Results 141 to 150 of about 2,923,075 (185)
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Continual Learning for Activity Recognition
2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2022The recent success of deep neural networks in prediction tasks on wearable sensor data is evident. However, in more practical online learning scenarios, where new data arrive sequentially, neural networks suffer severely from the "catastrophic forgetting" problem.
Ramesh Kumar Sah +2 more
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Transinformation for active object recognition
Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271), 2002This article develops an analogy between object recognition and the transmission of information through a channel based on the statistical representation of the appearances of 3D objects. This analogy provides a means to quantitatively evaluate the contribution of individual receptive field vectors, and to predict the performance of the object ...
Bernt Schiele, James L. Crowley
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Recognition of Activities of Daily Living
2012 IEEE 24th International Conference on Tools with Artificial Intelligence, 2012This paper presents a new method for human action recognition which exploits advantages of both trajectory and space-time based approaches in order to identify action patterns in given sequences. Videos with both a static and moving camera can be tackled, where camera motion effects are overcome via motion compensation.
Konstantinos Avgerinakis +2 more
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Recognition of Continuous Activities
2002The recognition of continuous human activities performed with several limbs is still an open problem. We propose a novel approach for recognition of continuous activities, which considers the direction change between frames to track the motion of several limbs and uses a Bayesian network to recognize different activities.
Rocío Díaz de León +1 more
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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
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Active Sensing in Human Activity Recognition
2017This work studies the problem of reducing the energy consumption of wearable sensors in a Human Activity Recognition (HAR) system. A HAR system is implemented using Hidden Markov Models, where decisions over the acquisition of new data are made based on the entropy of the posterior distribution of the activities. This problem is intractable in general,
Alfredo Nazábal +1 more
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Recognition of Human Activities
2011Computer Vision is the estimation of the three dimensional shape and other properties of objects based on their two dimensional (projection) images through the use of computers and cameras. It had its beginning in the early 1960s. At the time, it was thought to be an easy problem with a solution probably possible over a summer.
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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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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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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.
openaire +1 more source