Deep learning for Alzheimer's disease diagnosis: A survey

M Khojaste-Sarakhsi, SS Haghighi… - Artificial intelligence in …, 2022 - Elsevier
Alzheimer's Disease (AD) is an irreversible neurodegenerative disease that results in a
progressive decline in cognitive abilities. Since AD starts several years before the onset of …

Forest fire and smoke detection using deep learning-based learning without forgetting

VE Sathishkumar, J Cho, M Subramanian, OS Naren - Fire ecology, 2023 - Springer
Background Forests are an essential natural resource to humankind, providing a myriad of
direct and indirect benefits. Natural disasters like forest fires have a major impact on global …

A survey on deep learning based face recognition

G Guo, N Zhang - Computer vision and image understanding, 2019 - Elsevier
Deep learning, in particular the deep convolutional neural networks, has received
increasing interests in face recognition recently, and a number of deep learning methods …

On fine-tuning deep learning models using transfer learning and hyper-parameters optimization for disease identification in maize leaves

M Subramanian, K Shanmugavadivel… - Neural Computing and …, 2022 - Springer
Maize is one of the world's most important food crops, but its cultivation is hampered by
diseases. Rapid disease identification remains a challenge due to a lack of the necessary …

Hyperparameter optimization for transfer learning of VGG16 for disease identification in corn leaves using Bayesian optimization

M Subramanian, NP Lv, S VE - Big Data, 2022 - liebertpub.com
One of the world's most widely grown crops is corn. Crop loss due to diseases has a major
economic effect, putting the food supply in jeopardy. In many parts of the world, lack of …

Histopathological image classification with bilinear convolutional neural networks

C Wang, J Shi, Q Zhang, S Ying - 2017 39th Annual …, 2017 - ieeexplore.ieee.org
The computer-aided quantitative analysis for histopathological images has attracted
considerable attention. The stain decomposition on histopathological images is usually …

Canonical correlation analysis networks for two-view image recognition

X Yang, W Liu, D Tao, J Cheng - Information Sciences, 2017 - Elsevier
In recent years, deep learning has attracted an increasing amount of attention in machine
learning and artificial intelligence areas. Currently, many deep learning network-related …

Unsupervised pre-trained filter learning approach for efficient convolution neural network

S ur Rehman, S Tu, M Waqas, Y Huang, O ur Rehman… - Neurocomputing, 2019 - Elsevier
Abstract The concept of Convolution Neural Network (ConvNet or CNN) is evaluated from
the animal visual cortex. Since humans can learn through experience, similarly, ConvNet …

Histopathological image classification with color pattern random binary hashing-based PCANet and matrix-form classifier

J Shi, J Wu, Y Li, Q Zhang, S Ying - IEEE journal of biomedical …, 2016 - ieeexplore.ieee.org
The computer-aided diagnosis for histopathological images has attracted considerable
attention. Principal component analysis network (PCANet) is a novel deep learning …

A survey on image data analysis through clustering techniques for real world applications

S Wazarkar, BN Keshavamurthy - Journal of Visual Communication and …, 2018 - Elsevier
A huge amount of image data is being collected in real world sectors. Image data analytics
provides information about important facts and issues of a particular domain. But, it is …