Ammus: A survey of transformer-based pretrained models in natural language processing
KS Kalyan, A Rajasekharan, S Sangeetha - arXiv preprint arXiv …, 2021 - arxiv.org
Transformer-based pretrained language models (T-PTLMs) have achieved great success in
almost every NLP task. The evolution of these models started with GPT and BERT. These …
almost every NLP task. The evolution of these models started with GPT and BERT. These …
Multi-disease prediction based on deep learning: a survey
S Xie, Z Yu, Z Lv - Computer Modeling in Engineering & …, 2021 - ingentaconnect.com
In recent years, the development of artificial intelligence (AI) and the gradual beginning of
AI's research in the medical field have allowed people to see the excellent prospects of the …
AI's research in the medical field have allowed people to see the excellent prospects of the …
A comprehensive survey on segmentation techniques for retinal vessel segmentation
In recent years, enormous research has been carried out on the segmentation of blood
vessels. Segmentation of blood vessels in retinal images is crucial for diagnosing, treating …
vessels. Segmentation of blood vessels in retinal images is crucial for diagnosing, treating …
IoT and deep learning based approach for rapid screening and face mask detection for infection spread control of COVID-19
The spread of COVID-19 has been taken on pandemic magnitudes and has already spread
over 200 countries in a few months. In this time of emergency of COVID-19, especially when …
over 200 countries in a few months. In this time of emergency of COVID-19, especially when …
[HTML][HTML] Segmentation and classification of brain tumor using 3D-UNet deep neural networks
P Agrawal, N Katal, N Hooda - International Journal of Cognitive …, 2022 - Elsevier
Early detection and diagnosis of a brain tumor enhance the medical options and the
patient's chance of recovery. Magnetic resonance imaging (MRI) is used to detect and …
patient's chance of recovery. Magnetic resonance imaging (MRI) is used to detect and …
[HTML][HTML] An experimental analysis of different deep learning based models for Alzheimer's disease classification using brain magnetic resonance images
Classification of Alzheimer's disease (AD) is one of the most challenging issues for
neurologists. Manual methods are time consuming and may not be accurate all the time …
neurologists. Manual methods are time consuming and may not be accurate all the time …
Texture defect classification with multiple pooling and filter ensemble based on deep neural network
Fabric quality control is one of the most important phases of production in order to ensure
high-quality standards in the fabric production sector. For this reason, the development of …
high-quality standards in the fabric production sector. For this reason, the development of …
Deep multi-modal discriminative and interpretability network for Alzheimer's disease diagnosis
Multi-modal fusion has become an important data analysis technology in Alzheimer's
disease (AD) diagnosis, which is committed to effectively extract and utilize complementary …
disease (AD) diagnosis, which is committed to effectively extract and utilize complementary …
Improved YOLOv3-based bridge surface defect detection by combining High-and low-resolution feature images
S Teng, Z Liu, X Li - Buildings, 2022 - mdpi.com
Automatic bridge surface defect detection is of wide concern; it can save human resources
and improve work efficiency. The object detection algorithm, especially the You Only Look …
and improve work efficiency. The object detection algorithm, especially the You Only Look …
Concrete crack detection based on well-known feature extractor model and the YOLO_v2 network
S Teng, Z Liu, G Chen, L Cheng - Applied Sciences, 2021 - mdpi.com
This paper compares the crack detection performance (in terms of precision and
computational cost) of the YOLO_v2 using 11 feature extractors, which provides a base for …
computational cost) of the YOLO_v2 using 11 feature extractors, which provides a base for …