Day-11 Computer Vision Learning 𝗨𝗻𝗲𝘁 is one of the famous Fully Convolutional Networks (FCN) in biomedical image segmentation, which has been published in 2015 MICCAI with more than 3000 citations ------------------------------------------------------------------- 𝗔𝗺𝗮𝘇𝗶𝗻𝗴 𝗥𝗲𝘀𝗲𝗮𝗿𝗰𝗵 : https://lnkd.in/ePuKUBa 𝗣𝘆𝘁𝗼𝗿𝗰𝗵 𝗨𝗻𝗲𝘁 : https://bit.ly/2LH8woZ 𝗧𝗲𝗻𝘀𝗼𝗿𝗳𝗹𝗼𝘄𝟮 𝗨𝗻𝗲𝘁: https://bit.ly/38tTs7f 𝗞𝗲𝗿𝗮𝘀 𝗨𝗻𝗲𝘁 : https://bit.ly/35tI8Gm ------------------------------------------------------------------- 𝗜𝗠𝗣𝗢𝗥𝗧𝗔𝗡𝗖𝗘 Contraction path 🔸 Consecutive of two times of 3×3 Conv and 2×2 max pooling is done. This can help to extract more advanced features but it also reduces the size of feature maps. Note: More in comments #innovation #artificialintelligence #computervision
Oracle•105K followers
5yExpansion path The Unet architecture consists of a contracting path to capture context and a symmetric expanding path that enables precise localization. 🔸 Consecutive of 2×2 Up-conv and two times of 3×3 Conv is done to recover the size of segmentation map. However, the above process reduces the “where” though it increases the “what”. That means, we can get advanced features, but we also loss the localization information. 🔸 Thus, after each up-conv, we also have concatenation of feature maps (gray arrows) that are with the same level. This helps to give the localization information from contraction path to expansion path. 🔸 At the end, 1×1 conv to map the feature map size from 64 to 2 since the output feature map only have 2 classes, cell and membrane. #deeplearning #semanticsegmentation #india𝗘𝘅𝗽𝗮𝗻𝘀𝗶𝗼𝗻 𝗽𝗮𝘁𝗵𝗘𝘅𝗽𝗮𝗻𝘀𝗶𝗼𝗻 𝗽𝗮𝘁𝗵