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Page 1: CS230 Deep Learningcs230.stanford.edu/projects_fall_2018/reports/12450134.pdf · Multi-object detection is the task of finding objects in an image or video frame, which consists of
Page 2: CS230 Deep Learningcs230.stanford.edu/projects_fall_2018/reports/12450134.pdf · Multi-object detection is the task of finding objects in an image or video frame, which consists of
Page 3: CS230 Deep Learningcs230.stanford.edu/projects_fall_2018/reports/12450134.pdf · Multi-object detection is the task of finding objects in an image or video frame, which consists of
Page 4: CS230 Deep Learningcs230.stanford.edu/projects_fall_2018/reports/12450134.pdf · Multi-object detection is the task of finding objects in an image or video frame, which consists of
Page 5: CS230 Deep Learningcs230.stanford.edu/projects_fall_2018/reports/12450134.pdf · Multi-object detection is the task of finding objects in an image or video frame, which consists of
Page 6: CS230 Deep Learningcs230.stanford.edu/projects_fall_2018/reports/12450134.pdf · Multi-object detection is the task of finding objects in an image or video frame, which consists of

CS230 Deep Learningcs230.stanford.edu/projects_winter_2019/reports/15810428.pdf · Food image classification has many uses in everyday tasks, ranging from search to tagging. In our

CS230 Deep Learningcs230.stanford.edu/projects_winter_2019/reports/15810428.pdf · Food image classification has many uses in everyday tasks, ranging from search to tagging. In our

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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

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CS230 Deep Learningcs230.stanford.edu/projects_fall_2018/reports/12449275.pdf · Amita C. Patil and Rudra S. Bandhu Department of Computer Science Stanford University (amita2, . edu

CS230 Deep Learningcs230.stanford.edu/projects_fall_2018/reports/12449275.pdf · Amita C. Patil and Rudra S. Bandhu Department of Computer Science Stanford University (amita2, . edu

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CS230 Deep Learningcs230.stanford.edu/projects_fall_2018/reports/12439806.pdfDefense of the Ancients (DOT A) 2 is a multiplayer online battle arena (MOBA) game developed by Valve Corporation

CS230 Deep Learningcs230.stanford.edu/projects_fall_2018/reports/12439806.pdfDefense of the Ancients (DOT A) 2 is a multiplayer online battle arena (MOBA) game developed by Valve Corporation

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cs230.stanford.educs230.stanford.edu/projects_fall_2018/reports/12449630.pdf · OpenAI Gym's classic control tasks are less explored. This study aims to present and compare results

cs230.stanford.educs230.stanford.edu/projects_fall_2018/reports/12449630.pdf · OpenAI Gym's classic control tasks are less explored. This study aims to present and compare results

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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_spring_2018/reports/8290634.pdf · alternative of rating food photos' attractiveness to Yelp's published approach that utilized EXIF

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CS230 Deep Learningcs230.stanford.edu/projects_winter_2019/reports/15808904.pdf · Erick Cardenas implemented the Convolutional Baseline model, setup and managed the AWS instances

CS230 Deep Learningcs230.stanford.edu/projects_winter_2019/reports/15808904.pdf · Erick Cardenas implemented the Convolutional Baseline model, setup and managed the AWS instances

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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 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

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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

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

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CS230 Deep Learningcs230.stanford.edu/projects_fall_2018/reports/12449264.pdfadversarial network (GAN) based off of the SRGAN network developed by Ledig et. al [2]. We modified this

CS230 Deep Learningcs230.stanford.edu/projects_fall_2018/reports/12449264.pdfadversarial network (GAN) based off of the SRGAN network developed by Ledig et. al [2]. We modified this

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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 Deep Learningcs230.stanford.edu/projects_winter_2019/reports/15782825.pdf · Generative Adversarial Networks (GANs) [Goodfellow et al, 2014; Isola et al, 2017] and Variational

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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/15812222.pdf · 2019-04-04 · Iterative Cloud Point (ICP) with depth information or iterative model matching architecture

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CS230 Deep Learningcs230.stanford.edu/files_winter_2018/projects/6940460.pdf · also begun exploring deep unsupervised learning methods in the healthcare setting. One example includes

CS230 Deep Learningcs230.stanford.edu/files_winter_2018/projects/6940460.pdf · also begun exploring deep unsupervised learning methods in the healthcare setting. One example includes

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CS230 Deep Learningcs230.stanford.edu/projects_spring_2019/posters/18673358.pdfThe ability to synthesize subsections of large volumes of texts into a concise, summarative format will

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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 Deep Learningcs230.stanford.edu/projects_winter_2019/reports/15806293.pdf · Most sentiment analysis studies in the finance and accounting literature use ... Apple Inc. : ]

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CS230 Deep Learningcs230.stanford.edu/files_winter_2018/projects/6933119.pdf2 Methods: Quantum mechanics as an optimization problem Carleo [2017] outlines a theoretical formulation

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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/15871106.pdf5.0.2 Models Using the retrained Inception ResNet classifier, we ran several experiments to test the

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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

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CS230 Deep Learningcs230.stanford.edu/projects_fall_2018/reports/12450133.pdf · using PERCEPTRON, ADALINE, MADALINE and BACK-PROPAGATION models. It turns out to work fairly well

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CS230 Deep Learningcs230.stanford.edu/projects_winter_2019/reports/15813380.pdf · CS230 Final Project: Milestone Topic: Transfer Learning Ajay Sohmshetty (collaboration with Amir

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cs230.stanford.edu › projects_fall_2018 › reports › ... · 2019-01-16 · 2 Related Work Many work has been ... From the DCGAN loss training curve in Fig.5, we can see that

cs230.stanford.edu › projects_fall_2018 › reports › ... · 2019-01-16 · 2 Related Work Many work has been ... From the DCGAN loss training curve in Fig.5, we can see that

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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/15812470.pdf · upon them by pursuing deep learning techniques. Using techniques like LSTMs, RNNs, and highway networks,

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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

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CS230 Deep Learningcs230.stanford.edu/projects_fall_2018/reports/12447287.pdf · Similarity and tf-idf are insufficient for questions but are more effective for bags of words approaches

CS230 Deep Learningcs230.stanford.edu/projects_fall_2018/reports/12447287.pdf · Similarity and tf-idf are insufficient for questions but are more effective for bags of words approaches

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CS230 Deep Learningcs230.stanford.edu/files_winter_2018/projects/6940506.pdf · OCR focused on historical transcription has been rarely applied on Arabic histor- ical manuscripts

CS230 Deep Learningcs230.stanford.edu/files_winter_2018/projects/6940506.pdf · OCR focused on historical transcription has been rarely applied on Arabic histor- ical manuscripts

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