1 code implementation • NeurIPS 2023 • Elena Sizikova, Niloufar Saharkhiz, Diksha Sharma, Miguel Lago, Berkman Sahiner, Jana G. Delfino, Aldo Badano
To generate evidence regarding the safety and efficacy of artificial intelligence (AI) enabled medical devices, AI models need to be evaluated on a diverse population of patient cases, some of which may not be readily available.
no code implementations • 14 Dec 2022 • Kun Tang, Xu Cao, Zhipeng Cao, Tong Zhou, Erlong Li, Ao Liu, Shengtao Zou, Chang Liu, Shuqi Mei, Elena Sizikova, Chao Zheng
THMA has been deployed by the Tencent Map team to provide services to downstream companies and users, serving over 1, 000 labeling workers and producing more than 30, 000 kilometers of HD map data per day at most.
1 code implementation • 30 Oct 2022 • Xu Cao, Wenqian Ye, Elena Sizikova, Xue Bai, Megan Coffee, Hongwu Zeng, Jianguo Cao
Research progress in the field of ASD facial analysis in pediatric patients has been hindered due to a lack of well-established baselines.
1 code implementation • 28 Aug 2022 • Elena Sizikova, Joshua Vendrow, Xu Cao, Rachel Grotheer, Jamie Haddock, Lara Kassab, Alona Kryshchenko, Thomas Merkh, R. W. M. A. Madushani, Kenny Moise, Annie Ulichney, Huy V. Vo, Chuntian Wang, Megan Coffee, Kathryn Leonard, Deanna Needell
Automatic infectious disease classification from images can facilitate needed medical diagnoses.
1 code implementation • 23 Aug 2022 • Elena Sizikova, Xu Cao, Ashia Lewis, Kenny Moise, Megan Coffee
Chest computed tomography (CT) imaging adds valuable insight in the diagnosis and management of pulmonary infectious diseases, like tuberculosis (TB).
1 code implementation • 16 Jun 2022 • Ajay Subramanian, Sara Price, Omkar Kumbhar, Elena Sizikova, Najib J. Majaj, Denis G. Pelli
Using FLOPs as an analog for reaction time, we compare networks with humans on curve-fit error, category-wise correlation, and curve steepness, and conclude that cascaded dynamic neural networks are a promising model of human reaction time in object recognition tasks.
1 code implementation • 8 Jun 2022 • Pranav Singh, Elena Sizikova, Jacopo Cirrone
We also show that CASS is much more robust to changes in batch size and training epochs.
Ranked #1 on Classification on Brain Tumor MRI Dataset
no code implementations • 28 Feb 2022 • Jamie Haddock, Lara Kassab, Sixian Li, Alona Kryshchenko, Rachel Grotheer, Elena Sizikova, Chuntian Wang, Thomas Merkh, RWMA Madushani, Miju Ahn, Deanna Needell, Kathryn Leonard
We propose new semi-supervised nonnegative matrix factorization (SSNMF) models for document classification and provide motivation for these models as maximum likelihood estimators.
1 code implementation • 23 Sep 2021 • Ashia Lewis, Evanjelin Mahmoodi, Yuyue Zhou, Megan Coffee, Elena Sizikova
The evaluation of infectious disease processes on radiologic images is an important and challenging task in medical image analysis.
1 code implementation • NeurIPS 2021 • Huy V. Vo, Elena Sizikova, Cordelia Schmid, Patrick Pérez, Jean Ponce
Extensive experiments on COCO and OpenImages show that, in the single-object discovery setting where a single prominent object is sought in each image, the proposed LOD (Large-scale Object Discovery) approach is on par with, or better than the state of the art for medium-scale datasets (up to 120K images), and over 37% better than the only other algorithms capable of scaling up to 1. 7M images.
no code implementations • 25 Nov 2020 • Omkar Kumbhar, Elena Sizikova, Najib Majaj, Denis G. Pelli
We conclude that Anytime classification (i. e. early exits) is a promising model for human reaction time in recognition tasks.
no code implementations • 9 Nov 2020 • Fangyin Wei, Elena Sizikova, Avneesh Sud, Szymon Rusinkiewicz, Thomas Funkhouser
Many applications in 3D shape design and augmentation require the ability to make specific edits to an object's semantic parameters (e. g., the pose of a person's arm or the length of an airplane's wing) while preserving as much existing details as possible.
1 code implementation • 15 Oct 2020 • Jamie Haddock, Lara Kassab, Sixian Li, Alona Kryshchenko, Rachel Grotheer, Elena Sizikova, Chuntian Wang, Thomas Merkh, R. W. M. A. Madushani, Miju Ahn, Deanna Needell, Kathryn Leonard
We propose several new models for semi-supervised nonnegative matrix factorization (SSNMF) and provide motivation for SSNMF models as maximum likelihood estimators given specific distributions of uncertainty.
Ranked #13 on Text Classification on 20NEWS
no code implementations • 30 Jun 2020 • Sahar Siddiqui, Elena Sizikova, Gemma Roig, Najib J. Majaj, Denis G. Pelli
Relative to the attention-based (Attn) model, we discover that the connectionist temporal classification (CTC) model is more robust to noise and occlusion, and better at generalizing to different word lengths.
no code implementations • 2 Jan 2020 • Miju Ahn, Nicole Eikmeier, Jamie Haddock, Lara Kassab, Alona Kryshchenko, Kathryn Leonard, Deanna Needell, R. W. M. A. Madushani, Elena Sizikova, Chuntian Wang
There is currently an unprecedented demand for large-scale temporal data analysis due to the explosive growth of data.