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Design of a Wearable Smart sEMG Recorder Integrated Gradient Boosting Decision Tree based Hand Gesture Recognition

Wei Song, Anhe Wang, Yang Chen, Shuo Bai, Qingquan Han, Zhonghang Lin, Nan Yan, Deng Luo, Yiqiao Liao, Milin Zhang, Zhihua Wang, Xiang Xie
2019 IEEE Transactions on Biomedical Circuits and Systems  
This paper proposed a wearable smart sEMG recorder integrated gradient boosting decision tree (GBDT) based hand gesture recognition.  ...  A RF module is used for wireless communication. A hand gesture set including 12 gestures is designed for human-computer interaction.  ...  The GBDT Based Classification Algorithm Gradient Boosting Decision Tree (GBDT) is used in this work for classification due to its low complexity.  ... 
doi:10.1109/tbcas.2019.2953998 pmid:31751286 fatcat:mqgsg4akhzdxjiyyglmva66fdq

Real-Time, Embedded Scene Invariant Crowd Counting Using Scale-Normalized Histogram of Moving Gradients (HoMG)

Parthipan Siva, Mohammad Javad Shafiee, Michael Jamieson, Alexander Wong
2016 2016 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)  
A novel low-complexity, scale-normalized feature called Histogram of Moving Gradients (HoMG) is introduced for highly effective spatiotemporal representation of crowds within a video.  ...  This paper proposes a novel scene invariant crowd counting algorithm designed for high accuracy yet low computational complexity in order to facilitate widespread use in real-time embedded video analytics  ...  Specifically, the AdaBoost [12] algorithm is used to obtain 100 boosted weak classifiers, where each weak classifier is a decision tree [8] with three decision nodes.  ... 
doi:10.1109/cvprw.2016.115 dblp:conf/cvpr/SivaSJW16 fatcat:fj5d35ykibadvjs2vpxxiwhdte

Machine Learning at the Network Edge: A Survey [article]

M.G. Sarwar Murshed, Christopher Murphy, Daqing Hou, Nazar Khan, Ganesh Ananthanarayanan, Faraz Hussain
2021 arXiv   pre-print
A typical solution involves offloading data to external computing systems (such as cloud servers) for further processing but this worsens latency, leads to increased communication costs, and adds to privacy  ...  However, deploying machine learning models on such end-devices is nearly impossible.  ...  size of a CNN model by up to 90% Lin et al. [86] Deep gradient compression to reduce gradient up to 600 times maintaining accu- racy Gupta et. al [50] ProtoNN, an algorithmic technique for classification  ... 
arXiv:1908.00080v4 fatcat:mw4lwwvzf5gupjr6pgdgnabeuu

A Comprehensive Survey of Machine Learning Applied to Radar Signal Processing [article]

Ping Lang, Xiongjun Fu, Marco Martorella, Jian Dong, Rui Qin, Xianpeng Meng, Min Xie
2020 arXiv   pre-print
Traditional radar signal processing (RSP) methods have shown some limitations when meeting such requirements, particularly in matters of target classification.  ...  This paper then concludes with a series of open questions and proposed research directions, in order to indicate current gaps and potential future solutions and trends.  ...  XGBoost As an implementation of gradient tree boosting, XGBoost [54] , an end-to-end scalable tree boosting system, is widely used in data mining.  ... 
arXiv:2009.13702v1 fatcat:m6am73324zdwba736sn3vmph3i

Special issue on intelligent tools and techniques for signals, machines and automation

Smriti Srivastava, Hasmat Malik, Rajneesh Sharma
2018 Journal of Intelligent & Fuzzy Systems  
In [44] , a novel feature extraction technique for palmprint recognition is proposed using Oriented Gabor Gradients (OGG).  ...  In [34] , a novel squared pinball loss twin support vector regression model (SPTSVR) is proposed.  ... 
doi:10.3233/jifs-169773 fatcat:gjntjnlig5fabdbqlwsjpl2awm

An experimental evaluation of large scale GBDT systems

Fangeheng Fu, Jiawei Jiang, Yingxia Shao, Bin Cui
2019 Proceedings of the VLDB Endowment  
Gradient boosting decision tree (GBDT) is a widely-used machine learning algorithm in both data analytic competitions and real-world industrial applications.  ...  Based on the analysis, we further propose a novel distributed GBDT system named Vero, which adopts the unexplored composition of vertical partitioning and row-store and suits for many large-scale cases  ...  INTRODUCTION Gradient boosting decision tree (GBDT) [12] is an ensemble model which uses decision tree as weak learner and improves model quality with a boosting strategy [11, 38] .  ... 
doi:10.14778/3342263.3342273 fatcat:h3lo7wel25fp3niclkoi2mvrf4

Research on a Fast Human-Detection Algorithm for Unmanned Surveillance Area in Bulk Ports

Chao Mi, Xin He, Haiwei Liu, Youfang Huang, Weijian Mi
2014 Mathematical Problems in Engineering  
To speed up the detection process, the optimized histograms of oriented gradients (HOG) algorithm that can avoid the large number of double calculations of the original HOG and ignore insignificant features  ...  In this paper, a fast human-detection algorithm is proposed based on image processing.  ...  Acknowledgments The authors would like to thank Editor Hung-Yu Wei and anonymous referees for their helpful and very delicate comments.  ... 
doi:10.1155/2014/386764 fatcat:dvmkf3g6pjedrobl4om7r3u5r4

A survey on compact features for visual content analysis

Luca Baroffio, Alessandro E. C. Redondi, Marco Tagliasacchi, Stefano Tubaro
2016 APSIPA Transactions on Signal and Information Processing  
, content-based retrieval, and classification.  ...  In this survey, we present an overview of state-of-the-art methods for the extraction, encoding, and transmission of compact features for visual content analysis, thoroughly addressing each step of the  ...  CHoG models such descriptors as tree structures, and exploits tree coding algorithms to reduce the number of bits needed to encode each feature.  ... 
doi:10.1017/atsip.2016.13 fatcat:lokgfydqrrd6zcvgngcbloopbu

Machine Learning in Python: Main Developments and Technology Trends in Data Science, Machine Learning, and Artificial Intelligence

Sebastian Raschka, Joshua Patterson, Corey Nolet
2020 Information  
This survey offers insight into the field of machine learning with Python, taking a tour through important topics to identify some of the core hardware and software paradigms that have enabled it.  ...  Python continues to be the most preferred language for scientific computing, data science, and machine learning, boosting both performance and productivity by enabling the use of low-level libraries and  ...  Another time-consuming computation in gradient boosting algorithms is to evaluate different feature thresholds for splitting the nodes when constructing the decision trees [39] .  ... 
doi:10.3390/info11040193 fatcat:hetp7ngcpbbcpkhdcyowuiiwxe

ML-LGBM: A Machine Learning Model based on Light Gradient Boosting Machine for the Detection of Version Number Attacks in RPL-Based Networks

Musa Osman, Jingsha He, Fawaz Mahiuob Mohammed Mokbal, Nafei Zhu, Sirajuddin Qureshi
2021 IEEE Access  
algorithm used in all GBDT (Gradient Boosting Decision Tree) frameworks [27] .  ...  The main contributions of this paper can be summarized as follows: • A novel model is proposed using a light gradient boosting machine trained on a unique dataset with extreme parameter optimization characterized  ...  .: Preparation of Papers for IEEE TRANSACTIONS and JOURNALS SIRAJUDDIN QURESHI received his bache-lorŠs degree in Computer Sciences from Quaid-e-Awam University of Engineering, Science Technology, Pakistan  ... 
doi:10.1109/access.2021.3087175 fatcat:oerxro6ovfg6pgvvgszlvhqkby

IEEE Access Special Section Editorial: Mission-Critical Sensors and Sensor Networks (MC-SSN)

Qilian Liang, Tariq S. Durrani, Jinhwan Koh, Jing Liang, Yonghui Li, Xin Wang
2021 IEEE Access  
Algorithms are sought for fused and/or coherent cross-platform radio frequency (RF) sensing.  ...  New approaches and low-complexity algorithms are expected to enable MC-SSN to automatically manage and effect risk and uncertainty in a highly deceptive, mixed cooperative/adversarial, information-centric  ...  A novel framework called domain transfer multiple kernel boosting (DTMKB) is investigated in the article ''Domain transfer multiple kernel boosting for classification of EEG motor imagery signals,'' by  ... 
doi:10.1109/access.2021.3068830 fatcat:mcmdtikg2vfqvokgu7pnm6xofq

Human Face Detection Techniques: A Comprehensive Review and Future Research Directions

Md Khaled Hasan, Md. Shamim Ahsan, Abdullah-Al-Mamun, S. H. Shah Newaz, Gyu Myoung Lee
2021 Electronics  
We provide the strengths and limitations of these algorithms and a novel literature survey that includes their use besides face detection.  ...  Secondly, we include a comparative evaluation among different algorithms in each single method.  ...  LBP works robustly as a texture descriptor and was found to have significant performance boost when working with histogram of oriented gradients (HOG) [47] .  ... 
doi:10.3390/electronics10192354 fatcat:oy7adwj6cjefnm66cn5kxrybni

Nanosecond machine learning event classification with boosted decision trees in FPGA for high energy physics [article]

Tae Min Hong, Benjamin Carlson, Brandon Eubanks, Stephen Racz, Stephen Roche, Joerg Stelzer, Daniel Stumpp
2021 arXiv   pre-print
We present a novel implementation of classification using the machine learning / artificial intelligence method called boosted decision trees (BDT) on field programmable gate arrays (FPGA).  ...  Our intended user is an expert of custom electronics-based trigger systems in high energy physics experiments or anyone that needs decisions at the lowest latency values for real-time event classification  ...  Conclusions We presented a novel implementation of machine learning / artificial intelligence method of boosted decision trees in FPGA.  ... 
arXiv:2104.03408v2 fatcat:m2wncqq4fjarfomn5jliyoteyu

Trustworthy AI: A Computational Perspective [article]

Haochen Liu, Yiqi Wang, Wenqi Fan, Xiaorui Liu, Yaxin Li, Shaili Jain, Yunhao Liu, Anil K. Jain, Jiliang Tang
2021 arXiv   pre-print
In this survey, we present a comprehensive survey of trustworthy AI from a computational perspective, to help readers understand the latest technologies for achieving trustworthy AI.  ...  For each dimension, we review the recent related technologies according to a taxonomy and summarize their applications in real-world systems.  ...  The work [328] proposes a tree-enhanced embedding method that seamlessly combines embedding-based methods with decision tree-based approaches, where a gradient boosting decision trees (GBDT) and an easy-to-interpret  ... 
arXiv:2107.06641v3 fatcat:ymqaxvzsoncqrcosj5mxcvgsuy

Machine Learning in Python: Main developments and technology trends in data science, machine learning, and artificial intelligence [article]

Sebastian Raschka, Joshua Patterson, Corey Nolet
2020 arXiv   pre-print
This survey offers insight into the field of machine learning with Python, taking a tour through important topics to identify some of the core hardware and software paradigms that have enabled it.  ...  Python continues to be the most preferred language for scientific computing, data science, and machine learning, boosting both performance and productivity by enabling the use of low-level libraries and  ...  Acknowledgments: We would like to thank John Zedlewski, Dante Gama Dessavre, and Thejaswi Nanditale from the RAPIDS team at NVIDIA and Scott Sievert for helpful feedback on the manuscript.  ... 
arXiv:2002.04803v2 fatcat:lvbczmz7xvbyjhs65zubwluzb4
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