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Keyword: ResNetConvolutional Neural Network Based on HOG Feature for Bird Species Detection and Classification
This work is concerned with the detection and classification of birds that have applications like monitoring extinct and migrated birds. Recent computer vision algorithms can precise this kind of task but still there are some dominant issues like low light, very little differences between subspecies of birds, etc are to be studied. As Convolution Neural…
Read MoreUsing Classic Networks for Classifying Remote Sensing Images: Comparative Study
This paper presents a comparative study for using the classic networks in remote sensing images classification. There are four deep convolution models that used in this comparative study; the DenseNet 196, the NASNet Mobile, the VGG 16, and the ResNet 50 models. These learning convolution models are based on the use of the ImageNet pre-trained…
Read MoreInvestment of Classic Deep CNNs and SVM for Classifying Remote Sensing Images
Feature extraction is an important process in image classification for achieving an efficient accuracy for the classification learning models. One of these methods is using the convolution neural networks. The use of the trained classic deep convolution neural networks as features extraction gives a considerable results in the remote sensing images classification models. So, this…
Read MoreTransfer Learning and Fine Tuning in Breast Mammogram Abnormalities Classification on CBIS-DDSM Database
Breast cancer has an important incidence in women mortality worldwide. Currently, mam- mography is considered the gold standard for breast abnormalities screening examinations, since it aids in the early detection and diagnosis of the illness. However, both identification of mass lesions and its malignancy classification is a challenging problem for artificial intelligence. In this work,…
Read MoreSentiment Analysis of Transjakarta Based on Twitter using Convolutional Neural Network
TransJakarta is one of the methods to reduce congestion in Jakarta. However, the number of TransJakarta users compared to number of private vehicle users is very small, only 24% of the total population in Jakarta. The purpose of this research is to know public opinions about TransJakarta whether positive or negative by doing sentiment analysis…
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