both regions.Wesampled aquatic insects in 100 subtropical (Brazil…
Biometric Fish Classification of Temperate Species Using Convolutional Neural Network with Squeeze-and-Excitation
2019
Our understanding and ability to effectively monitor and manage coastal ecosystems are severely limited by observation methods. Automatic recognition of species in natural environment is a promising tool which would revolutionize video and image analysis for a wide range of applications in marine ecology. However, classifying fish from images captured by underwater cameras is in general very challenging due to noise and illumination variations in water. Previous classification methods in the literature relies on filtering the images to separate the fish from the background or sharpening the images by removing background noise. This pre-filtering process may negatively impact the classificat…
Brown bear behaviour in human-modified landscapes: The case of the endangered Cantabrian population, NW Spain
2018
Large carnivores are recolonizing parts of their historical range in Europe, a heavily modified human landscape. This calls for an improvement of our knowledge on how large carnivores manage to coexist with humans, and on the effects that human activity has on large carnivore behaviour, especially in areas where carnivore populations are still endangered. Brown bears Ursus arctos have been shown to be sensitive to the presence of people and their activities. Thus, bear conservation and management should take into account potential behavioural alterations related to living in human-modified landscapes. We studied the behaviour of brown bears in the Cantabrian Mountains, NW Spain, where an en…
Benchmark database for fine-grained image classification of benthic macroinvertebrates
2018
Managing the water quality of freshwaters is a crucial task worldwide. One of the most used methods to biomonitor water quality is to sample benthic macroinvertebrate communities, in particular to examine the presence and proportion of certain species. This paper presents a benchmark database for automatic visual classification methods to evaluate their ability for distinguishing visually similar categories of aquatic macroinvertebrate taxa. We make publicly available a new database, containing 64 types of freshwater macroinvertebrates, ranging in number of images per category from 7 to 577. The database is divided into three datasets, varying in number of categories (64, 29, and 9 categori…
Temperate Fish Detection and Classification: a Deep Learning based Approach
2021
A wide range of applications in marine ecology extensively uses underwater cameras. Still, to efficiently process the vast amount of data generated, we need to develop tools that can automatically detect and recognize species captured on film. Classifying fish species from videos and images in natural environments can be challenging because of noise and variation in illumination and the surrounding habitat. In this paper, we propose a two-step deep learning approach for the detection and classification of temperate fishes without pre-filtering. The first step is to detect each single fish in an image, independent of species and sex. For this purpose, we employ the You Only Look Once (YOLO) …