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[PDF] Top 20 Automatic Face and Hijab Segmentation Using Convolutional Network

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Automatic Face and Hijab Segmentation Using Convolutional Network

Automatic Face and Hijab Segmentation Using Convolutional Network

... Image segmentation is the process of partitioning an image into multiple segments (Regions), by assigning label to every pixel in an image where the pixels with the same label have common ...characteristics. ... See full document

6

Automatic Face Detection Using Color Based Segmentation and Morphological Operation

Automatic Face Detection Using Color Based Segmentation and Morphological Operation

... machines. Face detection is defined as to detect the human faces from their background in an image and exactly locate their position in an ...matching, face decomposition, support vector machine, pattern ... See full document

7

Human Face Recognition in Video using Convolutional Neural Network (CNN)

Human Face Recognition in Video using Convolutional Neural Network (CNN)

... high-quality face image and it is done through face recognition algorithm due to these approaches there is a huge increase in recognition accuracy, it reduces the computational ...human face ... See full document

7

Semi Automated Brain Tumor Segmentation and Detection from MRI

Semi Automated Brain Tumor Segmentation and Detection from MRI

... actual segmentation time is too difficult to achieve but in medical routine, computation time over a few minutes is not ...tumor segmentation methods is robustness. If an automatic ... See full document

7

Automatic Facial Expression Recognition using Convolutional Neural Network (CNN)

Automatic Facial Expression Recognition using Convolutional Neural Network (CNN)

... We trained and tested the model on the database from FER Kaggle. The data consists of 48x48 pixel grayscale images of faces. The faces have been automatically registered so that the face is more or less centered ... See full document

8

Aortic Valve Segmentation using Convolutional Neural Network with Skip Mechanism

Aortic Valve Segmentation using Convolutional Neural Network with Skip Mechanism

... complete automatic segmentation tech- nique where marginal space learning technique is used for pre- or post-operative planning ...model-based segmentation technique is ...valve segmentation ... See full document

5

Automatic Brain Tumor Segmentation by Deep Convolutional Networks and Graph Cuts

Automatic Brain Tumor Segmentation by Deep Convolutional Networks and Graph Cuts

... of convolutional layers and a non-linear activation function between each consecutive ...the network to only see small context, but computation cost is ... See full document

96

Face Authentication Using Efficient Deep Convolutional Neural Network

Face Authentication Using Efficient Deep Convolutional Neural Network

... Convolutional Neural Network (CNN) has been widely used in variety of applications. It achieves state-of-the-art for many challenge benchmarks. One of the most challenges that CNN achieves state-of-the-art ... See full document

6

Deep Convolution Neural Networks for Automatic Eyeglasses Removal

Deep Convolution Neural Networks for Automatic Eyeglasses Removal

... Resolution Convolutional Neural Network (SRCNN) proposed by Dong [6] shows the great potential of an end-to-end DCN in image super- ...the network directly learns an end-to-end mapping between low- ... See full document

8

Brain Tumour Segmentation and Classification using Convolutional Neural Network in MRI images

Brain Tumour Segmentation and Classification using Convolutional Neural Network in MRI images

... manual segmentation in a reasonable time, limiting the use of precise quantitative measurements in the clinical ...So, automatic and reliable segmentation methods are required; however, the large ... See full document

6

Automatic QRS complex detection using two-level convolutional neural network

Automatic QRS complex detection using two-level convolutional neural network

... attention-based automatic feature extraction sys- tem comprised of object-level 1-D CNN and part-level 1-D CNN is proposed, which is shown in ...different-level segmentation, the number of layers between ... See full document

17

Automatic Facial Expressions and Identification of different face reactions using Convolutional Neural Network

Automatic Facial Expressions and Identification of different face reactions using Convolutional Neural Network

... Neural Network. A Neural Network is simply a network of Neurons, where a Neuron is simply a mimic of bio neuron with input as pixel of the images, output as ... See full document

5

Image Segmentation Using Convolutional Neural Network

Image Segmentation Using Convolutional Neural Network

... of segmentation is to train the model with some hand-crafted features and then use the model on input data to classify the objects, whereas in this approach CNN automatically extracts features which are required ... See full document

9

Semantic Segmentation on Remotely Sensed Images Using an Enhanced Global Convolutional Network with Channel Attention and Domain Specific Transfer Learning

Semantic Segmentation on Remotely Sensed Images Using an Enhanced Global Convolutional Network with Channel Attention and Domain Specific Transfer Learning

... global convolutional network (GCN) is employed and enhanced by adding larger numbers of layers to better capture complex ...weights using other remotely sensed corpora whose resolutions can be ... See full document

21

Music Genre Classification using Machine Learning Algorithms: A Comparison

Music Genre Classification using Machine Learning Algorithms: A Comparison

... III. In Lu L. et al., (2002). Content analysis for audio classification and segmentation, they have presented their study of segmentation and classification of audio content analysis. Here an audio stream ... See full document

8

Robust Face Recognition Based on Convolutional Neural Network

Robust Face Recognition Based on Convolutional Neural Network

... The network model architecture includes 4 convolution layers, 4 maximum feature map activation functions, 4 maximum pooling layers and 2 fully connected ...proposed network model is a 144 × 144 grayscale ... See full document

6

Synergistic Face Detection and Pose Estimation with Energy-Based Models

Synergistic Face Detection and Pose Estimation with Energy-Based Models

... to face detection abound, including real-time methods (Viola and Jones, 2001), and approaches based on convolutional networks (Vaillant et ...or using a pose estimator to select the most appropriate ... See full document

19

Facial expression recognition by using modified convolutional neural network (mcnn) and modified gabor filter

Facial expression recognition by using modified convolutional neural network (mcnn) and modified gabor filter

... by using a modified Convolutional Neural Network ...of using MCNN with Modified Gabor was (93%-99%) accuracy rate with very less time for both multi and single face respectively We have ... See full document

8

Convolutional neural networks for brain tumour segmentation

Convolutional neural networks for brain tumour segmentation

... Other applications are in the sphere of treatment planning, particularly for radiotherapy and targeted chemotherapy. Assessment of the tumour microvascu- lature can be performed by fractal analysis which as- sesses ... See full document

9

Fully automated, real-time 3D ultrasound segmentation to estimate first trimester placental volume using deep learning

Fully automated, real-time 3D ultrasound segmentation to estimate first trimester placental volume using deep learning

... assessed using 1-way ...assessed using histograms and probability plots), and differences in gestational age were corrected for by expressing log PlVol as MoMs of the AGA ...visualized using 3D ... See full document

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