[PDF] Top 20 Optimization of Convolutional Neural Network Target Recognition Algorithm

Optimization of Convolutional Neural Network Target Recognition Algorithm

... In addition to weight initialization, the pooling layer is also an important factor that affects the recognition rate and robustness of the CNN. The pooling layer mainly aims to obscure and generalize features, to ... See full document

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Convolutional neural networks for radar HRRP target recognition and rejection

... of convolutional layers as shown in ...two convolutional layers, both of which have 32 output channels, termed as ...the recognition results, for both SCNN and TCNN models, the best results are ... See full document

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A Detection algorithm based on Convolutional Neural Network

... traversal recognition algorithm to compare the key frames read each time with the knowledge base template, but the computational efficiency of this method decreases as the number of station marks in the ... See full document

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A NOVEL TWO DIMENSIONAL SPECTRAL/SPATIAL HYBRID CODE FOR OPTICAL CODE DIVISION MULTIPLE ACCESS SYSTEM

... ear recognition method, which measures the similarity between the input ear image and the ear images of known individuals in a ...the recognition accuracy and reducing the time required of measuring the ... See full document

10

Handwritten Digit Recognition: Convolutional Neural Network as a Classifier

... a neural network method for recognizing printed and handwritten ...The recognition is performed using a multilayer and clustered back propagation ...multilayer neural network is to ... See full document

6

Automatic diagnosis of imbalanced ophthalmic images using a cost-sensitive deep convolutional neural network

... and algorithm lev- elling [9, 21, 22] are employed to address the imbalanced datasets ...using algorithm leveling has a distinct advantage because it makes full use of the original data [9, 21, ...deep ... See full document

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DETECTION AND CLASSIFICATION OF DIABETIC RETINOPATHY USING ADAPTIVE BOOSTING AND ARTIFICIAL NEURAL NETWORK

... our network for training purpose. Multiple layered convolutional neural networks are designed and trained with different hyper- parameter values, changing behavior of the training curves are analyzed ... See full document

6

SAR Automatic Target Recognition Based on Deep Convolutional Neural Networks

... Stationary Target Acquisition and recognition (MSTAR) program ...each target, images are captured at two different depression angles 15deg and 17deg over all the 360deg aspect angles with 1ft1ft ... See full document

9

Vehicle Recognition Based On Convolutional Neural Network

... Convolutional neural network (CNN) is a machine learning model for a deep supervised ...speech recognition and image ...numeral recognition as a tool for Bank of America of ... See full document

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Three-dimensional convolutional restricted Boltzmann machine for human behavior recognition from RGB-D video

... weight-sharing network structure with the biological neural networks makes it possible to reduce the complexity of network model as well as the number of ...the network is a multi-dimen- ... See full document

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Robust Face Recognition Based on Convolutional Neural Network

... multi-layer neural network algorithm of machine learning field and artificial intelligence (AI), has obtained great ...deep network, the parallel calculation under the large-scale data, the ... See full document

6

Iris Recognition using Convolutional Neural Network Design

... for recognition rate with state of art approaches. The recognition rate obtained is summarized in table ...The optimization techniques have shown slightly varying recognition rates for same ... 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 ...model recognition. The network performance comparison and optimization ... See full document

6

Optimization of Convolutional Neural Network for Recognition of Vehicle Frame Number

... character recognition method has the problem of complex feature extraction, and the convolutional neural network has unique advantages in processing two-dimensional ...tional neural ... See full document

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3D Convolutional Neural Network for Object Recognition

... Object recognition in 3D CNN is done, by selecting most similar features from targeted ...exploit network, we provide rotation of 30° along the gravity to the ...proposed network is modified version ... See full document

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Recognition of Brahmi words by Using Deep Convolutional Neural Network

... the Convolutional Neural Network (CNN) in ...training algorithm made it hard to use at the ...learning algorithm with ...of network which are fully connected and similar in size, ... See full document

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A Convolutional Neural Network for Handwritten Digit Recognition

... a neural network with multiple layers, trained with a version of the back-propagation algorithm and it is designed to recognize visual patterns directly from pixel images with minimal ...Many ... See full document

9

DialogueGCN: A Graph Convolutional Neural Network for Emotion Recognition in Conversation

... of target and context utterances decides how past utterances influence fu- ture utterances and vice ...convolution network (GCN) (Defferrard et ... See full document

11

Firearm Recognition Using Convolutional Neural Network

... and recognition of dangerous situations for CCTV ...detection algorithm that offers a near zero rate of false alarms and have shown that it is possible to create a system that are capable of an early ... See full document

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REVIEW OF SPEECH AND SPEECH RECOGNITION SYSTEM USING FEATURE EXTRACTION ALGORITHM AND OPTIMIZATION ALGORITHMS

... speech recognition and speaker recognition ...speech recognition with speaker recognition based on Hidden Markov Model for security is a requirement of ...Artificial Neural networks is ... See full document

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