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Face recognition based on full convolutional neural network based on transfer learning model
2021
Computer Science and Information Systems
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Finally, the face features extracted by this method and the face features extracted from the convolutional neural network method are adapted to sketch faces through transfer learning, and the results of ...
Deep learning has achieved a great success in face recognition (FR), however, little work has been done to apply deep learning for face photo-sketch recognition. ...
is proposed, which can adaptively adjust the feature extraction scale according to feature sensitivity. (2) Establish a full convolutional neural network based on transfer learning model by analysing ...
doi:10.2298/csis200922028f
fatcat:ucccpeehzrevfp2p4wekuussxa
Optimal Approach for Image Recognition using Deep Convolutional Architecture
[article]
2019
arXiv
pre-print
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The article mainly focuses on the state-of-art deep learning models and various real world applications specific training methods. ...
recognition. ...
Patel Institute of Technology for providing us computer resources as and when needed for training and implementing models presented in this paper. ...
arXiv:1904.11187v1
fatcat:6mcql2glabgk3lxo2aj2f776de
The Application of a Hybrid Transfer Algorithm based on a Convolutional Neural Network Model and an Improved Convolution Restricted Boltzmann Machine Model in Facial Expression Recognition
2019
IEEE Access
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In order to improve the facial expression recognition ability in transfer learning, a hybrid transfer learning model based on an improved convolution restricted boltzmann machine (CRBM) model and a CNN ...
INDEX TERMS Facial expression recognition, convolutional neural network, convolution restricted Boltzmann machine, transfer learning. ...
THE TRANSFER LEARNING BASED ON DEEP CONVOLUTIONAL NEURAL NETWORK Under the traditional machine learning framework, the learning task is to learn a classification model based on the given sufficient training ...
doi:10.1109/access.2019.2961161
fatcat:4owkpkykkfca3f3mb5hl55mwou
Image Classification and Object Detection Algorithm Based on Convolutional Neural Network
2019
Science Insights
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At the same time, the generative adversarial network and capsule network based on the deep learning-based image classification extension model are also introduced; simulation experiments verify the image ...
advantages and disadvantages, time / space used in image classification based on convolutional neural networks are given. ...
(iv) Based on transfer learning and network structure improvements, convolutional neural networks have gradually become a general-purpose feature extraction and pattern recognition tool, and its application ...
doi:10.15354/si.19.re117
fatcat:r7xmvkx6qjfsdkyep4urmggz24
Deep Convolutional Neural Network-Based Approaches for Face Recognition
2019
Applied Sciences
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Deep learning, specifically the convolutional neural network (CNN), has recently made commendable progress in FR technology. ...
This paper investigates the performance of the pre-trained CNN with multi-class support vector machine (SVM) classifier and the performance of transfer learning using the AlexNet model to perform classification ...
Figure 9 .Figure 9 . 99 Transfer learning from AlexNet convolutional neural networks. Transfer learning from AlexNet convolutional neural networks.
Figure 10 . 10 Accuracy for CNN models. ...
doi:10.3390/app9204397
fatcat:otjlvzfjqfc57akbnmnb4xwcqe
Definition of Unique Objects by Convolutional Neural Networks using Transfer Learning
2020
International Journal of Advanced Computer Science and Applications
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The article provides a detailed analysis of existing solutions for face detection and automatic recognition of medical masks, method based on the use of convolutional neural networks was proposed. ...
It is shown that the use of transfer learning on scales, learned to work with faces, significantly accelerates learning and increases the accuracy of recognition. ...
by a light convolutional neural network trained using transfer learning on scales for face recognition. ...
doi:10.14569/ijacsa.2020.0111106
fatcat:gkh3zirowjcwtfyzgdjor7u2lu
Convolutional Neural Network Model in Machine Learning Methods and Computer Vision for Image Recognition: A Review
2018
Journal of Applied Sciences Research
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Based on twenty five journal that have been review, this paper focusing on the development trend of convolution neural network (CNNs) model due to various learning method in image recognition since 2000s ...
The objective of this paper is to review a few learning machine methods of convolutional neural network (CNNs) in image recognition. ...
to train the full neural net and cause problems in transfer learning [7] . ...
doi:10.22587/jasr.2018.14.6.5
fatcat:stw6qs54szbkbozd2yy3edch6y
REAL TIME AGE AND GENDER CLASSIFIER
2022
International Journal of Engineering Applied Sciences and Technology
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In the proposed method, a Deep Learning technique called Convolutional Neural Network (ConvNet / CNN) is employed to extract features. ...
Face photos of individuals were trained with convolutional neural networks in this study, and age and sex were accurately predicted with a high rate of success. ...
Sequential convolutional neural networks are developed to take advantage of the parallel computing capability of convolutional neural networks and the temporal sensitivity of convolutional neural networks ...
doi:10.33564/ijeast.2022.v07i01.047
fatcat:4pmahvglvbdvjckpinlnwetozi
Face Detection and Recognition Method Based on Improved Convolutional Neural Network
2021
North atlantic university union: International Journal of Circuits, Systems and Signal Processing
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with rapid development of deep learning technology, face recognition based on deep convolutional neural network becomes one of the main research methods. ...
based on convolutional neural network is proposed in this paper. ...
the rapid development of deep learning, face recognition technology especially based on deep convolutional neural network has become one of the mainstream research methods. ...
doi:10.46300/9106.2021.15.85
fatcat:rfqpj6lpkrcxpbo5opptn4zc6q
A Survey of Biometric Recognition Using Deep Learning
2020
EAI Endorsed Transactions on Energy Web
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The paper starts with biometric basics, transfer learning in deep biometrics, an overview of convolutional neural networks, and then survey work. ...
Further, some of the main challenges when utilizing these biometric recognition models and potential future avenues for research into this field are also addressed. ...
In recent times, deep learning techniques such as convolutional neural networks and transfer learning and image augmentation have been used extensively for biometric recognition. ...
doi:10.4108/eai.27-10-2020.166775
fatcat:aihqgrk6pvbxpa54umpemr4s7a
Enhancing Mouth-Based Emotion Recognition Using Transfer Learning
2020
Sensors
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This work concludes the first study on mouth-based emotion recognition while adopting a transfer learning approach. ...
Using transfer learning, we can use fewer training data than training a whole network from scratch, and thus more efficiently fine-tune the network with emotional data and improve the convolutional neural ...
Keywords: transfer learning; convolutional neural networks; emotion recognition
1. ...
doi:10.3390/s20185222
pmid:32933178
fatcat:udk2e2jxvvarjby4xycrsxoz24
Control The COVID-19 Pandemic: Face Mask Detection Using Transfer Learning
2020
2020 IEEE 2nd International Conference on Electronics, Control, Optimization and Computer Science (ICECOCS)
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In this work, we investigated using different deep Convolutional Neural Networks (CNN) to extract deep features from images of faces. ...
Despite the small dataset used (1376 images), we have obtained very satisfactory results for the detection of masks on the faces. ...
Description The proposed method to detect faces with the mask or without it is based on feature selection using pre-trained deep convolutional neural networks and classification using machine learning ...
doi:10.1109/icecocs50124.2020.9314511
fatcat:7phpgwrikjc3veso5gpalgau7u
Face Detection Algorithm Based on Double-Channel CNN with Occlusion Perceptron
2022
Computational Intelligence and Neuroscience
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Transfer learning algorithm is utilized to pretrain parameters of the convolution layer to reduce the overfitting problem caused by insufficient training data samples. ...
Aiming at the problem of low accuracy of face detection under complex occlusion conditions, a double-channel occlusion perceptron neural network model was proposed. ...
Facial features were extracted using the modified residual network based on the residual neural network. ...
doi:10.1155/2022/3705581
pmid:35126488
pmcid:PMC8816569
fatcat:4srwruzch5ephk5pxopz6724aa
Traffic Sign Recognition Based on CNN and Twin Support Vector Machine Hybrid Model
2021
Journal of Applied Mathematics and Physics
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With the progress of deep learning research, convolutional neural networks have become the most important method in feature extraction. ...
In order to solve the problem that the traditional convolutional neural network is prone to over-fitting for the classification of small samples, a CNN-TWSVM hybrid model was proposed by fusing the twin ...
Chen
Concluding Remarks Based on the idea of migration learning, this paper reconstructs the feature extraction model for traffic sign recognition based on the VGG16 network. ...
doi:10.4236/jamp.2021.912204
fatcat:mtnms3a6c5dyvinvbyihfwzebi
Guest editorial - Pattern recognition, optimization, neural computing and applications in smart city
2021
Computer Science and Information Systems
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The fourth article entitled" Face Recognition Based on Full Convolutional Neural Network Based on Transfer Learning Model", authors develop an adaptive scale feature extraction method based on convolutional ...
This research also adopts the transfer learning approach to construct the sketch face recognition model by using the training sample. ...
doi:10.2298/csis210400iiic
fatcat:tfxo3ctuengu5kfj5l7oac63am
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