cs230.stanford.educs230.stanford.edu/projects_winter_2019/reports/15811654.pdf · 2019-04-04 · Using preprocessing code provided by Kuleshov et al.'s GitHub repositoryl , I generated
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CS230 Deep Learningcs230.stanford.edu/projects_winter_2019/reports/15871106.pdf5.0.2 Models Using the retrained Inception ResNet classifier, we ran several experiments to test the
CS230 Deep Learningcs230.stanford.edu/projects_winter_2019/reports/15813172.pdf80/10/10 train, dev, and test splits based on recom- Fig. 1) The Starry Night by Vincent van Gogh [1]
CS230 Deep Learningcs230.stanford.edu/projects_winter_2019/reports/15811993.pdfChallenge[91 on Kaggle, which presents a dataset of user submitted photos of restaurants and 9 possible
CS230 Deep Learningcs230.stanford.edu/projects_winter_2019/reports/15809694.pdfexisting previous piece of artwork in a personalized manner. In our method, we alter an existing piece
CS230 Deep Learningcs230.stanford.edu/projects_spring_2018/reports/8290634.pdf · alternative of rating food photos' attractiveness to Yelp's published approach that utilized EXIF
CS230 Deep Learningcs230.stanford.edu/projects_fall_2018/reports/12437786.pdf · ANET achieved 0.87 recall rate across all test cases. CS230: Deep Learning, Fall 2018, Stanford University,
CS230 Deep Learningcs230.stanford.edu/projects_winter_2019/reports/15811878.pdf · striker (offensive agent) and goalie (defensive agent), we explore how agents can ... formation
Midterm Review - CS230 Deep Learningcs230.stanford.edu/fall2018/midterm_review.pdf · Midterm Review CS230 Fall 2018. Broadcasting. Calculating Means How would you calculate the means
cs230.stanford.educs230.stanford.edu/projects_winter_2019/reports/15766721.pdf · and representations of the results), media monitoring, newsletters, social media marketing, question
CS230 Deep Learningcs230.stanford.edu/projects_winter_2019/reports/15791197.pdf3.1 Manga The manga dataset is a subset of Manga109 [9], [8]. Manga109 consists of manga pages from 109
cs230.stanford.educs230.stanford.edu/projects_winter_2019/posters/15811897.pdfdeep reinforcement learning networks to play simple cooperative games. This project utilizes a simulated
CS230 Deep Learningcs230.stanford.edu/projects_spring_2018/reports/8290433.pdf · Stanford University {zhaozhuo, zhiyuan8, edu Abstract Damage of building is an essential indicator
CS230 Deep Learningcs230.stanford.edu/projects_spring_2019/reports/18681615.pdfStanford University 1050 Arastradero Rd., Stanford, CA kkaganov [ at ] stanford.edu Abstract In order
CS230 Deep Learningcs230.stanford.edu/projects_winter_2019/reports/15811843.pdfincluding flipping, cropping, rotating, and etc. MOM Figure 1. Sample image of Bart Simpson, Homer Simpson
CS230 Deep Learningcs230.stanford.edu/projects_winter_2019/reports/15806104.pdf · Description 3 inputs, 1 hidden layer, 100 units 3 inputs, 1 hidden layer, 100 units 4 inputs, 1
CS230 Deep Learningcs230.stanford.edu/projects_winter_2019/reports/15812583.pdfwith 1,716 car models. The full car images are labeled with bounding boxes and viewpoints. Each car model
cs230.stanford.educs230.stanford.edu/projects_winter_2019/reports/15802276.pdf · each artist. The resulting model attained good performance over the baseline, and provided subjectively