개발 공부

#overview-Loss function : takes in a w, looks at the scores and tells us how bad quantitatively is that w.-optimization : coming up with best w through loss function #Loss function support vector machine(SVM) binary SVM multi-class SVM Loss -- is image(pixel)- is (integer) label : expecting category --Ss are the predicted scores for the classes that are coming out of the classifier.- : score of ..

#Image Classification : core task in Computer Vision -the problem : Semantic Gap -chanllenges: Viewpoint variation - all pixels change when the camera moves: Illumination - 명암: Deformation - 다양한 포즈: Occlusion - 부분만 보이는 경우: Background Clutter - 배경: Intraclass variation - 여러 종류의 형태로 존재 #An Image Classifier -Data-Driven Approach1. Collect a dataset of images and labels2. Use Machine Learning to tra..

※introduction #computer vision - study of visual data-censor(smartphones) -> visual data exploded #statistics (2015 study of cisco)2017 -> 80% traffic of internet will be video-pure bits perspective -visual data #problem dark matter(astonishingly large fraction of the universe) of the internet - difficult for the algorithm to go in and understand and see what is comprising all the visual data. #..