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Facial Recognition with Face Regions by Machine Learning: Review

Vijaya Ravindra Wankhade, Prof. Krutika K Chhajed
2022 International Journal for Research in Applied Science and Engineering Technology  
detected by the IntraFace algorithm.  ...  Keywords: Facial expression recognition, SVM, feature descriptor, Facial decomposition, facial landmarks  ...  When planning associate automatic face expression recognition system, three issues are considered: face detection, facial feature extraction, and classification of expressions.  ... 
doi:10.22214/ijraset.2022.40644 fatcat:36lcyump3jh5jax6nd4mo6sany


Suresh K, Chellappan C
2017 International Research Journal of Pharmacy  
This paper proposes a novel framework for human mind recognition in real time mode. We used Viola-Jones face detection technique to detect the faces in the image.  ...  These active image sequences are filtered with low pass Gaussian mask to remove the noises.  ...  Jeffery Cohn for CK+ Database usage, and Prof. Dr. Michael J. Lyons for JAFFE database usage.  ... 
doi:10.7897/2230-8407.0811237 fatcat:a6z5uipbyrb45m76ynkwffjqae

Semantic Recognition of Signed Language Using Convolutional Neural Network

Lanzhong Wang
2017 Innovative Computing Information and Control Express Letters, Part B: Applications  
Third, the detected hand image patch is applied with a state-of-the-art landmark localization algorithm using Markov Random Fields and Active Shape Models.  ...  In this paper we study the hand gesture recognition problem for signed language. The complex background in real world application is a major challenge for hand region segmentation.  ...  The final signed language recognition result is shown in Table 2 . Notice that Method-I uses human annotation and it is not fully automatic.  ... 
doi:10.24507/icicelb.08.08.1211 fatcat:4tjgcsthgbeuxb3rwg4nnii63u

Learning with noisy supervision for Spoken Language Understanding

Christian Raymond, Giuseppe Riccardi
2008 Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing  
Active learning has been successfully applied to automatic speech recognition and utterance classification.  ...  The strategies detect likely erroneous examples and improve significantly the SLU performance for a given labeling cost.  ...  Acknowledgment We would like to thank Yulan He for sharing with us her ATIS annotated dataset.  ... 
doi:10.1109/icassp.2008.4518778 dblp:conf/icassp/RaymondR08 fatcat:wfijxxw6kzgznmcmk6xyvuykny

Perceived Gender Classification from Face Images

Hlaing Htake Khaung Tin
2012 International Journal of Modern Education and Computer Science  
The proposed system produced very promising recognition rates for our applications with same set of features and classifiers. The system is also realtime capable and automatic.  ...  There are many methods have been proposed in the literature for the facial features and gender classification.  ...  Human facial image processing has been an active and interesting research issue for years.  ... 
doi:10.5815/ijmecs.2012.01.02 fatcat:spz3xruadfb5rhhwmakdkgen2q

Learning to Recognize Faces by Successive Meetings

M. Castrillón-Santana, O. Déniz-Suárez, J. Lorenzo-Navarro, M. Hernández-Tejera
2006 Journal of Multimedia  
For revisitors, the accumulated error rate decreases in both cases, reaching around 50% if no verification is included.  ...  In this paper we focus on the face recognition problem.  ...  His research interests include facial detection and recognition, and computer vision for human computer interaction.  ... 
doi:10.4304/jmm.1.7.1-8 fatcat:ui4xsq7t5vanhp4ac3a5i22bli

2020 Index IEEE/ACM Transactions on Audio, Speech, and Language Processing Vol. 28

2020 IEEE/ACM Transactions on Audio Speech and Language Processing  
., +, TASLP 2020 798-812 Error Correction in Pitch Detection Using a Deep Learning Based Classification.  ...  ., +, TASLP 2020 1303-1314 Error Correction in Pitch Detection Using a Deep Learning Based Classification.  ...  T Target tracking Multi-Hypothesis Square-Root Cubature Kalman Particle Filter for Speaker Tracking in Noisy and Reverberant Environments. Zhang, Q., +, TASLP 2020 1183 -1197  ... 
doi:10.1109/taslp.2021.3055391 fatcat:7vmstynfqvaprgz6qy3ekinkt4

Automatic Association of Chats and Video Tracks for Activity Learning and Recognition in Aerial Video Surveillance

Riad Hammoud, Cem Sahin, Erik Blasch, Bradley Rhodes, Tao Wang
2014 Sensors  
VIVA and MINER examples are demonstrated for wide aerial/overhead imagery over common data sets affording an improvement in tracking from video data alone, leading to 84% detection with modest misdetection  ...  MINER includes: (1) a fusion of graphical track and text data using probabilistic methods; (2) an activity pattern learning framework to support querying an index of activities of interest (AOIs) and targets  ...  The authors would like to thank Adnan Bubalo (AFRL), Robert Biehl, Brad Galego, Helen Webb and Michael Schneider (BAE Systems) for their support.  ... 
doi:10.3390/s141019843 pmid:25340453 pmcid:PMC4239870 fatcat:ony3ylej4nhzxbnap2zide3kwi

RADAR 2019 Author Index

2019 2019 International Radar Conference (RADAR)  
Syed Aziz Human Activity Recognition : Preliminary Results for Dataset Portability using FMCW Radar submission_167 SHAN Tao Automatic Arm Motion Recognition Using Radar for Smart Home Technologies  ...  Radar and Video Multimodal Learning for Human Activity Classification submission_139 DE WIT Jacco J.M.  ... 
doi:10.1109/radar41533.2019.9078992 fatcat:qgj7mi5yrfc7ti5qz6he5n4xvm

On the Use of Brain Decoded Signals for Online User Adaptive Gesture Recognition Systems [chapter]

Kilian Förster, Andrea Biasiucci, Ricardo Chavarriaga, José del R. Millán, Daniel Roggen, Gerhard Tröster
2010 Lecture Notes in Computer Science  
This should be automatic, transparent, and unconscious. We capitalize on advances in electroencephalography (EEG) signal processing that allow for error related potentials (ErrP) recognition.  ...  Thus the gesture recognition system becomes self-aware of its performance, and can self-improve through re-occurring detection of ErrP signals.  ...  i.e. the probability of the state (error or correct) knowing the observations (EEG activity).  ... 
doi:10.1007/978-3-642-12654-3_25 fatcat:372nns7zd5d3hjihpb66f2cxri

A Novel Multimodal Data Analytic Scheme for Human Activity Recognition [chapter]

Girija Chetty, Mohammad Yamin
2014 IFIP Advances in Information and Communication Technology  
classification and detection approaches for remote activity recognition for novel, eHealth application scenarios, such as monitoring and tracking of elderly, disabled and those with special needs.  ...  In this article, we propose a novel multimodal data analytics scheme for human activity recognition.  ...  automatic processing technique can result in robust activity recognition.  ... 
doi:10.1007/978-3-642-55355-4_47 fatcat:2w5mr77qcja3vkcnj454gtnknu

Automatic speech recognition and its application to information extraction

Sadaoki Furui
1999 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics -  
Applications of speech recognition technology can be classified into two main areas, dictation and human-computer dialogue systems. •  ...  This paper describes recent progress and the author's perspectives of speech recognition technology.  ...  The newscasts are automatically segmented and an index is created for each of the segments by means of automatic speech recognition.  ... 
doi:10.3115/1034678.1034680 dblp:conf/acl/Furu99 fatcat:ovnd2rgnwrf5ddhnnshwtppxje

Design and Evaluation of a Self-Correcting Gesture Interface based on Error Potentials from EEG

Felix Putze, Christoph Amma, Tanja Schultz
2015 Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems - CHI '15  
The automatic detection of error potentials in electroencephalographic data recorded from a user allows the system to detect such states of confusion and automatically bring the interaction back on track  ...  We show that selfcorrection significantly improves gesture recognition accuracy at lower costs and with higher acceptance than manual correction.  ...  As we also want to compare the automatic correction strategies with user-triggered correction, we define the MANUAL strategy that requires the user to actively report a system error.  ... 
doi:10.1145/2702123.2702184 dblp:conf/chi/PutzeAS15 fatcat:tzthdbow3jdd3dht3fggxvejbq

Brief review on gender classification techniques

et al. Noor
2017 International Journal of Advanced and Applied Sciences  
The main primary contributions are comparable and comprehensive results for the classification of gender methods and combined with real-time automatic detection of face.  ...  We carried a study of comparison for the gender classification methods for finding their pros and cons.  ...  He used a network architecture for both gender and age classification. For human face parsing and pose estimation key point CNN was used.  ... 
doi:10.21833/ijaas.2017.07.013 fatcat:y6slq72w3nfw3kk63siycdjrjy

Response error correction-a demonstration of improved human-machine performance using real-time eeg monitoring

L.C. Parra, C.D. Spence, A.D. Gerson, P. Sajda
2003 IEEE transactions on neural systems and rehabilitation engineering  
We describe a brain-computer interface (BCI) system, which uses a set of adaptive linear preprocessing and classification algorithms for single-trial detection of error related negativity (ERN).  ...  Our initial results show average improvement in subject performance of 21% when errors are automatically corrected via the BCI.  ...  CORRECTING ERRORS USING THE DETECTED ERN Using the detected ERN to correct human response errors requires choosing a threshold on the output of the linear classifier so as to minimize the number of errors  ... 
doi:10.1109/tnsre.2003.814446 pmid:12899266 fatcat:g3q7l4poozb3bdg23atksg25ym
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