Why U-Net?
Look, I'll be honest with you. There are better models than U-Net out there and newer models are being released every month. However, U-Net was designed for biomedical applications such as XRay, and MRI Images for tumor detection.
⭐️Free U-NET Course - [ Ссылка ]
🚀$47 U-NET PRO Course - [ Ссылка ]
U-Net is preferred over other architectures largely because of the 3 reasons:
1. Simplicity - U-Net has a very simple architecture with no complicated convolutional blocks
2. Good Baseline Architecture - It's not only a better choice for advanced-level applications but acts as a great starting for beginners, too.
3. Competitive Performance - U-Net produces excellent results with far better accuracy and minimum occurring loss.
⭐ AI Projects:
[ Ссылка ]
⭐ FREE Computer Vision Course :
[ Ссылка ]
⭐ JOIN our Membership to get access to Source Code : [ Ссылка ]
===Product Links===
✔️ Webcam - [ Ссылка ]
✔️ Deep Learning PC - [ Ссылка ]
✔️ OpenCV Python Books -[ Ссылка ]
✔️ Camera Gear - [ Ссылка ]
✔️ Drone Kit - [ Ссылка ]
✔️ Raspberry Pi 4 - [ Ссылка ]
✔️ OpenCV AI Kit - [ Ссылка ]
✔️ Roboflow - [ Ссылка ]
✔️ Arduino Electronics kit - [ Ссылка ]
------------------------------------------------------------
Support us on Patreon
►[ Ссылка ]
Chat to us on Discord
►[ Ссылка ]
Interact with us on Facebook
►[ Ссылка ]
Check my latest work on LinkedIn
►[ Ссылка ]
------------------------------------------------------------
#unet
#OpenCV
#Python
Why Choose UNET for Image Segmentation?
Теги
opencvcomputer visionopencv tutorialscomputer vision tutorialsartificial intelligencetensorflowopencv pythonimage segmentationUNETUNET SegmentationObject segmentationmask rcnnbinary segmentationimage processing using pythonsemantic segmentationimage processingdeep learningmachine learningdeep learning coursedeep learning projectsmachine learning full coursemachine learning interview questionsmachine learning algorithms
