Search Results for author: Niveditha Kalavakonda

Found 5 papers, 1 papers with code

Proceedings of the NeurIPS 2021 Workshop on Machine Learning for the Developing World: Global Challenges

no code implementations10 Jan 2023 Paula Rodriguez Diaz, Tejumade Afonja, Konstantin Klemmer, Aya Salama, Niveditha Kalavakonda, Oluwafemi Azeez, Simone Fobi

These are the proceedings of the 5th workshop on Machine Learning for the Developing World (ML4D), held as part of the Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS) on December 14th, 2021.

WiCV 2022: The Tenth Women In Computer Vision Workshop

no code implementations24 Aug 2022 Doris Antensteiner, Silvia Bucci, Arushi Goel, Marah Halawa, Niveditha Kalavakonda, Tejaswi Kasarla, Miaomiao Liu, Nermin Samet, Ivaxi Sheth

In this paper, we present the details of Women in Computer Vision Workshop - WiCV 2022, organized alongside the hybrid CVPR 2022 in New Orleans, Louisiana.

WiCV 2021: The Eighth Women In Computer Vision Workshop

no code implementations11 Mar 2022 Arushi Goel, Niveditha Kalavakonda, Nour Karessli, Tejaswi Kasarla, Kathryn Leonard, Boyi Li, Nermin Samet and, Ghada Zamzmi

In this paper, we present the details of Women in Computer Vision Workshop - WiCV 2021, organized alongside the virtual CVPR 2021.

Proceedings of the NeurIPS 2020 Workshop on Machine Learning for the Developing World: Improving Resilience

no code implementations12 Jan 2021 Tejumade Afonja, Konstantin Klemmer, Aya Salama, Paula Rodriguez Diaz, Niveditha Kalavakonda, Oluwafemi Azeez

These are the proceedings of the 4th workshop on Machine Learning for the Developing World (ML4D), held as part of the Thirty-fourth Conference on Neural Information Processing Systems (NeurIPS) on Saturday, December 12th 2020.

BIG-bench Machine Learning

2017 Robotic Instrument Segmentation Challenge

3 code implementations18 Feb 2019 Max Allan, Alex Shvets, Thomas Kurmann, Zichen Zhang, Rahul Duggal, Yun-Hsuan Su, Nicola Rieke, Iro Laina, Niveditha Kalavakonda, Sebastian Bodenstedt, Luis Herrera, Wenqi Li, Vladimir Iglovikov, Huoling Luo, Jian Yang, Danail Stoyanov, Lena Maier-Hein, Stefanie Speidel, Mahdi Azizian

In mainstream computer vision and machine learning, public datasets such as ImageNet, COCO and KITTI have helped drive enormous improvements by enabling researchers to understand the strengths and limitations of different algorithms via performance comparison.

Benchmarking Person Re-Identification +2

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