3,791 research outputs found
Planetary Hinterlands:Extraction, Abandonment and Care
This open access book considers the concept of the hinterland as a crucial tool for understanding the global and planetary present as a time defined by the lasting legacies of colonialism, increasing labor precarity under late capitalist regimes, and looming climate disasters. Traditionally seen to serve a (colonial) port or market town, the hinterland here becomes a lens to attend to the times and spaces shaped and experienced across the received categories of the urban, rural, wilderness or nature. In straddling these categories, the concept of the hinterland foregrounds the human and more-than-human lively processes and forms of care that go on even in sites defined by capitalist extraction and political abandonment. Bringing together scholars from the humanities and social sciences, the book rethinks hinterland materialities, affectivities, and ecologies across places and cultural imaginations, Global North and South, urban and rural, and land and water
A novel segmentation approach for crop modeling using a plenoptic light-field camera : going from 2D to 3D
OMICASCrop phenotyping is a desirable task in crop characterization since it allows the farmer
to make early decisions, and therefore be more productive.
This research is motivated by the generation of tools for rice crop phenotyping within
the OMICAS research ecosystem framework. It proposes implementing the image process-
ing technologies and artificial intelligence technics through a multisensory approach with
multispectral information. Three main stages are covered: (i) A segmentation approach
that allows identifying the biological material associated with plants, and the main contri-
bution is the GFKuts segmentation approach; (ii) a strategy that allows the development
of sensory fusion between three different cameras, a 3D camera, an infrared multispectral
camera, and a thermal multispectral camera, this stage is developed through a complex
object detection approach; and (iii) the characterization of a 4D model that generates
topological relationships with the information of the point cloud, the main contribution
of this strategy is the improvement of the point cloud captured by the 3D sensor, in this
sense, this stage improves the acquisition of any 3D sensor.
This research presents a development that receives information from multiple sensors,
especially infrared 2D, and generates a single 4D model in geometric space [X, Y, Z]. This
model integrates the color information of 5 channels and topological information, relating
the points in space. Overall, the research allows the integration of the 3D information from
any sensor\technology and the multispectral channels from any multispectral camera, to
generate direct non-invasive measurements on the plant.MagĂster en IngenierĂa ElectrĂłnicaMagĂster en Inteligencia ArtificialMaestrĂahttps://orcid.org/ 0000-0002-1477-6825https://scholar.google.com/citations?user=cpuxcwgAAAAJ&hl=eshttps://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=000155691
Dynamics and Modelling of the 2015 Calbuco eruption Volcanic Debris Flows (Chile). From field evidence to a primary lahar model
The Calbuco volcanic eruption of 2015, was characterized by two explosive phases with partialand major column collapses that triggered lahars in many of the flanks of the volcano. Large lahar flows descended to the southern flank where highly fractured ice bodies were emplaced on steep slopes.In this study, we present a chronology of the volcanic flows based on a multi parameterdata set that includes social media, reports of authoritative institutions, instrumental monitoringdata and published research literature on the eruption. Our review established thatlahars in the Amarillo river began during the first phase of the eruption due to the sustained emplacement of pyroclastic flows in its catchment. In contrast, we propose that the lahars in theBlanco – Correntoso river system and the Este river were likely to have been triggered by asudden mechanical collapse of the glacier that triggered mixed avalanches which transitionedinto lahars downstream.Our observations include inundation cross-sections, estimates of flow speeds, and characterization of the morphology, grain sizes, and componentry of deposits.Field measurements are used together with instrumental data for calibrating a dynamic, physics-based model of lahar, Laharflow. We model flows in the Blanco – Correntoso river system and explore the influence of the model parameters on flow predictions in an ensemble of simulations. We develop a calibration that accounts for the substantial epistemic uncertainties in our observations and the model formulation, that seeks to determine plausible ranges for the model parameters, including those representing the lahar source. Our approach highlights the parameters in the model that have a dominant effect on the ability of the model to match observations, indicating where further development and additional observations could improve model predictions. The simulations in our ensemble that provide plausible matches to the observations are combined to produce flow inundation maps
Introduction to Facial Micro Expressions Analysis Using Color and Depth Images: A Matlab Coding Approach (Second Edition, 2023)
The book attempts to introduce a gentle introduction to the field of Facial
Micro Expressions Recognition (FMER) using Color and Depth images, with the aid
of MATLAB programming environment. FMER is a subset of image processing and it
is a multidisciplinary topic to analysis. So, it requires familiarity with
other topics of Artifactual Intelligence (AI) such as machine learning, digital
image processing, psychology and more. So, it is a great opportunity to write a
book which covers all of these topics for beginner to professional readers in
the field of AI and even without having background of AI. Our goal is to
provide a standalone introduction in the field of MFER analysis in the form of
theorical descriptions for readers with no background in image processing with
reproducible Matlab practical examples. Also, we describe any basic definitions
for FMER analysis and MATLAB library which is used in the text, that helps
final reader to apply the experiments in the real-world applications. We
believe that this book is suitable for students, researchers, and professionals
alike, who need to develop practical skills, along with a basic understanding
of the field. We expect that, after reading this book, the reader feels
comfortable with different key stages such as color and depth image processing,
color and depth image representation, classification, machine learning, facial
micro-expressions recognition, feature extraction and dimensionality reduction.
The book attempts to introduce a gentle introduction to the field of Facial
Micro Expressions Recognition (FMER) using Color and Depth images, with the aid
of MATLAB programming environment.Comment: This is the second edition of the boo
Synthetic Aperture Radar (SAR) Meets Deep Learning
This reprint focuses on the application of the combination of synthetic aperture radars and depth learning technology. It aims to further promote the development of SAR image intelligent interpretation technology. A synthetic aperture radar (SAR) is an important active microwave imaging sensor, whose all-day and all-weather working capacity give it an important place in the remote sensing community. Since the United States launched the first SAR satellite, SAR has received much attention in the remote sensing community, e.g., in geological exploration, topographic mapping, disaster forecast, and traffic monitoring. It is valuable and meaningful, therefore, to study SAR-based remote sensing applications. In recent years, deep learning represented by convolution neural networks has promoted significant progress in the computer vision community, e.g., in face recognition, the driverless field and Internet of things (IoT). Deep learning can enable computational models with multiple processing layers to learn data representations with multiple-level abstractions. This can greatly improve the performance of various applications. This reprint provides a platform for researchers to handle the above significant challenges and present their innovative and cutting-edge research results when applying deep learning to SAR in various manuscript types, e.g., articles, letters, reviews and technical reports
Computer Vision and Architectural History at Eye Level:Mixed Methods for Linking Research in the Humanities and in Information Technology
Information on the history of architecture is embedded in our daily surroundings, in vernacular and heritage buildings and in physical objects, photographs and plans. Historians study these tangible and intangible artefacts and the communities that built and used them. Thus valuableinsights are gained into the past and the present as they also provide a foundation for designing the future. Given that our understanding of the past is limited by the inadequate availability of data, the article demonstrates that advanced computer tools can help gain more and well-linked data from the past. Computer vision can make a decisive contribution to the identification of image content in historical photographs. This application is particularly interesting for architectural history, where visual sources play an essential role in understanding the built environment of the past, yet lack of reliable metadata often hinders the use of materials. The automated recognition contributes to making a variety of image sources usable forresearch.<br/
Workshop Proceedings of the 12th edition of the KONVENS conference
The 2014 issue of KONVENS is even more a forum for exchange: its main topic is the interaction between Computational Linguistics and Information Science, and the synergies such interaction, cooperation and integrated views can produce. This topic at the crossroads of different research traditions which deal with natural language as a container of knowledge, and with methods to extract and manage knowledge that is linguistically represented is close to the heart of many researchers at the Institut für Informationswissenschaft und Sprachtechnologie of Universität Hildesheim: it has long been one of the institute’s research topics, and it has received even more attention over the last few years
Digital agriculture: research, development and innovation in production chains.
Digital transformation in the field towards sustainable and smart agriculture. Digital agriculture: definitions and technologies. Agroenvironmental modeling and the digital transformation of agriculture. Geotechnologies in digital agriculture. Scientific computing in agriculture. Computer vision applied to agriculture. Technologies developed in precision agriculture. Information engineering: contributions to digital agriculture. DIPN: a dictionary of the internal proteins nanoenvironments and their potential for transformation into agricultural assets. Applications of bioinformatics in agriculture. Genomics applied to climate change: biotechnology for digital agriculture. Innovation ecosystem in agriculture: Embrapa?s evolution and contributions. The law related to the digitization of agriculture. Innovating communication in the age of digital agriculture. Driving forces for Brazilian agriculture in the next decade: implications for digital agriculture. Challenges, trends and opportunities in digital agriculture in Brazil
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