Deep convolution neural network (DCNN)
Research on image classification model based on deep convolution neural network
... Deep convolution neural networks are used to identify scaling, translation, and other forms of distortion-invari- ant ...convolutional network uses feature detection layer to learn from ...
11
A Step Forward to Revolutionise IntrusionDetection System Using Deep Convolution Neural Network
... of deep learning was introduced, a new platform has opened for the ...the network traffic events as time series of TCP/IP ...challenging. Deep Auto-encoder is an unsupervised learning tool, which was ...
13
An Novel Framework For Content Based Image Retrieval With Quality Assessment System using Optimal Deep Convolution Neural Network
... Abstract: Content based image retrieval (CBIR) models become popular for retrieving images connected to the query image (QI) from massive dataset. Feature extraction process in CBIR plays a vital role as it affects the ...
11
Deep Convolution Neural Networks for Automatic Eyeglasses Removal
... on deep convolutional neural network (DCNN). Our DCNN removes the eyeglasses region and reconstructs this region by selecting one piece from the facial ...a DCNN to learn the ...
8
Deep Learning Pre-Trained Architecture Of Alex Net And Googlenet For DICOM Image Classification
... of Deep learning has found many applications in various fields not limited to Computer Vision, Natural Language Processing, Image Processing and Automatic Speech ...classification, Deep Convolutional ...
7
Deep Belief Networks Using Convolution Neural Networks Algorithm
... problems considered by Hinton & Salakhutdinov (2006) (abbr. H&S). We adopt precisely the same model architectures, datasets, loss functions and training/test partitions that they did, so as to ensure that our ...
8
Research on Face Detection based on Deep Learning
... the deep learning method and the convolution neural network model for face detection, which can be better for facial landmark ...Alexnet convolution neural ...
7
Nikolov Radivchev at SemEval 2019 Task 6: Offensive Tweet Classification with BERT and Ensembles
... Approaches to detecting hate speech on Twit- ter using convolutional neural networks and convolution-GRU based deep neural network are discussed in Gambäck and Sikdar, 2017 and Zhang et[r] ...
5
Vehicle Brand Recognition by Deep Neural Networks
... At present, object detection algorithms based on deep learning are mainly divided into two categories. One is the two-stage detection algorithm, which divides the detection problem into two stages. First, ...
6
Fine Grained Classification of Product Images Based on Convolutional Neural Networks
... a deep convolutional neural network that the convolution kernel size and the order of network connection are based on the high efficiency of the filter capacity and cover- ...of ...
19
A Deep Learning Approach For Brain Tumor Segmentation Using Convolution Neural Network
... Medical image processing is one of the topics leading the research. Many researches contributed their algorithms and techniques towards the segmentation of the medical image. Bandhyophyav and Paul [10] put forward a ...
6
Fake News Detection using Convolution Neural Network in Deep Learning
... Internet and Social media provides facilities to the users to access news information and this can be a double-edged sword with both pros and cons, every day huge massive amount of news is generated and manipulated in ...
15
¬¬¬Facial Emotion Recognition - A Gift For The Visionless
... and deep learning with artificial intelligence plays a pivotal role in these ...individual. Deep learning adheres to deep neural network models for different tasks from image processing ...
6
Rumor Classification Model Based on Deep Convolutional Neural Networks
... Convolutional Neural Network (CNN) is developed on the basis of the standard neural network, are as for neural network on the overall architecture is very similar, both by the ...
5
Scalable flood level trend monitoring with surveillance cameras using a deep convolutional neural network
... following network structure ...the network takes color images with a resolution of 512 pixels × 512 ...The network is com- posed of five encoding and five decoding blocks, each block consisting of ...
14
A Novel Method for Remotely Sensed Hyperspectral Image Classification Based on Convolutional Neural Network
... Convolutional Neural Networks (CNN) are gaining attention due to their capability to automatically discover relevant relative features in image classification ...Connected Network (FCN) hidden layers to ...
10
Image Description Using Deep Neural Network
... uses deep learning Convolution Neural Network and Recurrent Neural Network for generating description of ...result, Neural Network shows better result for ...
6
Emotion Recognition And Classification Using Eeg: A Review
... recurrent neural networks (RNN) were engaged on spatial orientations of signal, to travel across the two ...find deep features of EEG, keeping spatial dependency ...sub- network was implemented to ...
10
Integrated Animal Recognition and Detection Using Deep Convolutional Neural Network
... There are several advantages of using a quadtree to hierarchically represent the image data for convolutional neural networks. First, the quadtree can be efficiently computed once for each image, and its structure ...
7
Deep Learning Based Crime Investigation Framework
... Abstract:— Deep learning has emerged as the best way to infer knowledge from data with more meaning and ...of Deep Neural Networks in a variety of domains have made it an important area of ...make ...
5