Multiclass Image Segmentation using UNETR in TensorFlow | Vision Transformer for Image Segmentation
Video Description: In this video, we are going to train the UNEt TRansformers (UNETR) architecture on the Landmark Guided Face Parsing dataset (LaPa) dataset for Multiclass Image Segmentation.
UNETR, or UNet Transformer, is a specialized architecture for medical image segmentation. It uses a pure transformer as the encoder, focusing on learning sequence representations for the input volume to capture global multi-scale information. The encoder connects directly to a decoder through skip connections, forming a U-Net-like structure and producing the ultimate semantic segmentation output.
Code:
Timeline:
00:00 - Introduction
00:59 - Landmark Guided Face Parsing dataset (LaPa) dataset.
02:46 - UNETR Architecture
04:35 - Training the UNETR
16:23 - Testing the UNETR
31:36 - Conclusion
Binary Image Segmentation using UNETR in TensorFlow:
UNETR Implementation in TensorFlow:
UNETR Implementation in PyTorch:
Support:
-
-
Connect with Me:
Blog: idiotdeveloper.com
Telegram: t.me/idiotdeveloper
Facebook: facebook.com/idiotdeveloper
Twitter: twitter.com/nikhilroxtomar
Instagram: instagram/nikhilroxtomar
Immerse yourself in the world of UNETR and revolutionize your understanding of image segmentation. Subscribe, code along, and let's embark on this transformative journey together!
Смотрите видео Multiclass Image Segmentation using UNETR in TensorFlow | Vision Transformer for Image Segmentation онлайн без регистрации, длительностью 32 минут 27 секунд в хорошем hd качестве. Это видео добавил пользователь Idiot Developer 02 Февраль 2024, не забудьте поделиться им ссылкой с друзьями и знакомыми, на нашем сайте его посмотрели 1 тысяч раз и оно понравилось 32 людям.