[PDF] Top 20 Convolutional neural network-based automatic image recognition for agricultural machinery

Convolutional neural network-based automatic image recognition for agricultural machinery

... from convolutional layers to be trained for the machinery recognition model in this study, which involved hundreds of millions of additions and multiplications to process all images, it would take ... See full document

7

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

6

Deep Kernel based Convolutional Neural Networks for Image Recognition

... in neural network the high level reasoning is done via fully connected layers, after several convolutional layer and max pooling ...offset. Convolutional neural networks use three basic ... See full document

7

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

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

... Android-based image recognition system using Convolutional Neural Network was used as a new method to classify and identify rice variety in terms of visual features such as size, ... See full document

5

An analytical study of information extraction from unstructured and multidimensional big data

... artificial neural network; ASR: automatic speech recognition; AVS: automatic video summarization; BFM: Bayesian fusion model; CNN: convolutional neural network; ... See full document

38

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

6

SAR Automatic Target Recognition Based on Deep Convolutional Neural Networks

... Deep convolutional neural networks (CNN) have recently proven extremely competitive in challenging visible light image and speech recognition ...learned convolutional network ... See full document

9

PestNet : an end-to-end deep learning approach for large-scale multi-class pest detection and classification

... classification based on deep ...into Convolutional Neural Network (CNN) backbone for feature extraction and ...Proposal Network (RPN) that is adopted for providing region proposals as ... See full document

12

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

6

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

8

An Analysis of Convolutional Neural Networks for Image Recognition

... lower recognition rate or more time- ...is automatic, and CNN can take the original image as the input of network directly, avoiding the manual extraction of features that would lead to the ... See full document

5

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

17

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

14

License Plate Character Recognition using Riesz Fractional and Convolutional Neural Network

... (VEDA) based on the contrast between the grayscale ...new automatic license plate detection method based basic enhancement techniques, which effectively detected license plate area from an ... See full document

5

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 ... See full document

8

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 and ... See full document

8

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

TensorFlow and Keras based Convolutional Neural Network in CAT Image Recognition

... simple image recognition model is created to accurately differentiate the cats' picture from other pictures to ...Each image has a fixed width and length, and each pixel is represented by an RGB ... See full document

5

A Radon-based Convolutional Neural Network for Medical Image Retrieval

... deep network to propose a retrieval system for a highly imbalanced medical ...a convolutional neural network, significantly increases the performance, compared with other retrieval ... See full document

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