Search results for " lea"
showing 10 items of 6823 documents
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…
Leaf-Level Spectral Fluorescence Measurements : Comparing Methodologies for Broadleaves and Needles
2019
Successful measurements of chlorophyll fluorescence (ChlF) spectral properties (typically in the wavelength range of 650–850 nm) across plant species, environmental conditions, and stress levels are a first step towards establishing a quantitative link between solar-induced chlorophyll fluorescence (SIF), which can only be measured at discrete ChlF spectral bands, and photosynthetic functionality. Despite its importance and significance, the various methodologies for the estimation of leaf-level ChlF spectral properties have not yet been compared, especially when applied to leaves with complex morphology, such as needles. Here we present, to the best of our knowledge, a first comparison of …
On the Role of Perception: Understanding Stakeholders’ Collaboration in Natural Resources Management through the Evolutionary Theory of Innovation
2021
Natural resources management deals with highly complex socioecological systems. This complexity raises a conundrum, since wide-ranging knowledge from different sources and types is needed, but at the same time none of these types of knowledge is able by itself to provide the basis for a viable productive system, and mismatches between the two of them are common. Therefore, a growing body of literature has examined the integration of different types of knowledge in fisheries management. In this paper, we aim to contribute to this ongoing debate by integrating the evolutionary theory of innovation—and specifically the concept of proximity—and the theory of perception. We set up a theoretical …
Predators' consumption of unpalatable prey does not vary as a function of bitter taste perception
2020
Many prey species contain defensive chemicals that are described as tasting bitter. Bitter taste perception is, therefore, assumed to be important when predators are learning about prey defenses. However, it is not known how individuals differ in their response to bitter taste, and how this influences their foraging decisions. We conducted taste perception assays in which wild-caught great tits (Parus major) were given water with increasing concentrations of bitter-tasting chloroquine diphosphate until they showed an aversive response to bitter taste. This response threshold was found to vary considerably among individuals, ranging from chloroquine concentrations of 0.01 mmol/L to 8 mmol/L.…
Novel simple templates for reproducible positioning of skin applicators in brachytherapy.
2016
Purpose : Esteya and Valencia surface applicators are designed to treat skin tumors using brachytherapy. In clinical practice, in order to avoid errors that may affect the treatment outcome, there are two issues that need to be carefully addressed. First, the selected applicator for the treatment should provide adequate margin for the target, and second, the applicator has to be precisely positioned before each treatment fraction. In this work, we describe the development and use of a new acrylic templates named Template La Fe-ITIC. They have been designed specifically to help the clinical user in the selection of the correct applicator, and to assist the medical staff in reproducing the po…
Achievement of partial nitrification under different carbon-to-nitrogen ratio and ammonia loading rate for the co-treatment of landfill leachate with…
2019
Abstract Partial nitrification (PN) is a technically and economically effective solution for the treatment of wastewater featuring low C/N ratio, allowing to achieve approximately 25% energy saving and 40% carbon source for denitrification. This study investigated the effect of different carbon to nitrogen ratio (C/N) and ammonia loading rate (ALR) on PN performances in a sequencing batch reactor (SBR) treating landfill leachate with municipal wastewater. The aim was to find an optimum range for C/N and ALR to maximize PN performances. Results demonstrated that a proper balancing between ALR and C/N is crucial to achieve high PN efficiency. The results highlighted the existence of an optimu…
Simple learning rules to cope with changing environments
2008
10 pages; International audience; We consider an agent that must choose repeatedly among several actions. Each action has a certain probability of giving the agent an energy reward, and costs may be associated with switching between actions. The agent does not know which action has the highest reward probability, and the probabilities change randomly over time. We study two learning rules that have been widely used to model decision-making processes in animals-one deterministic and the other stochastic. In particular, we examine the influence of the rules' 'learning rate' on the agent's energy gain. We compare the performance of each rule with the best performance attainable when the agent …
Thompson Sampling Based Active Learning in Probabilistic Programs with Application to Travel Time Estimation
2019
The pertinent problem of Traveling Time Estimation (TTE) is to estimate the travel time, given a start location and a destination, solely based on the coordinates of the points under consideration. This is typically solved by fitting a function based on a sequence of observations. However, it can be expensive or slow to obtain labeled data or measurements to calibrate the estimation function. Active Learning tries to alleviate this problem by actively selecting samples that minimize the total number of samples needed to do accurate inference. Probabilistic Programming Languages (PPL) give us the opportunities to apply powerful Bayesian inference to model problems that involve uncertainties.…
A Methodology to Derive Global Maps of Leaf Traits Using Remote Sensing and Climate Data
2018
This paper introduces a modular processing chain to derive global high-resolution maps of leaf traits. In particular, we present global maps at 500 m resolution of specific leaf area, leaf dry matter content, leaf nitrogen and phosphorus content per dry mass, and leaf nitrogen/phosphorus ratio. The processing chain exploits machine learning techniques along with optical remote sensing data (MODIS/Landsat) and climate data for gap filling and up-scaling of in-situ measured leaf traits. The chain first uses random forests regression with surrogates to fill gaps in the database (> 45% of missing entries) and maximizes the global representativeness of the trait dataset. Plant species are then a…
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) …