[8] Convolutional neural network, From Wikipedia, the free encyclopedia, https://en.wikipedia.org/wiki/Convolutional_neural_network, last edited on 12 June 2020.
[88] Created by Yangqing Jia, Lead Developer Evan Shelhamer, ‘Deep learning framework by BAIR’, http://caffe.berkeleyvision.org/, last accessed on 15 June 2020.
[85] Application programming interface, From Wikipedia, https://en.wikipedia.org/wiki/Application_programming_interface, last edited on 9 June 2020.
[84] Sobel Operator, From Wikipedia, the free encyclopedia, https://en.wikipedia.org/wiki/Sobel_operator, last edited on 3 June 2020.
[82] scikit-image development team homepage, ‘scikit-image’, https://scikit-image.org/docs/dev/install.html, last accessed on 15 June 2020.
[80] Python Software Foundation, https://www.python.org/, last accessed on 15 June 2020.
[79] Project Jupyter, ‘Jupyter Notebook’, https://jupyter.org/, last updated on 16 May 2020.
[77] Labeled Faces in the Wild homepage, http://vis-www.cs.umass.edu/lfw/, last accessed on 10 June 2020.
[75] Region of interest, From Wikipedia, the free encyclopedia, https://en.wikipedia.org/wiki/Region_of_interest, last edited on 25 January 2020.
[73] OpenCV 2.4.13.7 documentation, ‘Affine Transformations’, https://docs.opencv.org/2.4/doc/tutorials/imgproc/imgtrans/warp_affine/w arp_affine.html, last accessed on 14 June 2020.
[70] OpenFace, https://cmusatyalab.github.io/openface, last accessed on 2 March 2020.
[66] Jaccard index, From Wikipedia, the free encyclopedia, https://en.wikipedia.org/wiki/Jaccard_index, last edited on 7 June 2020.
[62] Ground truth, From Wikipedia, the free encyclopedia, https://en.wikipedia.org/wiki/Ground_truth, last edited on 13 May 2020.
[61]Confusion matrix, From Wikipedia, the free encyclopedia, https://en.wikipedia.org/wiki/Confusion_matrix, last edited on 9 June 2020.
[59] Frame rate, From Wikipedia, the free encyclopedia, https://en.wikipedia.org/wiki/Frame_rate, last edited on 16 May 2020.
[55] Satya Mallick homepage, ‘Learn OpenCV’, https://www.learnopencv.com/histogram-of-oriented-gradients/, last edited on 6 December 2016.
https : //www.learnopencv.com/histogram-of-oriented-gradients/ , last edited on 6
[54] N. Dalal and B. Triggs, "Histograms of oriented gradients for human detection," CVPR 2005, IEEE Computer Society Conference, Vol. 1, pp. 886–893, 2015.
[50] Difference of Gaussians, From Wikipedia, the free encyclopedia, https://en.wikipedia.org/wiki/Difference_of_Gaussians, last edited on 15 May 2020.
[46] Dilution (neural networks), From Wikipedia, the free encyclopedia, https://en.wikipedia.org/wiki/Dilution_(neural_networks), last edited on 12 June 2020.
[43] Visual Geometry Group, https://www.robots.ox.ac.uk/~vgg/, last accessed on 15 June 2020.
[3] Face Detection & Recognition, https://facedetection.com, last edited on 2020.
[38] Sigmoid function, From Wikipedia, the free encyclopedia, https://en.wikipedia.org/wiki/Sigmoid_function, last edited on 10 June 2020.
[37] Diederik P. Kingma, Jimmy Lei Ba, "Adam: A Method for Stochastic Optimization", https://arxiv.org/pdf/1412.6980.pdf, 2014.
[34] Affine transformation, From Wikipedia, the free encyclopedia, https://en.wikipedia.org/wiki/Affine_transformation, last edited on 17 May 2020.
[32] Andrej Karpathy's blog, ‘Hacker's guide to Neural Networks’, http://karpathy.github.io/neuralnets/, last accessed on 16 June 2020.
[30] Stochastic gradient descent, From Wikipedia, the free encyclopedia, https://en.wikipedia.org/wiki/Stochastic_gradient_descent, last edited on 7 June 2020.
[27] Gradient descent, From Wikipedia, the free encyclopedia, https://en.wikipedia.org/wiki/Gradient_descent, last edited on 11 June 2020.
[26] Random search, From Wikipedia, the free encyclopedia, https://en.wikipedia.org/wiki/Random_search, last edited on 19 April 2020.
[25] Dankmar Böhning, "Multinomial logistic regression algorithm", Annals of the Institute of Statistical Mathematics, Vol. 44, pp. 197– 200, 1992.
[22] Training, validation, and test sets, From Wikipedia, https://en.wikipedia.org/wiki/Training,_validation,_and_test_sets, last edited on 2 June 2020.
[21] Hinge loss, From Wikipedia, the free encyclopedia, https://en.wikipedia.org/wiki/Hinge_loss, last edited on 9 April 2020.
[20] Support vector machine, From Wikipedia, the free encyclopedia, https://en.wikipedia.org/wiki/Support_vector_machine, last edited on 18 May 2020.
[1] Facial recognition system, From Wikipedia, the free encyclopedia, https://en.wikipedia.org/wiki/Facial_recognition_system, last edited on 15 May 2020.
[18] Christopher J. C. Burges, "A Tutorial on Support Vector Machines for Pattern Recognition", Data Mining and Knowledge Discovery, Vol. 2, pp. 121-167, 1998.
[16] CS231n: Stanford University, ‘CS231n: Convolutional Neural Networks for visual recognition’, http://cs231n.stanford.edu/, last accessed on 15 June 2020.
[13] Adam Geitgey’s FACE_RECOGNITION Library homepage, https://github.com/ageitgey/face_recognition, last accessed on 2 March 2020.
[12] Dlib C++ Library homepage, http://dlib.net/, last modified on 6 June 2020.
Understanding the difficulty training deep feedforward neural networks . , In Proceedings of the International Conference on Artificial Intelligence and Statistics ( AISTATS2010 )
[2010]
Understanding Learning Rates and How It Improves Performance in Deep Learning
[2018]
Unconstrained Minimization , Convex Optimization
pp . 457–520[2004]
Ssd : Single shot multibox detector
Volume 9905 LNCS Vol . 9905 , pp . 21–37[2016]
SSD object detection : Single Shot MultiBox Detector for real-time processing ’
Rapid object detection using a boostedCascade of simple features
[2001]
Permitted and Forbidden Sets in Symmetric Threshold-Linear Networks
[2001]
Openface : A general-purpose face recognition library with mobile applications
[2016]
One Millisecond Face Alignment with an Ensemble of Regression Trees
pp . 1867-1874[2014]
Neocognitron : A self-organizing neural network model For a mechanism of pattern recognition unaffected by shift in position .
36 , pp . 193-202 ,[1980]
Machine Learning is Fun ! Part 4 : Modern Face Recognition with Deep Learning ’
ImagenetClassification with deepConvolutional neural networks
pp . 1106-1114[2012]
Gradient-Based Learning Applied to Document Recognition
Vol . 86 , pp . 2278-2324[1998]
Going Deeper with Convolutions
[2015]
Generating Anchor boxes for Yolo-like network for vehicle detection using KITTI dataset .
7 , last edited on 10
From Wikipedia , the free encyclopedia
Feature Engineering for Images : A Valuable Introduction to the HOG Feature Descriptor ’
Faster r-cnn : Towards real-time object detection with region proposal networks
28 ,[2015]
Fast R-CNN
pp . 1440-1448[2015]
Facenet : A unified embedding for face recognition and clustering
[2015]
Face detection vs. Face Recognition ’
https : //www.facefirst.com/blog/face-detection-vs-face-recognition , last edited on
Face Recognition using OpenFace ’
E. Labeled faces in the wild : A database for studying face recognition in unconstrained environments , Technical report 07–49
[2007]
Dropout : a simple way to prevent neural networks from overfitting.
[2014]
Dlib-ml : A Machine Learning Toolkit
10 , pp . 1755-1758[2009]
Distinctive image features from scale-invariant keypoints
[2004]
Delving deep into rectifiers : Surpassing human-level performance on imagenet classification
[2015]
BetterToday homepage
‘mAP(mean average precision)의 개념’, https://better-today.tistory.com/3, last edited on 16 August[2017]
Batch Normalization : Accelerating Deep Network Training by Reducing Internal Covariate Shift
arXiv:1502.03167[2015]
Applications of support vector machines in chemistry
Vol . 23 , pp . 291-400[2007]
Adaptive Subgradient Methods for Online Learning and Stochastic Optimization
[2011]
6.5 Back-Propagation and Other Differentiation Algorithms .
pp . 200–220[2016]
'
물체 검출과 얼굴 인식을 위한 딥러닝 기법 = Deep learning method for object detection and human face recognition'
의 유사주제(
) 논문