Computer Vision News - July 2022

47 Vision Transformers in Medical CV Medical-imaging applications fail when moving from ImageNet to clinical tests due to the following problems: a small training set and generalization issues, and over-fitting. By using MedNet, they can easily notice those prominent effects and improve performance. Overall, MedNet as described and analysed earlier has the following advantages: a high performance, a small training set and generalization issues, and prevention of over-fitting. A question for all of you: are there applications where MedNet will be useful to you, and if so, which are they? Let us know! Next month Thank you for reading the article this month about amedical deep learning layered network. We hope that you enjoyed it and don’t hesitate to send our way any corrections, suggestions, or ideas for next month’s issue! Take care and as always have a great time and always be curious! 