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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 Deep Learningcs230.stanford.edu/projects_winter_2019/reports/15813380.pdf · CS230 Final Project: Milestone Topic: Transfer Learning Ajay Sohmshetty (collaboration with Amir
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/15782416.pdf · analysis of the models results can be found in the Discussion section. ... and a recognizing textual
CS230 Deep Learningcs230.stanford.edu/projects_winter_2019/reports/15812441.pdfStackGAN managed to generate more realistic, higher resolution images by splitting the problem into two
cs230.stanford.educs230.stanford.edu/projects_spring_2018/reports/8270111.pdf · With our efforts through this quarter, we have successfully built a speaker identification algorithm
CS230 Deep Learningcs230.stanford.edu/projects_winter_2019/reports/15782825.pdf · Generative Adversarial Networks (GANs) [Goodfellow et al, 2014; Isola et al, 2017] and Variational
cs230.stanford.educs230.stanford.edu/projects_winter_2019/reports/15813330.pdf · According to the Federal Statistics Office, 2013, the number of newly opened insolvency proceedings
cs230.stanford.educs230.stanford.edu/projects_spring_2019/reports/18681243.pdf · connected layers to obtain their object category and confidence level. We keep all the patches with
cs230.stanford.educs230.stanford.edu/projects_spring_2018/reports/8291220.pdf · Much of the published research on applying DL techniques in financial market applications is based
CS230 Deep Learningcs230.stanford.edu/projects_winter_2019/reports/15813329.pdf · from a 2019 Kaggle Competition*. The latest model achieved 97.2% accuracy against the test set
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_winter_2019/posters/15811897.pdfdeep reinforcement learning networks to play simple cooperative games. This project utilizes a simulated
cs230.stanford.educs230.stanford.edu/projects_spring_2018/posters/8285130.pdf · Image Restoration of Noisy and Low-Quality Retinal Images Katherine Sytwul, Fariah Hayee2 Dept. of
cs230.stanford.educs230.stanford.edu/projects_winter_2019/reports/15813480.pdf · 2019-04-04 · Yog.ai: Anna Lai alai2@stanf ord.edu Deep Learning for Yoga Bhargav Reddy brkreddy@stanf
cs230.stanford.educs230.stanford.edu/projects_spring_2019/reports/18681189.pdfMore broadly our project is part of the growing field of object detection and classification. A future
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/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/18679631.pdf · 2019-06-13 · train v2.csv - the updated training set - contains user transactions from August 1st
cs230.stanford.educs230.stanford.edu/projects_winter_2019/reports/15766721.pdf · and representations of the results), media monitoring, newsletters, social media marketing, question
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_2018/reports/8289547.pdf · MOOCs and online courses have notoriously high attrition [1]. One challenge is ... a student's performance
CS230 Deep Learningcs230.stanford.edu/projects_winter_2019/reports/15812470.pdf · upon them by pursuing deep learning techniques. Using techniques like LSTMs, RNNs, and highway networks,
CS230 Deep Learningcs230.stanford.edu/projects_winter_2019/reports/15806293.pdf · Most sentiment analysis studies in the finance and accounting literature use ... Apple Inc. : ]
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 Deep Learningcs230.stanford.edu/projects_winter_2019/reports/15812222.pdf · 2019-04-04 · Iterative Cloud Point (ICP) with depth information or iterative model matching architecture
CS230 Deep Learningcs230.stanford.edu/projects_winter_2019/reports/15342206.pdfNicole Kidman True Class Michael Jordan Michelle Obama Barack Obama Conclusion/Future Work 88 98 Identifying
cs230.stanford.educs230.stanford.edu/projects_fall_2018/posters/12377987.pdf · U.S. Timely, accurate diagnosis is a critical factor in determining patient outcomes. Currently, pneumonia
cs230.stanford.educs230.stanford.edu/projects_spring_2018/reports/8290434.pdf · A Content-Based Image Retrieval System (CBIR) for eCommerce Purposes Using Deep Neural Networks Lee
CS230 Deep Learningcs230.stanford.edu/projects_winter_2019/reports/15813120.pdf · animated images and applied to images earlier in the creative process. Style images from animated