Dragomir Anguelov and Christian Szegedy - Free people check

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SSD: Single Shot MultiBox Detector (UPC Reading Group)

www.slideshare.net

Slides by Míriam Bellver at the UPC Reading group for the paper: Liu, Wei, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, and Scott Reed.

[ ] Scalable Object Detection using Deep Neural Networks

arxiv.org

· Title: Scalable Object Detection using Deep Neural Networks. Authors: Dumitru Erhan, Christian Szegedy, Alexander Toshev, Dragomir Anguelov

CiteSeerX — SSD: Single Shot MultiBox Detector

citeseerx.ist.psu.edu

by Wei Liu , Dragomir Anguelov , Dumitru Erhan , Christian Szegedy , Scott Reed ... author = {Wei Liu and Dragomir Anguelov and Dumitru Erhan and Christian ...

[ ] Going Deeper with Convolutions

arxiv.org

Title: Going Deeper with Convolutions. Authors: Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, ...

Wikipedia: Deep Dream - Wikipedia

Deep Dream è un programma di visione artificiale creato da Google che utilizza una rete ... EN ) Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke e Andrew ...

All web results to the name "Dragomir Anguelov"

Dumitru Erhan - Research at Google

research.google

Wei Liu, Dragomir Anguelov, Dumitru Erhan ... Scott E. Reed, Honglak Lee, Dragomir Anguelov, Christian Szegedy, Dumitru Erhan, Andrew Rabinovich. ICLR 2015

Research Blog: High Quality Object Detection at Scale

ai.googleblog.com

Google Engineers Christian Szegedy, Scott Reed *, Dumitru Erhan, and Dragomir Anguelov Update We recently discovered a bug in the evaluation …

Awesome Deep Vision | Curated list of awesome lists |...

project-awesome.org

Wei Liu1, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott Reed, Cheng-Yang Fu, Alexander C. Berg, SSD: Single Shot MultiBox Detector, arXiv: Speed/accuracy trade-offs for modern convolutional object detectors [Paper]. Jonathan Huang, Vivek Rathod, Chen Sun, Menglong Zhu, Anoop ...

CS Cornell Computer Science - Cornell University

www.cs.cornell.edu

(1st place) GoogLeNet Team: "Going deeper with convolutions" Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, Andrew Rabinovich. [PDF]. (2nd place) VGG Team: "Very Deep Convolutional Networks for Large-Scale Image Recognition" ...

CVPR Open Access Repository

www.cv-foundation.org

Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, Andrew Rabinovich; The IEEE ...

Going Deeper with Convolutions – Google AI

research.google

@inproceedings{43022, title = {Going Deeper with Convolutions}, author = {Christian Szegedy and Wei Liu and Yangqing Jia and Pierre Sermanet and Scott Reed and Dragomir Anguelov and Dumitru Erhan and Vincent Vanhoucke and Andrew Rabinovich}, year = {2015}, URL = {http://arxiv.org/abs }, booktitle ...

NSF Award Search: Award# CAREER: Situated Recognition:...

www.nsf.gov

Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott Reed, Cheng-Yang Fu, Alexander C. Berg. "SSD: Single Shot MultiBox ...

Pretrained CNNs - MatConvNet - VLFeat

www.vlfeat.org

imagenet-resnet-50-dag; imagenet-resnet-101-dag; imagenet-resnet-152-dag. GoogLeNet model imported from the Princeton version [DagNN format]. `Going Deeper with Convolutions', Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, ...

SSD (Single Shot Multibox Detector) — ChainerCV documentation

chainercv.readthedocs.io

[1], Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott Reed, Cheng-Yang Fu, Alexander C. Berg. SSD: Single Shot MultiBox Detector. ECCV

Scott Reed

www.scottreed.info

Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, Andrew Rabinovich In IEEE Computer Vision and Pattern Recognition (CVPR), Boston, USA, Related Google Research Blog: Building a deeper understanding of images. Learning to ...