Ashish Patel 🇮🇳’s Post

Day-64 Computer Vision Learning Cascade R-CNN — Delving into High Quality Object Detection (Object Detection) by UC San Diego Follow me for similar post : 🇮🇳 Ashish Patel Interesting Facts : 🔸 It is published in 2018 CVPR, which has already got over 1002 citations. 🔸 It outperforms YOLOv2, SSD, RetinaNet, Faster R-CNN, FPN, G-RMI, R-FCN, DCNv1 and Mask R-CNN ------------------------------------------------------------------- 𝗔𝗺𝗮𝘇𝗶𝗻𝗴 𝗥𝗲𝘀𝗲𝗮𝗿𝗰𝗵 : https://lnkd.in/eRW2AMu Official Code : https://bit.ly/3bkvwVk tensorflow : https://bit.ly/3cjAKjF pytorch : https://bit.ly/3c3xM2j keras : https://bit.ly/38eWxHP ------------------------------------------------------------------- 𝗜𝗠𝗣𝗢𝗥𝗧𝗔𝗡𝗖𝗘 🔸 Overfitting during training, due to exponentially vanishing positive samples, i.e. lot of positive samples are gone when IoU threshold increases. 🔸 Inference-time mismatch between the IoUs for which the detector is optimal and those of the input hypotheses. e.g.: training at higher(lower) IoU threshold but test at lower(higher) IoU threshold. 🔸 However, the computation could be intensive especially when the number of object proposals is large. #computervision #arttificialintelligence #innovation