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Current Residents: Department of Surgery: Feinberg School of Medicine Catherine Valukas, MD, MS Undergraduate: University of Iowa Graduate: Northwestern University Medical School: VCU School of Medicine Hometown: Evanston, IL Clinical Interest: Minimally Invasive and bariatric surgery, complex abdominal wall reconstruction Research Interest: Medical Education, quality Improvement, access to and timeliness of care for vulnerable populations and disparities in
3D Convolutional Neural Networks for Human Action Recognition Abstract We consider the fully automated recognition of actions in uncontrolled environment Most existing work relies on domain knowledge to construct complex handcrafted features from inputs In addition, the environments are usually assumed to be controlled Convolu-tional neural networks (CNNs) are a type of deep models that can act directly on the raw inputs, thus automating the process
BiBP_c. dvi - Northwestern University †Shengyang Dai, ‡Mei Han, †Ying Wu, ‡Yihong Gong †EECS Department, Northwestern University, Evanston, IL 60208 ‡NEC Laboratories America, Inc , Cupertino
CAREER MANAGEMENT CENTER - kellogg. northwestern. edu T he Kellogg School of Management at Northwestern University is well known for its emphasis on collaboration and teamwork inside and outside the classroom This same spirit is evident in the school’s partnership with companies and organizations that look to Kellogg for their future leaders Finding the right fit requires a team effort As the front line for that team, the Kellogg Career
Life expectancy in California has not recovered since the pandemic Amid the COVID-19 pandemic, countries around the globe saw unprecedented causalities and increased mortality While many nations have since recovered, new Northwestern University research shows that California has not rebounded to pre-pandemic life expectancy, based on early data obtained from the state
Life Expectancy Drops in California Post-Covid California has not rebounded to pre-pandemic life expectancy, based on early data obtained from the state, according to new research published in AMA Open
BILATERAL BACK-PROJECTION FOR SINGLE IMAGE SUPER RESOLUTION 1 INTRODUCTION The objective of image super resolution (SR) [2] is to obtain high resolution (HR) images from low resolution (LR) inputs It is widely applicable in video communication, object recog-nition, HDTV, image compression, et al In this paper, we mainly focus on the super resolution task given one single low resolution input image
untitled [www. ece. northwestern. edu] Abstract—Designing effective image priors is of great interest to image super-resolution (SR), which is a severely under-deter-mined problem An edge smoothness prior is favored since it is able to suppress the jagged edge artifact effectively However, for soft image edges with gradual intensity transitions, it is generally dif-ficult to obtain analytical forms for evaluating their