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Proceedings of the 2011 international workshop on Situation activity & goal awareness - SAGAware '11, 2011
Activity recognition is an emerging field that demands active research in ubiquitous computing for analyzing complex scenarios such as concurrent situation assessment and domination of major over the minor activities. In this paper, an evolutionary ensembles approach using Genetic Algorithm (GA) as a homogeneous learner has been proposed. This approach
Muhammad Fahim +3 more
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Activity recognition is an emerging field that demands active research in ubiquitous computing for analyzing complex scenarios such as concurrent situation assessment and domination of major over the minor activities. In this paper, an evolutionary ensembles approach using Genetic Algorithm (GA) as a homogeneous learner has been proposed. This approach
Muhammad Fahim +3 more
openaire +1 more source
Proceedings of the AAAI Conference on Artificial Intelligence
This paper outlines a proposal regarding the use of machine learning, specifically a long-short term model, to increase the military’s effectiveness and safety protocols. The approach is to collect data from weapons training and apply it to a model that can distinguish between weapon activities.
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This paper outlines a proposal regarding the use of machine learning, specifically a long-short term model, to increase the military’s effectiveness and safety protocols. The approach is to collect data from weapons training and apply it to a model that can distinguish between weapon activities.
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Egocentric Activity Recognition on a Budget
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018Recent advances in embedded technology have enabled more pervasive machine learning. One of the common applications in this field is Egocentric Activity Recognition (EAR), where users wearing a device such as a smartphone or smartglasses are able to receive feedback from the embedded device. Recent research on activity recognition has mainly focused on
Rafael Possas +2 more
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Duration discretisation for activity recognition
Technology and Health Care, 2007Activity recognition has become a key component within smart environments that aim at providing assistive solutions for their users. Learning high level activities from low level sensor data depends on several parameters, one of which is the duration of the activities themselves.
Priyanka, Chaurasia +3 more
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Active learning for sketch recognition
Computers & Graphics, 2015The increasing availability of pen-based tablets, and pen-based interfaces opened the avenue for computer graphics applications that can utilize sketch recognition technologies for natural interaction. This has led to an increasing interest in sketch recognition algorithms within the computer graphics community.
Erelcan Yanik, Tevfik Metin Sezgin
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A Factorization Approach for Activity Recognition
2003 Conference on Computer Vision and Pattern Recognition Workshop, 2003Understanding activities arising out of the interactions of a configuration of moving objects is an important problem in video understanding, with applications in surveillance and monitoring. A special situation is when the objects are small enough to be represented as points on a 2D plane. In this paper, we introduce a novel method of representing the
Amit K. Roy-Chowdhury, Rama Chellappa
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Active Monte Carlo Recognition
2007In this paper we introduce Active Monte Carlo Recognition (AMCR), a new approach for object recognition. The method is based on seeding and propagating "relational" particles that represent hypothetical relations between low-level perception and high-level object knowledge.
Felix von Hundelshausen +1 more
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Active rangefinding and recognition with Cubicscope
1996An active rangefinding using the Cubicscope is described in the paper. The following topics are reviewed: the principle of the Cubicscope, 3-D shape reconstruction by multiple range images obtained from actively selected viewpoints, high-speed edge detection from range image, and polyhedral object recognition by adaptive viewpoint selection.
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A Survey on Deep Learning for Human Activity Recognition
ACM Computing Surveys, 2022Shahrokh Valaee +2 more
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