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Performance metrics for activity recognition
2011
ACM Transactions on Intelligent Systems and Technology
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In this article, we introduce and evaluate a comprehensive set of performance metrics and visualisations for continuous activity recognition (AR). ...
Building on an earlier initial work on the topic, we develop a frame-based visualisation and corresponding set of class-skew invariant metrics for the one class versus all evaluation. ...
Judging by Performance Metrics for Activity Recognition
•
6:15
Note that it is permissible for r x to overlap with both part of e 1 and part of e 2 (and possibly more events). ...
doi:10.1145/1889681.1889687
fatcat:rya4nlcaureb7ii7kc7i2rxkpi
Exploring Techniques for Vision Based Human Activity Recognition: Methods, Systems, and Evaluation
2013
Sensors
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In this paper, we provide a comprehensive survey of the recent development of the techniques, including methods, systems, and quantitative evaluation of the performance of human activity recognition. ...
In image and video analysis, human activity recognition is an important research direction. ...
Evaluation Metrics for Activity Recognition Effectively evaluating the performance of methods and systems for activity recognition in videos or image sequences is important for the improvement of surveillance ...
doi:10.3390/s130201635
pmid:23353144
pmcid:PMC3649413
fatcat:pssdgo3rpbak7czx6zn47rvjla
Introduction to the special issue on intelligent systems for activity recognition
2011
ACM Transactions on Intelligent Systems and Technology
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Jamie Ward, Paul Lukowicz, and Hans Gellersen propose a set of new performance metrics for activity recognition in "Performance Metrics for Activity Recognition." ...
-Evaluation metric for activity recognition is a fundamental research issue that is worth studying. ...
doi:10.1145/1889681.1889682
fatcat:y7vxivvkfrhxnf7e4alq4adcsi
A statistical framework to evaluate virtual screening
2009
BMC Bioinformatics
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Although many other metrics, such as RIE, BEDROC, and pROC that emphasize "early recognition" have been proposed, there are no rigorous statistical guidelines for determining the thresholds and performing ...
Also no comparisons have been made between these metrics under a statistical framework to better understand their performances. ...
Ball for his suggestive comments and the St Jude Hartwell Center for providing computational assistance. ...
doi:10.1186/1471-2105-10-225
pmid:19619306
pmcid:PMC2722655
fatcat:zaxfqbfg6rh57lmyfiypznq6ui
Comparative Performance Analysis of Neural Networks Architectures on H2O Platform for Various Activation Functions
[article]
2017
arXiv
pre-print
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Other Versions
2017
2017 IEEE International Young Scientists Forum on Applied Physics and Engineering (YSF)
unpublished
doi:10.1109/ysf.2017.8126654 fatcat:x3vcuojhjzagnbpalefu5f2mte
doi:10.1109/ysf.2017.8126654 fatcat:x3vcuojhjzagnbpalefu5f2mte
In this paper, we present the results of testing neural networks architectures on H2O platform for various activation functions, stopping metrics, and other parameters of machine learning algorithm. ...
This result can have crucial influence for opitmization of available and new machine learning methods, especially for image recognition problems. ...
We found that generalization performance has very strong dependence on activation function and very slight dependence on stopping metric. ...
arXiv:1707.04940v1
fatcat:fohdbbdsbjg7fba2kz4aszxtdi
Human Health Activity Recognition Algorithm in Wireless Sensor Networks Based on Metric Learning
2022
Computational Intelligence and Neuroscience
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Based on the small sample problem and the linear indivisibility of real samples encountered in metric learning, this paper proposes a human activity recognition algorithm for wireless sensor networks. ...
Human activity recognition algorithm for wireless sensor networks uses human activity recognition algorithm to solve the singularity of intraclass divergence matrix, so as to reduce the impact of small ...
Human Activity Recognition Algorithm for Wireless Sensor Networks Based on Metric Learning. Metric learning can be traced back to some early research. ...
doi:10.1155/2022/4204644
pmid:35479601
pmcid:PMC9038378
fatcat:e5bjjij5bbfnti57pf4bjb4baa
Robust Human Activity Recognition based on Deep Metric Learning
2019
Proceedings of the 16th International Conference on Informatics in Control, Automation and Robotics
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In this work we investigate the use of Deep Metric Learning in the domain of activity recognition. ...
We use a deep Triplet Network to generate fixed-length descriptors from activity samples for purposes of classification. ...
In this work we apply deep metric learning specifically to activity recognition data. ...
doi:10.5220/0007916806560663
dblp:conf/icinco/Abdu-AguyeG19a
fatcat:6hp3p5t3izfrbbxqfmad6npbie
Selective Sampling Strategies to Conserve Power in Context Aware Devices
2007
2007 11th IEEE International Symposium on Wearable Computers
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These metrics include: accuracy as the percentage of time between samples that sampled activity matches true activity, average latency of detecting a change in activity, the percentage of missed activities ...
We analyze the use of selective sampling strategies to aid in power conservation in sensor platforms for context-aware systems. ...
Acknowledgments Additionally, we would like to thank Uwe Maurer and Anthony Rowe for eWatch support. ...
doi:10.1109/iswc.2007.4373783
dblp:conf/iswc/FrenchSSD07
fatcat:khr6iegf3fak3ib4qpexd4wqeq
Dendritic morphology predicts pattern recognition performance in multi-compartmental model neurons with and without active conductances
2014
Journal of Computational Neuroscience
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All relationships found for passive neuron models also hold, even in more accentuated form, for neurons with active membranes. ...
In this paper we examine how a neuron's dendritic morphology can affect its pattern recognition performance. ...
To study the effect of active conductances on the relationship between dendritic morphology and pattern recognition performance, and to compare this relationship for active and passive model neurons with ...
doi:10.1007/s10827-014-0537-1
pmid:25380637
pmcid:PMC4350002
fatcat:czggp6kxj5b2hlmkukoutfzb2y
Towards a Clustering Guided Hierarchical Framework for Sensor-Based Activity Recognition
2021
Sensors
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Accordingly, how to measure the relationships among activities and construct an activity recognizer for better distinguishing the confusing activities remains critical. ...
Afterwards, we design a hierarchical activity recognition framework under the guidance of the confusion relationships to reduce the recognition errors between similar activities. ...
For performance metrics, accuracy, precision, recall, and F1 are used to assess the power of an activity recognizer. F1, the harmonic mean of precision and recall. ...
doi:10.3390/s21216962
pmid:34770269
pmcid:PMC8587318
fatcat:zpmd2qilmrg5jmrmvd5sixeep4
Co-recognition of Human Activity and Sensor Location via Compressed Sensing in Wearable Body Sensor Networks
2012
2012 Ninth International Conference on Wearable and Implantable Body Sensor Networks
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Existing research work either extracts location information from certain activity signals or takes advantage of the sensor location information as a priori to achieve better activity recognition performance ...
To validate the effectiveness of our approach, we did a pilot study for the task of recognizing 14 human activities and 7 on body-locations. ...
Hassan Ghasemzadeh of Wireless Health Institute in UCLA for the experimental dataset and discussion. ...
doi:10.1109/bsn.2012.14
dblp:conf/bsn/XuZSS12
fatcat:4vbj5kai2fe4dgadsqueqc5rii
An online method for estimating grazing and rumination bouts using acoustic signals in grazing cattle
2020
Computers and Electronics in Agriculture
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In this study, an online algorithm called bottom-up foraging activity recognizer (BUFAR) is proposed. The method is based on the recognition of jaw movements ...
However, there is no online acoustic method for the recognition of rumination and grazing bouts that can be implemented in a low-cost device. ...
The recognition of grazing and rumination bouts was evaluated with specific metrics for activity recognition. ...
doi:10.1016/j.compag.2020.105443
fatcat:xv3n4kky5rfrlfqtpupmaz66wa
The effect of dendritic morphology on pattern recognition in the presence of active conductances
2011
BMC Neuroscience
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We also investigated suitable ranges for model parameters such as dendritic compartment length and synaptic strength, among other Figure 1 Pattern recognition performance in active and passive models. ...
In the present study, we analyse how the dendritic morphology affects the pattern recognition performance in active models. ...
for active as compared to passive dendrites. ...
doi:10.1186/1471-2202-12-s1-p315
fatcat:wdcrrsd4pzhipmns5spzz4cvfu
Privacy Enhanced Multimodal Neural Representations for Emotion Recognition
2020
PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE
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In this work, we show how multimodal representations trained for a primary task, here emotion recognition, can unintentionally leak demographic information, which could override a selected opt-out option ...
emotion recognition. ...
We define performance for emotion recognition as the ability of the model to correctly classify either activation or valence into 3 categories: low, medium, and high. ...
doi:10.1609/aaai.v34i05.6307
fatcat:r6iazmlvjzdavopnx6nlhoc6uq
A novel smartphone-based activity recognition modeling method for tracked equipment in forest operations
2022
PLoS ONE
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, and delay) were classified with the performance metrics for individual elements of the best model (50 Hz, 10 second window, 90% window overlap) falling within the following ranges: area under the curve ...
This study is the first example of developing a smartphone-based activity recognition model for ground-based forest equipment. ...
Acknowledgments The authors would like to thank University of Idaho Experimental Forest undergraduate forestry staff who planned and administered these stand treatments and Triple B Excavation for allowing ...
doi:10.1371/journal.pone.0266568
pmid:35385537
pmcid:PMC8985955
fatcat:4qwu5gtapjhjxcydamzinlycca
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