OmniDRL: Robust Pedestrian Detection using Deep Reinforcement Learning on Omnidirectional Cameras

Pedestrian detection is one of the most explored topics in computer vision and robotics. The use of deep learning methods allowed the development of new and highly competitive algorithms. Deep Reinforcement Learning has proved to be within the state-of-the-art in terms of both detection in perspective cameras and robotics applications. However, for detection in omnidirectional cameras, the literature is still scarce, mostly because of their high levels of distortion. This paper presents a novel and efficient technique for robust pedestrian detection in omnidirectional images. The proposed method uses deep Reinforcement Learning that takes advantage of the distortion in the image. By considering the 3D bounding boxes and their distorted projections into the image, our method is able to provide the pedestrian's position in the world, in contrast to the image positions provided by most state-of-the-art methods for perspective cameras. Our method avoids the need of pre-processing steps to remove the distortion, which is computationally expensive. Beyond the novel solution, our method compares favorably with the state-of-the-art methodologies that do not consider the underlying distortion for the detection task.Comment: Accepted in 2019 IEEE Int'l Conf. Robotics and Automation (ICRA

Challenges in Modeling the Effects of Trade Agreements on the Agricultural Sector

Major issues and challenges encountered in modeling and analyzing agricultural and trade policy reforms are reviewed. We focus on the modeling approach and pay special attention to the type and scope of the models, the calibration of a realistic baseline scenario, the representation of the reform agreement, the use of extra-model information, the choice of metrics to measure reform impacts, and emerging issues in policy modeling. Existing solutions and unresolved issues are examined. We stress the complementarity of various modeling approaches in assessing policy reforms and the importance of helping users understand the limitations of the chosen approach. Keywords: agricultural policy, economic modeling, trade agreements. JEL classification: Q17, Q18, F13

Comparative study of Land Use/Cover classification using Flickr photos, satellite imagery and Corine land cover database

Ponencias, comunicaciones y pósters presentados en el 17th AGILE Conference on Geographic Information Science "Connecting a Digital Europe through Location and Place", celebrado en la Universitat Jaume I del 3 al 6 de junio de 2014.Volunteered Geographic Information has been increasing exponentially over the last years, capturing the attention of the scientific community. Researchers have been very active exploring a vast amount of initiatives and trying to develop methodologies and possible real applications for this new source of geographic information. Land Use/Cover production is one of the areas where this type of geographic information might be very useful. In this paper we evaluate if geo-referenced and publicly available photos from the Flickr initiative can be used as a source of geographic information to help Land Use/Cover classification. Using the Corine Land Cover nomenclature, we compare the classification obtained for selected photo locations, against the classification obtained from high resolution satellite imagery for the same locations. We conclude that this source cannot be used alone for the purpose of Land Use/Cover classification but we also believe that it might contain helpful information if combined with other sources

Land Allocation Effects of the Global Ethanol Surge: Predictions from the International FAPRI Model

We quantify the emergence of biofuel markets and its impact on U.S. and world agriculture for the coming decade using the multi-market multi-commodity international FAPRI model. The model incorporates the tradeoffs between biofuel, feed, and food production and consumption and international feedback effects of the emergence through world commodity prices and trade. We examine land allocation by type of crop, and pasture use for countries growing feedstock for ethanol (corn, sorghum, wheat, sugarcane, and other grains) and major crops competing with feedstock for land resources such as oilseeds. We shock the model with exogenous changes in ethanol demand, first in the United States, then in Brazil, China, EU, and India, and compute shock multipliers for land allocation decisions for crops and countries of interest. The multipliers show at the margin how sensitive land allocation is to the growing demand for ethanol. Land moves away from major crops and pasture competing for resources with feedstock crops. Because of the high U.S. tariff on ethanol, higher U.S. demand for ethanol translates into a U.S. ethanol production expansion. The latter has global effects on land allocation as higher coarse grains prices transmit worldwide. Changes in U.S. coarse grain prices also affect U.S. wheat and oilseeds prices, which are all transmitted to world markets. In contrast, expansion in Brazil ethanol use and production chiefly affects land used for sugarcane production in Brazil and to a lesser extent in other sugar-producing countries, but with small impact on other land uses in most countries. Keywords: Acreage, area, biofuel, corn, crops, ethanol, FAPRI model, feedstock, land, sugar, sugarcane. JEL Code: Q42 Q17 Q15ethanol; acreage; area; biofuel; corn; crops; FAPRI model; feedstock; land; sugar; sugarcane

AGRICULTURAL MARKETS LIBERALIZATION AND THE DOHA ROUND

Using a partial equilibrium model of world agriculture, we investigate the multilateral removal of all border taxes and farm programs and their distortion of world agricultural markets. These distortions have significant terms-of-trade effects. World trade is also significantly impacted by both types of distortions. Trade expansion is substantial for most commodities, especially dairy, meats, and vegetable oils. Net agricultural and food exporters (Brazil, Australia, and Argentina) emerge with expanded exports; whereas net importing countries with limited distortions before liberalization are penalized by higher world markets prices and reduced imports. The US gains significant export shares in livestock products and imports more dairy products. Without protection and domestic subsidies, the EU loses many of its livestock and dairy export markets.Doha, Agriculture, trade liberalization, domestic policy, International Relations/Trade,

Efeito da conservação e do curtimento na qualidade de couros ovinos.

Editado por Ana Rita de Araújo Nogueira, Simone Cristina Méo Niciur

Influência da raça na qualidade de couros caprinos

O estudo foi conduzido com o objetivo de avaliar a influência da raça na qualidade de couros caprinos. Foram utilizados cinco caprinos de cada uma das raças: Anglo Nubiana, Alpina e Saanen, com seis meses de idade. Os animais foram abatidos e as peles foram curtidas ao cromo e recurtidas com recurtente acrílico. Dos couros foram retiradas três amostras na posição paralela e três na perpendicular à linha dorsal para a avaliação da qualidade intrínseca de resistência à tração, ao rasgamento e ao lastômetro. As médias dos resultados foram comparadas pelo teste de Tukey ao nível de 5% de probabilidade. A raça não influenciou a resistência à distensão da superfície dos couros dos animais estudados no teste de lastômetro. As médias da resistência dos couros à tração foram maiores na posição longitudinal (P&#61500;0,05) para as três raças. Na posição longitudinal os couros dos caprinos Anglo Nubianos foram mais resistentes à tração (P<0,05), comparado com os couros das outras duas raças, que não apresentaram diferença entre si. A resistência dos couros ao rasgamento não sofreu influência da posição, porém na posição transversal os couros dos caprinos Anglo Nubianos foram mais resistentes (P<0,05), comparado com os couros das outras duas raças, que não apresentaram diferença entre si. A raça e a posição de retirada das amostras de couro influenciam a qualidade de couros caprinos