cs230.stanford.educs230.stanford.edu/projects_spring_2018/reports/8290559.pdf · Dota 2 is a wildly...

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Transcript of cs230.stanford.educs230.stanford.edu/projects_spring_2018/reports/8290559.pdf · Dota 2 is a wildly...

Page 1: cs230.stanford.educs230.stanford.edu/projects_spring_2018/reports/8290559.pdf · Dota 2 is a wildly popular online five-on-five video game with a rich competitive scene. In every
Page 2: cs230.stanford.educs230.stanford.edu/projects_spring_2018/reports/8290559.pdf · Dota 2 is a wildly popular online five-on-five video game with a rich competitive scene. In every
Page 3: cs230.stanford.educs230.stanford.edu/projects_spring_2018/reports/8290559.pdf · Dota 2 is a wildly popular online five-on-five video game with a rich competitive scene. In every
Page 4: cs230.stanford.educs230.stanford.edu/projects_spring_2018/reports/8290559.pdf · Dota 2 is a wildly popular online five-on-five video game with a rich competitive scene. In every
Page 5: cs230.stanford.educs230.stanford.edu/projects_spring_2018/reports/8290559.pdf · Dota 2 is a wildly popular online five-on-five video game with a rich competitive scene. In every
Page 6: cs230.stanford.educs230.stanford.edu/projects_spring_2018/reports/8290559.pdf · Dota 2 is a wildly popular online five-on-five video game with a rich competitive scene. In every

cs230.stanford.educs230.stanford.edu/projects_winter_2019/reports/15811350.pdf · Monet painting to photo task. We gather Monet paintings both from the internet and from Wikiart.org.

cs230.stanford.educs230.stanford.edu/projects_winter_2019/reports/15811350.pdf · Monet painting to photo task. We gather Monet paintings both from the internet and from Wikiart.org.

cs230.stanford.educs230.stanford.edu/projects_winter_2019/reports/15813424.pdf · [1] Alexander Toshev and Christian Szegedy. Deeppose: Human pose estimation via deep neural networks.

cs230.stanford.educs230.stanford.edu/projects_winter_2019/reports/15813424.pdf · [1] Alexander Toshev and Christian Szegedy. Deeppose: Human pose estimation via deep neural networks.

cs230.stanford.educs230.stanford.edu/projects_spring_2019/reports/18680300.pdfThe following equation gives the final probability density function (pdf) to predict the network output

cs230.stanford.educs230.stanford.edu/projects_spring_2019/reports/18680300.pdfThe following equation gives the final probability density function (pdf) to predict the network output

cs230.stanford.educs230.stanford.edu/projects_spring_2019/reports/18679631.pdf · 2019-06-13 · train v2.csv - the updated training set - contains user transactions from August 1st

cs230.stanford.educs230.stanford.edu/projects_spring_2019/reports/18679631.pdf · 2019-06-13 · train v2.csv - the updated training set - contains user transactions from August 1st

cs230.stanford.educs230.stanford.edu/projects_spring_2018/reports/8289614.pdfduration, or only textual features, such as project description and keywords. To our knowledge, we are

cs230.stanford.educs230.stanford.edu/projects_spring_2018/reports/8289614.pdfduration, or only textual features, such as project description and keywords. To our knowledge, we are

cs230.stanford.educs230.stanford.edu/projects_spring_2018/reports/8288669.pdf · Hiro Tien (Kai Ping) Stanford Graduate School of Business Stanford School of Earth, Energy & Environmental

cs230.stanford.educs230.stanford.edu/projects_spring_2018/reports/8288669.pdf · Hiro Tien (Kai Ping) Stanford Graduate School of Business Stanford School of Earth, Energy & Environmental

cs230.stanford.educs230.stanford.edu › projects_winter_2019 › posters › 15794817.pdf · on the signal of similar pixels2. Here we use the scikit-image fast-mode implementation

cs230.stanford.educs230.stanford.edu › projects_winter_2019 › posters › 15794817.pdf · on the signal of similar pixels2. Here we use the scikit-image fast-mode implementation

web.stanford.eduweb.stanford.edu/class/cs230/projects_spring_2018/... · Medical diagnostics with retinal images is an active area of research in the deep- learning community. Building

web.stanford.eduweb.stanford.edu/class/cs230/projects_spring_2018/... · Medical diagnostics with retinal images is an active area of research in the deep- learning community. Building

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

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

CS230 Deep Learningcs230.stanford.edu/projects_spring_2018/reports/8271110.pdf · 2018. 9. 28. · reconstruction using e.g. template fitting. None of these methods are fully satisfactory

CS230 Deep Learningcs230.stanford.edu/projects_spring_2018/reports/8271110.pdf · 2018. 9. 28. · reconstruction using e.g. template fitting. None of these methods are fully satisfactory

cs230.stanford.educs230.stanford.edu/projects_spring_2019/reports/18676218.pdfProblem Statement: The purpose of this project was to create a system - based on neural networks - that

cs230.stanford.educs230.stanford.edu/projects_spring_2019/reports/18676218.pdfProblem Statement: The purpose of this project was to create a system - based on neural networks - that

cs230.stanford.educs230.stanford.edu/projects_winter_2019/reports/15813002.pdf · global education equity (4). CS230: Deep Learning, Winter 2019, Stanford ... To evolve beyond our

cs230.stanford.educs230.stanford.edu/projects_winter_2019/reports/15813002.pdf · global education equity (4). CS230: Deep Learning, Winter 2019, Stanford ... To evolve beyond our

cs230.stanford.educs230.stanford.edu/projects_fall_2018/reports/12447290.pdf · Emanuel Mendiola emanuelm@stanf ord. edu As techniques for creating photo realistic imagery evolve,

cs230.stanford.educs230.stanford.edu/projects_fall_2018/reports/12447290.pdf · Emanuel Mendiola emanuelm@stanf ord. edu As techniques for creating photo realistic imagery evolve,

cs230.stanford.educs230.stanford.edu/projects_winter_2019/reports/15802990.pdf · 2019-04-04 · Both regression and classification approaches have been used to address issue of fake

cs230.stanford.educs230.stanford.edu/projects_winter_2019/reports/15802990.pdf · 2019-04-04 · Both regression and classification approaches have been used to address issue of fake

cs230.stanford.educs230.stanford.edu/projects_spring_2019/reports/18681618.pdf · Tool detection:Used Fast-RCNN for spatial detection of surgical tools and VGG16 for classification

cs230.stanford.educs230.stanford.edu/projects_spring_2019/reports/18681618.pdf · Tool detection:Used Fast-RCNN for spatial detection of surgical tools and VGG16 for classification

CS230 Deep Learningcs230.stanford.edu/projects_spring_2018/reports/8289231.pdf · high gesture classification accuracy can be achieved using a convolutional neural network trained

CS230 Deep Learningcs230.stanford.edu/projects_spring_2018/reports/8289231.pdf · high gesture classification accuracy can be achieved using a convolutional neural network trained

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_2018/reports/8290433.pdf · Stanford University {zhaozhuo, zhiyuan8, edu Abstract Damage of building is an essential indicator

cs230.stanford.educs230.stanford.edu/projects_spring_2018/reports/8284387.pdf · 2018-09-28 · these phrases are consistent with the English language, the output does not represent

cs230.stanford.educs230.stanford.edu/projects_spring_2018/reports/8284387.pdf · 2018-09-28 · these phrases are consistent with the English language, the output does not represent

cs230.stanford.educs230.stanford.edu/projects_spring_2019/reports/18675538.pdfconvolutional neural networks. " Convolutional Neural Networks for Visual Recognition 2 (2016). [3] Sharma,

cs230.stanford.educs230.stanford.edu/projects_spring_2019/reports/18675538.pdfconvolutional neural networks. " Convolutional Neural Networks for Visual Recognition 2 (2016). [3] Sharma,

web.stanford.eduweb.stanford.edu/class/cs230/projects_spring_2018/... · 50 image as input, and generate a higher resolution 250 x 250 output image. 2. Related Work This project was

web.stanford.eduweb.stanford.edu/class/cs230/projects_spring_2018/... · 50 image as input, and generate a higher resolution 250 x 250 output image. 2. Related Work This project was