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Full-Text Articles in Engineering
Emocolor : Fine-Grained Emotion Recognition From Skin Color Information, Maria Guadalupe Jimenez Velasco
Emocolor : Fine-Grained Emotion Recognition From Skin Color Information, Maria Guadalupe Jimenez Velasco
Open Access Theses & Dissertations
In everyday human-to-human communication, emotions play a fundamental role. Emotions represent the affective behavior of humans that is multi-modal, subtle, and complex. Previous approaches based on conventional computer vision explicitly used shape information. Modern approaches based on deep learning implicitly exploit all information available in the image, but by their nature make it difficult to assess the contributions of each source of information. In addition, skin color as a unimodal technique to recognize emotions has been explored to recognize only three coarse-grained emotions in valence space.To the best of our knowledge, this work presents the first approach to fine-grained emotion …
Evaluating Flow Features For Network Application Classification, Carlos Alcantara
Evaluating Flow Features For Network Application Classification, Carlos Alcantara
Open Access Theses & Dissertations
Communication networks provide the foundational services on which our modern economy depends. These services include data storage and transfer, video and voice telephony, gaming, multimedia streaming, remote invocation, and the world wide web. Communication networks are large-scale distributed systems composed of heterogeneous equipment. As a result of scale and heterogeneity, communication networks are cumbersome to manage (e.g., configure, assess performance, detect faults) by human operators. With the emergence of easily accessible network data and machine learning algorithms, there is a great opportunity to move network management towards increasing automation. Network management automation will allow for a reduced likelihood of human …
A Comparison Of Data-Driven And Process-Based Modeling For Nutrient Estimation In A Eutrophic Reservoir, Yohtaro Kobayashi
A Comparison Of Data-Driven And Process-Based Modeling For Nutrient Estimation In A Eutrophic Reservoir, Yohtaro Kobayashi
Open Access Theses & Dissertations
As land use around bodies of water changes, the need to model the body of water increases. Models help to educate, understand, and predict the state of water. Process-based models are commonly used in modelling bodies of water, but there are challenges with these kinds of models. They require data which can be difficult for certain communities to obtain due to logistics or cost, are computationally intensive, technically complicated, and require calibration. In contrast, a data-driven model simply connect relationships from the data, are not as computationally intensive nor technically complicated, and do not require calibration. This research compared a …
Uav Parameter Estimation Through Machine Learning, Andres Enriquez Fernandez
Uav Parameter Estimation Through Machine Learning, Andres Enriquez Fernandez
Open Access Theses & Dissertations
Parameter identification of Unmanned Aerial Vehicles (UAV) is very helpful for understanding cause-effect relationships of physical phenomenon, investigating system performance and characteristics, fault diagnostics, control development/tuning, and more. Traditional ways of performing parameter identification involve establishing a mathematical model that describes the system's behavior. The equations in the model contain parameters that are estimated indirectly from measured flight data. This parameter identification process requires knowledge of the physics involved. Also, it necessitates a careful consideration of the aircraft instrumentation for accurate measurements. It also requires careful design of the flight maneuvers to ensure thorough excitation of the flight dynamics involved. …