288 research outputs found
Applications
Volume 3 describes how resource-aware machine learning methods and techniques are used to successfully solve real-world problems. The book provides numerous specific application examples: in health and medicine for risk modelling, diagnosis, and treatment selection for diseases in electronics, steel production and milling for quality control during manufacturing processes in traffic, logistics for smart cities and for mobile communications
Dense Visual Simultaneous Localisation and Mapping in Collaborative and Outdoor Scenarios
Dense visual simultaneous localisation and mapping (SLAM) systems can produce 3D
reconstructions that are digital facsimiles of the physical space they describe. Systems that
can produce dense maps with this level of fidelity in real time provide foundational spatial
reasoning capabilities for many downstream tasks in autonomous robotics. Over the past
15 years, mapping small scale, indoor environments, such as desks and buildings, with a
single slow moving, hand-held sensor has been one of the central focuses of dense visual
SLAM research.
However, most dense visual SLAM systems exhibit a number of limitations which
mean they cannot be directly applied in collaborative or outdoors settings. The contribution
of this thesis is to address these limitations with the development of new systems and
algorithms for collaborative dense mapping, efficient dense alternation and outdoors
operation with fast camera motion and wide field of view (FOV) cameras. We use
ElasticFusion, a state-of-the-art dense SLAM system, as our starting point where each of
these contributions is implemented as a novel extension to the system.
We first present a collaborative dense SLAM system that allows a number of
cameras starting with unknown initial relative positions to maintain local maps with the
original ElasticFusion algorithm. Visual place recognition across local maps results in
constraints that allow maps to be aligned into a common global reference frame, facilitating
collaborative mapping and tracking of multiple cameras within a shared map.
Within dense alternation based SLAM systems, the standard approach is to fuse
every frame into the dense model without considering whether the information contained
within the frame is already captured by the dense map and therefore redundant. As the
number of cameras or the scale of the map increases, this approach becomes inefficient. In
our second contribution, we address this inefficiency by introducing a novel information
theoretic approach to keyframe selection that allows the system to avoid processing
redundant information. We implement the procedure within ElasticFusion, demonstrating
a marked reduction in the number of frames required by the system to estimate an accurate,
denoised surface reconstruction.
Before dense SLAM techniques can be applied in outdoor scenarios we must
first address their reliance on active depth cameras, and their lack of suitability to fast
camera motion. In our third contribution we present an outdoor dense SLAM system. The system overcomes the need for an active sensor by employing neural network-based depth
inference to predict the geometry of the scene as it appears in each image. To address the
issue of camera tracking during fast motion we employ a hybrid architecture, combining
elements of both dense and sparse SLAM systems to perform camera tracking and to
achieve globally consistent dense mapping.
Automotive applications present a particularly important setting for dense visual
SLAM systems. Such applications are characterised by their use of wide FOV cameras and
are therefore not accurately modelled by the standard pinhole camera model. The fourth
contribution of this thesis is to extend the above hybrid sparse-dense monocular SLAM
system to cater for large FOV fisheye imagery. This is achieved by reformulating the
mapping pipeline in terms of the Kannala-Brandt fisheye camera model. To estimate depth,
we introduce a new version of the PackNet depth estimation neural network (Guizilini et
al., 2020) adapted for fisheye inputs.
To demonstrate the effectiveness of our contributions, we present experimental
results, computed by processing the synthetic ICL-NUIM dataset of Handa et al. (2014) as
well as the real-world TUM-RGBD dataset of Sturm et al. (2012). For outdoor SLAM we
show the results of our system processing the autonomous driving KITTI and KITTI-360
datasets of Geiger et al. (2012a) and Liao et al. (2021) respectively
Systematic Approaches for Telemedicine and Data Coordination for COVID-19 in Baja California, Mexico
Conference proceedings info:
ICICT 2023: 2023 The 6th International Conference on Information and Computer Technologies
Raleigh, HI, United States, March 24-26, 2023
Pages 529-542We provide a model for systematic implementation of telemedicine within a large evaluation center for COVID-19 in the area of Baja California, Mexico. Our model is based on human-centric design factors and cross disciplinary collaborations for scalable data-driven enablement of smartphone, cellular, and video Teleconsul-tation technologies to link hospitals, clinics, and emergency medical services for point-of-care assessments of COVID testing, and for subsequent treatment and quar-antine decisions. A multidisciplinary team was rapidly created, in cooperation with different institutions, including: the Autonomous University of Baja California, the Ministry of Health, the Command, Communication and Computer Control Center
of the Ministry of the State of Baja California (C4), Colleges of Medicine, and the College of Psychologists. Our objective is to provide information to the public and to evaluate COVID-19 in real time and to track, regional, municipal, and state-wide data in real time that informs supply chains and resource allocation with the anticipation of a surge in COVID-19 cases. RESUMEN Proporcionamos un modelo para la implementación sistemática de la telemedicina dentro de un gran centro de evaluación de COVID-19 en el área de Baja California, México. Nuestro modelo se basa en factores de diseño centrados en el ser humano y colaboraciones interdisciplinarias para la habilitación escalable basada en datos de tecnologías de teleconsulta de teléfonos inteligentes, celulares y video para vincular hospitales, clínicas y servicios médicos de emergencia para evaluaciones de COVID en el punto de atención. pruebas, y para el tratamiento posterior y decisiones de cuarentena. Rápidamente se creó un equipo multidisciplinario, en cooperación con diferentes instituciones, entre ellas: la Universidad Autónoma de Baja California, la Secretaría de Salud, el Centro de Comando, Comunicaciones y Control Informático.
de la Secretaría del Estado de Baja California (C4), Facultades de Medicina y Colegio de Psicólogos. Nuestro objetivo es proporcionar información al público y evaluar COVID-19 en tiempo real y rastrear datos regionales, municipales y estatales en tiempo real que informan las cadenas de suministro y la asignación de recursos con la anticipación de un aumento de COVID-19. 19 casos.ICICT 2023: 2023 The 6th International Conference on Information and Computer Technologieshttps://doi.org/10.1007/978-981-99-3236-
Artificial Intelligence and Cognitive Computing
Artificial intelligence (AI) is a subject garnering increasing attention in both academia and the industry today. The understanding is that AI-enhanced methods and techniques create a variety of opportunities related to improving basic and advanced business functions, including production processes, logistics, financial management and others. As this collection demonstrates, AI-enhanced tools and methods tend to offer more precise results in the fields of engineering, financial accounting, tourism, air-pollution management and many more. The objective of this collection is to bring these topics together to offer the reader a useful primer on how AI-enhanced tools and applications can be of use in today’s world. In the context of the frequently fearful, skeptical and emotion-laden debates on AI and its value added, this volume promotes a positive perspective on AI and its impact on society. AI is a part of a broader ecosystem of sophisticated tools, techniques and technologies, and therefore, it is not immune to developments in that ecosystem. It is thus imperative that inter- and multidisciplinary research on AI and its ecosystem is encouraged. This collection contributes to that
Understanding Quantum Technologies 2022
Understanding Quantum Technologies 2022 is a creative-commons ebook that
provides a unique 360 degrees overview of quantum technologies from science and
technology to geopolitical and societal issues. It covers quantum physics
history, quantum physics 101, gate-based quantum computing, quantum computing
engineering (including quantum error corrections and quantum computing
energetics), quantum computing hardware (all qubit types, including quantum
annealing and quantum simulation paradigms, history, science, research,
implementation and vendors), quantum enabling technologies (cryogenics, control
electronics, photonics, components fabs, raw materials), quantum computing
algorithms, software development tools and use cases, unconventional computing
(potential alternatives to quantum and classical computing), quantum
telecommunications and cryptography, quantum sensing, quantum technologies
around the world, quantum technologies societal impact and even quantum fake
sciences. The main audience are computer science engineers, developers and IT
specialists as well as quantum scientists and students who want to acquire a
global view of how quantum technologies work, and particularly quantum
computing. This version is an extensive update to the 2021 edition published in
October 2021.Comment: 1132 pages, 920 figures, Letter forma
ECOS 2012
The 8-volume set contains the Proceedings of the 25th ECOS 2012 International Conference, Perugia, Italy, June 26th to June 29th, 2012. ECOS is an acronym for Efficiency, Cost, Optimization and Simulation (of energy conversion systems and processes), summarizing the topics covered in ECOS: Thermodynamics, Heat and Mass Transfer, Exergy and Second Law Analysis, Process Integration and Heat Exchanger Networks, Fluid Dynamics and Power Plant Components, Fuel Cells, Simulation of Energy Conversion Systems, Renewable Energies, Thermo-Economic Analysis and Optimisation, Combustion, Chemical Reactors, Carbon Capture and Sequestration, Building/Urban/Complex Energy Systems, Water Desalination and Use of Water Resources, Energy Systems- Environmental and Sustainability Issues, System Operation/ Control/Diagnosis and Prognosis, Industrial Ecology
EG-ICE 2021 Workshop on Intelligent Computing in Engineering
The 28th EG-ICE International Workshop 2021 brings together international experts working at the interface between advanced computing and modern engineering challenges. Many engineering tasks require open-world resolutions to support multi-actor collaboration, coping with approximate models, providing effective engineer-computer interaction, search in multi-dimensional solution spaces, accommodating uncertainty, including specialist domain knowledge, performing sensor-data interpretation and dealing with incomplete knowledge. While results from computer science provide much initial support for resolution, adaptation is unavoidable and most importantly, feedback from addressing engineering challenges drives fundamental computer-science research. Competence and knowledge transfer goes both ways
- …