Gender Classification Using a Convolutional Neural Network (CNN)
Abstract The purpose of this paper is to demonstrate an innovative convolutional neural network (also known as CNN) methodology for real-time categorization of gender via face photos. The suggested CNN architecture boasts much reduced computational complexity than the current methodologies used in pattern recognition applications.
Vyshnavi, Cherukuri +4 more
openaire +2 more sources
HSI-CNN: A Novel Convolution Neural Network for Hyperspectral Image
CoRR, 2018 With the development of deep learning, the performance of hyperspectral image (HSI) classification has been greatly improved in recent years. The shortage of training samples has become a bottleneck for further improvement of performance. In this paper, we propose a novel convolutional neural network framework for the characteristics of hyperspectral ...
Yanan Luo +4 more
openaire +2 more sources
A Dilated CNN Model for Image Classification
IEEE Access, 2019 The dilated convolution algorithm, which is widely used for image segmentation, is applied in the image classification field in this paper. In many traditional image classification algorithms, convolution neural network (CNN) plays an important role ...
Xinyu Lei +2 more
doaj +1 more source
Application of Convolution Neural Network (CNN) Model Combined with Pyramid Algorithm in Aerobics Action Recognition. [PDF]
Comput Intell Neurosci, 2021 Liang Q.
europepmc +1 more source
, 2022 Convolutional neural networks (CNNs) are one of the popular deep learning methods used to solve the hyperspectral image classification (HSIC) problem. CNN has a strong feature learning ability that can ensure more distinctive features for higher quality ...
Davut HANBAY +5 more
core +1 more source
Chest Radiographs Using a Context-Fusion Convolution Neural Network (CNN): Can It Distinguish the Etiology of Community-Acquired Pneumonia (CAP) in Children? [PDF]
J Digit Imaging, 2022 Hu S +7 more
europepmc +1 more source
Convolution Neural Network for Feature Extraction in Skin Disease Detection
, 2018 Skin Diseases are becoming very common now days. Number of people suffering from skin diseases is increasing rapidly. Human judgment on diagnosis of skin diseases is sometimes subjective and not reproducible.
Kalbande, Dhananjay; Sardar Patel Institute of Tech, Andheri,Mumbai, India +2 more
core
Photonic Convolution Neural Network Based on Interleaved Time-Wavelength Modulation
, 2021 Convolution neural network (CNN), as one of the most powerful and popular technologies, has achieved remarkable progress for image and video classification since its invention in 1989.
Wenjia Zhang (417706) +3 more
core +1 more source
A comparative study of machine learning models in predicting crop yield
Discover AgricultureThis paper explores different machine learning techniques applied in the prediction of crop yield based on meteorological parameters. Recurrent Neural Networks (RCN), Convolutional Neural Networks, Random Forest, Decision Trees, Gradient Boosting machine
Bobo Mafrebo Lionel +3 more
doaj +1 more source
Correction to: Extraction of Retinal Layers Through Convolution Neural Network (CNN) in an OCT Image for Glaucoma Diagnosis. [PDF]
J Digit Imaging, 2021 Raja H +6 more
europepmc +1 more source