CNN variants for computer vision: History, architecture, application, challenges and future scope
Computer vision is becoming an increasingly trendy word in the area of image processing.
With the emergence of computer vision applications, there is a significant demand to …
With the emergence of computer vision applications, there is a significant demand to …
State of the art in defect detection based on machine vision
Z Ren, F Fang, N Yan, Y Wu - International Journal of Precision …, 2022 - Springer
Abstract Machine vision significantly improves the efficiency, quality, and reliability of defect
detection. In visual inspection, excellent optical illumination platforms and suitable image …
detection. In visual inspection, excellent optical illumination platforms and suitable image …
A review of deep learning methods for semantic segmentation of remote sensing imagery
X Yuan, J Shi, L Gu - Expert Systems with Applications, 2021 - Elsevier
Semantic segmentation of remote sensing imagery has been employed in many
applications and is a key research topic for decades. With the success of deep learning …
applications and is a key research topic for decades. With the success of deep learning …
Medical image segmentation using deep semantic-based methods: A review of techniques, applications and emerging trends
Semantic-based segmentation (Semseg) methods play an essential part in medical imaging
analysis to improve the diagnostic process. In Semseg technique, every pixel of an image is …
analysis to improve the diagnostic process. In Semseg technique, every pixel of an image is …
On the analyses of medical images using traditional machine learning techniques and convolutional neural networks
Convolutional neural network (CNN) has shown dissuasive accomplishment on different
areas especially Object Detection, Segmentation, Reconstruction (2D and 3D), Information …
areas especially Object Detection, Segmentation, Reconstruction (2D and 3D), Information …
Deep learning system for paddy plant disease detection and classification
Automatic detection and analysis of rice crop diseases is widely required in the farming
industry, which can be utilized to avoid squandering financial and other resources, reduce …
industry, which can be utilized to avoid squandering financial and other resources, reduce …
COVID-19 detection using deep learning models to exploit Social Mimic Optimization and structured chest X-ray images using fuzzy color and stacking approaches
Coronavirus causes a wide variety of respiratory infections and it is an RNA-type virus that
can infect both humans and animal species. It often causes pneumonia in humans. Artificial …
can infect both humans and animal species. It often causes pneumonia in humans. Artificial …
A survey of the recent architectures of deep convolutional neural networks
Abstract Deep Convolutional Neural Network (CNN) is a special type of Neural Networks,
which has shown exemplary performance on several competitions related to Computer …
which has shown exemplary performance on several competitions related to Computer …
A survey of the vision transformers and their CNN-transformer based variants
Vision transformers have become popular as a possible substitute to convolutional neural
networks (CNNs) for a variety of computer vision applications. These transformers, with their …
networks (CNNs) for a variety of computer vision applications. These transformers, with their …
Modality specific U-Net variants for biomedical image segmentation: a survey
With the advent of advancements in deep learning approaches, such as deep convolution
neural network, residual neural network, adversarial network; U-Net architectures are most …
neural network, residual neural network, adversarial network; U-Net architectures are most …