Advanced metaheuristic optimization techniques in applications of deep neural networks: a review
Deep neural networks (DNNs) have evolved as a beneficial machine learning method that
has been successfully used in various applications. Currently, DNN is a superior technique …
has been successfully used in various applications. Currently, DNN is a superior technique …
Multiscaled fusion of deep convolutional neural networks for screening atrial fibrillation from single lead short ECG recordings
Atrial fibrillation (AF) is one of the most common sustained chronic cardiac arrhythmia in
elderly population, associated with a high mortality and morbidity in stroke, heart failure …
elderly population, associated with a high mortality and morbidity in stroke, heart failure …
Gabor convolutional networks
In steerable filters, a filter of arbitrary orientation can be generated by a linear combination of
a set of “basis filters.” Steerable properties dominate the design of the traditional filters, eg …
a set of “basis filters.” Steerable properties dominate the design of the traditional filters, eg …
Drawing and recognizing chinese characters with recurrent neural network
Recent deep learning based approaches have achieved great success on handwriting
recognition. Chinese characters are among the most widely adopted writing systems in the …
recognition. Chinese characters are among the most widely adopted writing systems in the …
Online and offline handwritten Chinese character recognition: A comprehensive study and new benchmark
Recent deep learning based methods have achieved the state-of-the-art performance for
handwritten Chinese character recognition (HCCR) by learning discriminative …
handwritten Chinese character recognition (HCCR) by learning discriminative …
[PDF][PDF] Arabic handwritten characters recognition using convolutional neural network
A El-Sawy, M Loey, H El-Bakry - WSEAS Transactions on …, 2017 - researchgate.net
Handwritten Arabic character recognition systems face several challenges, including the
unlimited variation in human handwriting and large public databases. In this work, we model …
unlimited variation in human handwriting and large public databases. In this work, we model …
Food/non-food image classification and food categorization using pre-trained googlenet model
A Singla, L Yuan, T Ebrahimi - … of the 2nd international workshop on …, 2016 - dl.acm.org
Recent past has seen a lot of developments in the field of image-based dietary assessment.
Food image classification and recognition are crucial steps for dietary assessment. In the …
Food image classification and recognition are crucial steps for dietary assessment. In the …
[HTML][HTML] A bibliometric analysis of off-line handwritten document analysis literature (1990–2020)
Providing computers with the ability to process handwriting is both important and
challenging, since many difficulties (eg, different writing styles, alphabets, languages, etc.) …
challenging, since many difficulties (eg, different writing styles, alphabets, languages, etc.) …
Data augmentation for motor imagery signal classification based on a hybrid neural network
As an important paradigm of spontaneous brain-computer interfaces (BCIs), motor imagery
(MI) has been widely used in the fields of neurological rehabilitation and robot control …
(MI) has been widely used in the fields of neurological rehabilitation and robot control …
Improving handwritten Chinese text recognition using neural network language models and convolutional neural network shape models
Handwritten Chinese text recognition based on over-segmentation and path search
integrating multiple contexts has been demonstrated successful, wherein the language …
integrating multiple contexts has been demonstrated successful, wherein the language …