[PDF] Top 20 TensorFlow and Keras based Convolutional Neural Network in CAT Image Recognition

TensorFlow and Keras based Convolutional Neural Network in CAT Image Recognition

... and image recognition is a key part of Artificial Intelligence. Based on the convolutional neural network model, 4 layers of convolution layers and two layers of common dense ... See full document

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Deep Kernel based Convolutional Neural Networks for Image Recognition

... PERFORMANCE NEURAL NETWORKS FOR VISUAL OBJECT ...input image size, number of hidden layers, number of maps per layer, kernel sizes, skipping factors and connection tables are adaptable to any particular ... See full document

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Recognition of Handwritten Digit using Convolutional Neural Network in Python with Tensorflow and Comparison of Performance for Various Hidden Layers

... handwritten recognition digits, characters are given as ...artificial neural network (ANN) has an input layer, an output layer and some hidden layers between the input and output ...the ... See full document

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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

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Vehicle Model Recognition Based on Convolutional Neural Network

... model recognition method based on CNN. However, the neural network was simple in structure and low in ...accuracy. Based on the front-view images of vehicles, Literature [2] proposed a ... See full document

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Android-Based Rice Variety Classifier (Arvac) Using Convolutional Neural Network

... was based on the Rapid Application Development (RAD) model which consists of different phases such as Analysis and Quick Design, Testing and ...google’s TensorFlow and a smartphone that has a built-in ... See full document

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The Performance of Deep Learning Algorithms on Automatic Pulmonary Nodule Detection and Classiﬁcation Tested on Di erent Datasets That Are Not Derived from LIDC-IDRI: A Systematic Review

... studies: convolutional neural network (CNN), massive training artificial neural network (MTANN), and deep supervised denoising autoencoder architecture based on extreme learning ... See full document

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

... expression recognition is an important topic in an image processing and pattern ...expressions based on these extracted features by using a modified Convolutional Neural Network ... See full document

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Firearm Recognition Using Convolutional Neural Network

... approach based on various tools designed for object detection and recognition that has been applied in MPEG-7 visual descriptors, directed towards safety related ...advanced image cataloguing tool ... See full document

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Oracle-Bone Inscription Recognition Based on Deep Convolutional Neural Network

... OBI image is , therefore, after 5 convolutional layers and 4 max-pool layers, the feature maps are flattened and concatenated into a vector with the dimensionality of ... See full document

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Recognition of Printed Mathematical Formula Symbols Based on Convolutional Neural Network

... and image recognition in recent years, and its advantage is that can overcome the shortcomings of manual feature ...deep network model with multiple hidden layers and using a large number of training ... See full document

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Identification Of Weeds From Crops Using Convolutional Neural Network

... input image which helps to optimize the number of hyper parameters in the architecture and supports in improving the computation efficiency of the ...varieties based on its commonality and it also able to ... See full document

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Video Analysis with Image Recognition in TensorFlow

... Bayesian network classifiers are a popular supervised classification ...Bayesian network classifier is the Naïve Bayes’ classifier is a probabilistic classifier based on the Bayes’ theorem, ... See full document

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3D Convolutional Neural Network for Object Recognition

... object recognition models have its origin in the ...est recognition frameworks were created on geometry-based models ...3D recognition has first used for RGB-D images, where depth is treated ... See full document

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A Radon-based Convolutional Neural Network for Medical Image Retrieval

... Step 4: image retrieval is the main aim of this step. Suppose a test query is selected. This query goes through the proposed chain of processing. Figure 6 depicts, 90 equidistant Radon projections of the computed ... See full document

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A new algorithm of SAR image target recognition based on improved deep convolutional neural network

... SAR-ATR systems generally consist of three stages: detection [1, 2], recognition, and classification. At present, common methods of SAR-ATR include template matching [3], support vector machine (SVM)[4], Linear ... See full document

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Vehicle Recognition Based On Convolutional Neural Network

... vehicle image recognition as an ...the image of three models of cars, buses and trucks as test samples and training ...the convolutional neural network input, the images of three ... See full document

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Research on road extraction of remote sensing image based on convolutional neural network

... natural image classification, target recognition, image segmentation ...applied convolutional neural networks to target recognition inlarge scale natural ...target ... See full document

11

Machine Learning based Object Identification System using Python

... learning convolutional neural network based on keras and tensorflow is developed using python for image ...namely cat and dog which are used to train the ... See full document

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A CONVOLUTIONAL NEURAL NETWORK (CNN) APPROACH TO DETECT FACE USING TENSORFLOW AND KERAS

... positive image and an anchor and a negative ...the network are not the same but if the distances between the pair of images are small then we could say that both the images are of the same ... See full document

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