tejus-gupta

\begin{figure*}[t]
\begin{center}
\includegraphics[width=1.4in,height=1.4in]{pictures/vgg16_envelope.png}
\hspace{0.2cm}
\includegraphics[width=1.4in,height=1.4in]{pictures/vgg16_horsecart.png}
\hspace{0.2cm}
\includegraphics[width=1.4in,height=1.4in]{pictures/vgg16_tablelamp.png}
\end{center}

\begin{center}

tejus-gupta

\begin{figure*}
\begin{center}
\includegraphics[width=3.132in,height=2.349in]{Figure_1-11.png}
\hspace{0.2cm}
\includegraphics[width=3.132in,height=2.349in]{Figure_1-6.png}
\end{center}


\begin{center}
    \caption{A. (left) Ratio of $i^{th}$ singular value to first singular value of matrix $P$ containing example-wise adversarial perturbations. B. (right) Cosine similarity of our universal perturbation for class '0' with singular vectors of matrix $P$.}

tejus-gupta

\begin{figure}[t]
\begin{center}
\includegraphics[width=1in,height=1in]{images/flute.png}
\hspace{0.1cm}
\includegraphics[width=1in,height=1in]{pictures/adv12.png}
\hspace{0.1cm}
\includegraphics[width=1in,height=1in]{images/carpenter_kit.png}
\end{center}

\begin{center}

tejus-gupta

\begin{figure}[t]
\begin{center}
\includegraphics[width=1in,height=1in]{images/flute.png}
\hspace{0.1cm}
\includegraphics[width=1in,height=1in]{pictures/adv12.png}
\hspace{0.1cm}
\includegraphics[width=1in,height=1in]{images/carpenter_kit.png}
\hspace{0.1cm}
\includegraphics[width=1in,height=1in]{images/iron.png}
\end{center}

tejus-gupta

using Images, TestImages, Statistics, BenchmarkTools, Test

img = testimage("lena_gray")

function median_filter_multilevel(img::Array{Gray{Normed{T,f}}, 2}, window_size::Tuple{Int64,Int64}) where {T,f}

    nlevels = 2^f
    course_nlevels = 2^(f>>1)
    bin_bits = f>>1

tejus-gupta

import requests

def download_file_from_google_drive(id, destination):
    def get_confirm_token(response):
        for key, value in response.cookies.items():
            if key.startswith('download_warning'):
                return value

        return None

tejus-gupta

using Images, TestImages, Statistics, BenchmarkTools, Test

img = testimage("lena_gray")
high_resolution_img = convert(Array{Gray{Normed{UInt16,16}}, 2}, img)

function median_filter(img::Array{Gray{Normed{T,f}}, 2}, window_size::Tuple{Int64,Int64}) where {T,f}

    function update_median(median_val, n_pixels_below_median, hist, half_pixels)
        if n_pixels_below_median <= half_pixels
            for val in median_val:2^f

tejus-gupta

📋 Project overview: Parallelizing Apollo

Status	Just starting 🌱 / In progress 🔨 / Ready to go 🚀
Team	Start with you and add others with @mentions
Description	What do you have in mind?
Deadline	When do you want to finish?

Timeline

• What are the key dates?

tejus-gupta

Automated Fiducial Localization

tejus-gupta

#include <pcl/visualization/cloud_viewer.h>

boost::shared_ptr<pcl::visualization::PCLVisualizer> cloudVis (pcl::PointCloud<pcl::PointXYZ>::ConstPtr cloud)
{
  boost::shared_ptr<pcl::visualization::PCLVisualizer> viewer (new pcl::visualization::PCLVisualizer ("3D Viewer"));
  viewer->setBackgroundColor (0, 0, 0);
  viewer->addPointCloud<pcl::PointXYZ> (cloud, "sample cloud");
  viewer->setPointCloudRenderingProperties (pcl::visualization::PCL_VISUALIZER_POINT_SIZE, 1, "sample cloud");
  viewer->addCoordinateSystem (1.0);
  viewer->initCameraParameters ();