Application of Convolutional Neural Network (CNN) to Recognize Ship Structures. [PDF]
Sensors (Basel), 2022 The purpose of this paper is to study the recognition of ships and their structures to improve the safety of drone operations engaged in shore-to-ship drone delivery service. This study has developed a system that can distinguish between ships and their structures by using a convolutional neural network (CNN).
Lim JJ +6 more
europepmc +6 more sources
Klasifikasi Penyakit Mata Menggunakan Convolutional Neural Network (CNN)
Sistemasi: Jurnal Sistem Informasi, 2021 Abstrak Gangguan pada mata atau disebut juga penyakit mata adalah suatu kondisi yang mampu mempengaruhi jangka waktu hidup bagi sebagian orang. Gangguan mata atau penyakit mata banyak sekali jenisnya, diantaranya yaitu katarak, glaukoma dan retina ...
Fani Nurona Cahya +3 more
doaj +3 more sources
A noise robust convolutional neural network for image classification
Results in Engineering, 2021 Convolutional Neural Networks (CNNs) are extensively used for image classification. Noisy images reduce the classification performance of convolutional neural networks and increase the training time of the networks.
Mohammad Momeny +4 more
doaj +3 more sources
Understanding of Convolutional Neural Network (CNN): A Review [PDF]
International Journal of Robotics and Control Systems, 2022 The application of deep learning technology has increased rapidly in recent years. Technologies in deep learning increasingly emulate natural human abilities, such as knowledge learning, problem-solving, and decision-making. In general, deep learning can
Purwono, Purwono +6 more
core +2 more sources
DK-CNNs: Dynamic kernel convolutional neural networks [PDF]
Neurocomputing, 2021 This paper introduces dynamic kernel convolutional neural networks (DK-CNNs), an enhanced type of CNN, by performing line-by-line scanning regular convolution to generate a latent dimension of kernel weights. The proposed DK-CNN applies regular convolution to the DK weights, which rely on a latent variable, and discretizes the space of the latent ...
Liu, Jialin +4 more
openaire +2 more sources
Chinese fingerspelling sign language recognition using a nine-layer convolutional neural network [PDF]
EAI Endorsed Transactions on e-Learning, 2021 INTRODUCTION: Sign language is a form of communication and exchange of ideas by people who are hearing-impaired or unable to speak.
Ya Gao +3 more
doaj +1 more source
Convolutional neural networks (CNNs): concepts and applications in pharmacogenomics [PDF]
Molecular Diversity, 2021 AbstractConvolutional neural networks (CNNs) have been used to extract information from various datasets of different dimensions. This approach has led to accurate interpretations in several subfields of biological research, like pharmacogenomics, addressing issues previously faced by other computational methods.
Vaz, Joel Markus, Balaji, S.
openaire +2 more sources
RF-CNN-F: random forest with convolutional neural network features for coronary artery disease diagnosis based on cardiac magnetic resonance [PDF]
, 2022 Coronary artery disease (CAD) is a prevalent disease with high morbidity and mortality rates. Invasive coronary angiography is the reference standard for diagnosing CAD but is costly and associated with risks.
Shoeibi, Afshin +17 more
core +1 more source
Research on improved convolutional wavelet neural network
Scientific Reports, 2021 Artificial neural networks (ANN) which include deep learning neural networks (DNN) have problems such as the local minimal problem of Back propagation neural network (BPNN), the unstable problem of Radial basis function neural network (RBFNN) and the ...
Jingwei Liu +4 more
doaj +1 more source
SAR image classification based on multi‐feature fusion decision convolutional neural network
IET Image Processing, 2022 With the success of convolutional neural network (CNN) in the field of image processing and image recognition, an improved fully convolutional neural network (FCNN) based on CNN is proposed.
Liang Guo
doaj +1 more source