𝗗𝗮𝘆-𝟭𝟭𝟭 Computer Vision Learning 𝐕𝐆𝐆𝐍𝐞𝐭 for COVID-19 Detection (Biomedical Image Classification) Follow me for similar post : 🇮🇳 Ashish Patel Interesting Facts : 🔸 This is a paper in 2020 IEEE ACCESS with over 35 citations. 🔸 Detect Multimodal Imaging Data: Ultrasound, X-Ray & CT Scan ------------------------------------------------------------------- 𝗔𝗺𝗮𝘇𝗶𝗻𝗴 𝗥𝗲𝘀𝗲𝗮𝗿𝗰𝗵 : https://lnkd.in/g2upBth ------------------------------------------------------------------- 𝗜𝗠𝗣𝗢𝗥𝗧𝗔𝗡𝗖𝗘 🔸 Broncho vascular thickening in the lesion, and traction bronchiectasis are visible during absorption stage, automatic diagnosis is possible. 🔸 Various classification models are tested, such as VGG16/VGG19, ResNet-50, Inception-v3, Xception, Inception-ResNet-v2, DenseNet, and NASNet-Large, for COVID-19 detection. 🔸It is found that VGGNet has the most stable performance across different multimodal datasets including Ultrasound, X-ray and CT scan. #computervision #artificialintelligence #deeplearning
Love this
This is very helpful for many students
Would be more helpful if you could share the code snippet
I really like these short posts about nice research papers. Helps a lot.
Amazing 👍
For previous post visit this github : https://github.com/ashishpatel26/365-Days-Computer-Vision-Learning-Linkedin-Post
The aim is to provide over-stressed medical professionals a second pair of eyes through intelligent deep learning image classi cation models, providing an automated “second reading’’ to clinicians, assisting in the diagnosis and criticality assessment.
Complete research of Multimodal imaging :- https://www.linkedin.com/posts/pooja-jagtap-978091216_multimodalabrimaging-multimodalabrimaging-activity-6868414506683498496-3mm5