no code implementations • 8 Jul 2022 • HaoYu Yang, Zongyi Li, Kumara Sastry, Saumyadip Mukhopadhyay, Anima Anandkumar, Brucek Khailany, Vivek Singh, Haoxing Ren
Machine learning techniques have been extensively studied for mask optimization problems, aiming at better mask printability, shorter turnaround time, better mask manufacturability, and so on.
no code implementations • 12 Mar 2022 • HaoYu Yang, Zongyi Li, Kumara Sastry, Saumyadip Mukhopadhyay, Mark Kilgard, Anima Anandkumar, Brucek Khailany, Vivek Singh, Haoxing Ren
Lithography simulation is a critical step in VLSI design and optimization for manufacturability.
no code implementations • 8 May 2020 • Walid Bekhtaoui, Ruhan Sa, Brian Teixeira, Vivek Singh, Klaus Kirchberg, Yao-jen Chang, Ankur Kapoor
Point cloud based methods have produced promising results in areas such as 3D object detection in autonomous driving.
1 code implementation • 2 Aug 2019 • Brian Teixeira, Birgi Tamersoy, Vivek Singh, Ankur Kapoor
Landmark localization is a challenging problem in computer vision with a multitude of applications.
Ranked #8 on Facial Landmark Detection on 300W
no code implementations • 29 Mar 2019 • Elena Balashova, Jiangping Wang, Vivek Singh, Bogdan Georgescu, Brian Teixeira, Ankur Kapoor
Automatic delineation and measurement of main organs such as liver is one of the critical steps for assessment of hepatic diseases, planning and postoperative or treatment follow-up.
no code implementations • 8 Nov 2018 • Xiaoxiao Li, Vivek Singh, Yifan Wu, Klaus Kirchberg, James Duncan, Ankur Kapoor
Tracking organ motion is important in image-guided interventions, but motion annotations are not always easily available.
no code implementations • 4 Aug 2018 • Elena Balashova, Vivek Singh, Jiangping Wang, Brian Teixeira, Terrence Chen, Thomas Funkhouser
We propose a new procedure to guide training of a data-driven shape generative model using a structure-aware loss function.
no code implementations • CVPR 2018 • Brian Teixeira, Vivek Singh, Terrence Chen, Kai Ma, Birgi Tamersoy, Yifan Wu, Elena Balashova, Dorin Comaniciu
Furthermore, the synthetic X-ray image is parametrized and can be manipulated by adjusting a set of body markers which are also generated during the X-ray image prediction.
no code implementations • CVPR 2016 • Venkatesh N. Murthy, Vivek Singh, Terrence Chen, R. Manmatha, Dorin Comaniciu
During the learning phase, starting from the root network node, DDN automatically builds a network that splits the data into disjoint clusters of classes which would be handled by the subsequent expert networks.