Ashish Patel 🇮🇳’s Post

𝗗𝗮𝘆-𝟮𝟬𝟳 𝗖𝗼𝗺𝗽𝘂𝘁𝗲𝗿 𝗩𝗶𝘀𝗶𝗼𝗻 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 A Review on Deep Learning Techniques Applied to 𝗦𝗲𝗺𝗮𝗻𝘁𝗶𝗰 𝗦𝗲𝗴𝗺𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻 by Universitat d'Alacant, Spain Follow me for a similar post:  🇮🇳 Ashish Patel Interesting Facts : 🔸 This is a paper in TPAMI 2017 with over 810 citations. 🔸 It's a detailed review of all semantic segmentation techniques. ------------------------------------------------------------------- 𝗔𝗺𝗮𝘇𝗶𝗻𝗴 𝗥𝗲𝘀𝗲𝗮𝗿𝗰𝗵 : https://lnkd.in/eqcsT92 Code : https://lnkd.in/eigeYbb ------------------------------------------------------------------- 𝗜𝗠𝗣𝗢𝗥𝗧𝗔𝗡𝗖𝗘 🔸 Image semantic segmentation is more and more being of interest for computer vision and machine learning researchers. Many applications on the rise need accurate and efficient segmentation mechanisms: autonomous driving, indoor navigation, and even virtual or augmented reality systems to name a few.  🔸 This demand coincides with the rise of deep learning approaches in almost every field or application target related to computer vision, including semantic segmentation or scene understanding. This paper provides a review of deep learning methods for semantic segmentation applied to various application areas. 🔸 Firstly, we describe the terminology of this field as well as mandatory background concepts. Next, the main datasets and challenges are exposed to help researchers decide which are the ones that best suit their needs and their targets.  🔸Then, existing methods are reviewed, highlighting their contributions and their significance in the field. Finally, quantitative results are given for the described methods and the datasets in which they were evaluated, following up with a discussion of the results. 🔸 At last, we point out a set of promising future works and draw our own conclusions about the state of the art of semantic segmentation using deep learning techniques. #computervision #artificialintelligence #deeplearning