[PDF] Top 20 An Analysis of Convolutional Neural Networks for Image Recognition
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An Analysis of Convolutional Neural Networks for Image Recognition
... lower recognition rate or more time- ...original image as the input of network directly, avoiding the manual extraction of features that would lead to the accumulation of ... See full document
5
Deep Kernel based Convolutional Neural Networks for Image Recognition
... for image recognition requires deep machine ...on convolutional neural net processor as the specific task requires massive amount power for its compute-intensive nature images are often ... See full document
7
Analysis of Tourists’ Image of Seoul with Geotagged Photos using Convolutional Neural Networks
... In this study we aim to analyze the tourists’ images of Seoul by making use of the photos uploaded by visitors on Flickr which is one SNS platforms, from January 1, 2015 until December 31, 2017. We were able to find out ... See full document
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An Algorithm for Power System Fault Analysis ...
... Three depth channels are used for the different phases. This idea originates from the intuition that there might be an analogy between a three-phased power signal and an image with three color layers (in ... See full document
8
Dense ResNet based Human Action Recognition using Novel Trajectory Maps on 3D Skeletal Data
... hierarchical image functionality of Deep Convolutional Neural Networks ...learning networks. The Residual Networks (ResNets) are proposed to use [1] to get higher levels of ... See full document
10
Deep learning for smart agriculture: Concepts, tools, applications, and opportunities
... of Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN) and Generative Adversarial Networks (GAN), has been widely studied and applied in various fields including ... See full document
13
An Approach for Face Recognition System Using Convolutional Neural Network and Extracted Geometric Features
... automatic image processing to extract semantic content for effective analysis and pattern ...facial analysis is to extract valuable information from face images such as position in the image, ... See full document
5
Estimation of the PCB Production Process Using a Neural Network
... uses Convolutional Neural Networks (CNN) to find the number of smaller pitch areas in the PCB ...and analysis can be used to estimate the time required for ...the Convolutional ... See full document
7
Asymmetric 3D Convolutional Neural Networks for Action Recognition
... Convolutional Neural Network based action recognition methods have achieved significant improvements in recent ...better analysis of human activities in ...3D convolutional ... See full document
36
Sentiment Classification Via Recurrent Convolutional Neural Networks
... Sentiment analysis (also known as opinion mining) refers to the use of natural language processing, text analysis and computational linguistics to identify and extract subjective information in source ... See full document
9
Wildlife surveillance using deep learning methods
... 2012). Convolutional neural networks have only recently been ap- plied to automatic classification of wildlife images, with limitations in performance ...same image recognition ... See full document
15
Convolutional Neural Networks for Clothing Image Style Recognition
... for image recognition include: Bayesian classification, template matching, ...the recognition of clothing image styles, for example, keywords in style quantification the color attributes and ... See full document
6
Handwritten Digit Recognition Using Convolutional Neural Networks
... digit recognition becomes vital scope and it is appealing many researchers because of its using in variety of machine learning and computer vision ...deep convolutional neural network is used for ... See full document
6
Deep machine learning provides state of the art performance in image based plant phenotyping
... large image sets in order to aid genetic ...data analysis problems. Building on artificial neural networks, deep approaches have many more hidden layers in the network, and hence have greater ... See full document
10
Captioning for Motion Detection for video surveillance Applications using Deep Learning
... this image captioning framework and so that the attributes can be introduced to the CNN and RNN ...feeding image representations in various ways to explore mutual and fuzzy relationship between ...visual ... See full document
6
Generalizing convolutional neural networks for pattern recognition tasks
... the two-dimensional (2-D) image topology of input changes. This makes CNN robust against changes of input patterns, including translation, scaling, and rotation. This robustness is due to the built-in invariance ... See full document
11
Combination of Multiple Acoustic Models with Multi-scale Features for Myanmar Speech Recognition
... deep convolutional neural networks ...speech recognition due to its ability of reducing spectral variations and modelling spectral correlations in the input ...speech recognition ... See full document
10
Human emotion recognition in video using subtraction pre-processing
... new image pre-processing method, which can show features or important information ...expression recognition is one of the most popular classification topics and will become essential in robotics and ... See full document
8
Khmer handwritten text recognition with Convolution Neural Networks
... symbols recognition using Convolutional Neural Networks ...a recognition system for digitizing large corpora of Khmer handwritten ...documents. Image data consists of six ... See full document
6
Deep Learning Techniques for Object Detection
... one-stage networks in order to maintain accuracy while eliminating ...anomalies. Neural Networks are being employed to detect cancerous cells from images, detection of heart risks from patients’ ... See full document
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