Search Results for author: Aakash Kaku

Found 10 papers, 7 papers with code

Deep Probability Estimation

no code implementations21 Nov 2021 Sheng Liu, Aakash Kaku, Weicheng Zhu, Matan Leibovich, Sreyas Mohan, Boyang Yu, Haoxiang Huang, Laure Zanna, Narges Razavian, Jonathan Niles-Weed, Carlos Fernandez-Granda

Reliable probability estimation is of crucial importance in many real-world applications where there is inherent (aleatoric) uncertainty.

Autonomous Vehicles Binary Classification +2

Sequence-to-Sequence Modeling for Action Identification at High Temporal Resolution

1 code implementation3 Nov 2021 Aakash Kaku, Kangning Liu, Avinash Parnandi, Haresh Rengaraj Rajamohan, Kannan Venkataramanan, Anita Venkatesan, Audre Wirtanen, Natasha Pandit, Heidi Schambra, Carlos Fernandez-Granda

To address this, we propose a novel approach for high-resolution action identification, inspired by speech-recognition techniques, which is based on a sequence-to-sequence model that directly predicts the sequence of actions.

Action Recognition speech-recognition +2

Intermediate Layers Matter in Momentum Contrastive Self Supervised Learning

1 code implementation NeurIPS 2021 Aakash Kaku, Sahana Upadhya, Narges Razavian

Our analysis reveals that models trained via our approach have higher feature reuse compared to a standard MoCo and learn informative features earlier in the network.

Self-Supervised Learning

An artificial intelligence system for predicting the deterioration of COVID-19 patients in the emergency department

1 code implementation4 Aug 2020 Farah E. Shamout, Yiqiu Shen, Nan Wu, Aakash Kaku, Jungkyu Park, Taro Makino, Stanisław Jastrzębski, Duo Wang, Ben Zhang, Siddhant Dogra, Meng Cao, Narges Razavian, David Kudlowitz, Lea Azour, William Moore, Yvonne W. Lui, Yindalon Aphinyanaphongs, Carlos Fernandez-Granda, Krzysztof J. Geras

In order to verify performance in a real clinical setting, we silently deployed a preliminary version of the deep neural network at New York University Langone Health during the first wave of the pandemic, which produced accurate predictions in real-time.

COVID-19 Diagnosis Decision Making +1

Towards data-driven stroke rehabilitation via wearable sensors and deep learning

no code implementations14 Apr 2020 Aakash Kaku, Avinash Parnandi, Anita Venkatesan, Natasha Pandit, Heidi Schambra, Carlos Fernandez-Granda

Thus, using a combination of IMU-based motion capture and deep learning, we were able to identify primitives automatically.

Be Like Water: Robustness to Extraneous Variables Via Adaptive Feature Normalization

no code implementations10 Feb 2020 Aakash Kaku, Sreyas Mohan, Avinash Parnandi, Heidi Schambra, Carlos Fernandez-Granda

Extraneous variables are variables that are irrelevant for a certain task, but heavily affect the distribution of the available data.


Knee Cartilage Segmentation Using Diffusion-Weighted MRI

1 code implementation4 Dec 2019 Alejandra Duarte, Chaitra V. Hegde, Aakash Kaku, Sreyas Mohan, José G. Raya

We benchmark our model against a human expert test-retest segmentation and conclude that our model is superior for Patellar and Tibial cartilage using dice score as the comparison metric.

Segmentation Test

DARTS: DenseUnet-based Automatic Rapid Tool for brain Segmentation

1 code implementation13 Nov 2019 Aakash Kaku, Chaitra V. Hegde, Jeffrey Huang, Sohae Chung, Xiuyuan Wang, Matthew Young, Alireza Radmanesh, Yvonne W. Lui, Narges Razavian

This is also the first work to include an expert reader study to assess the quality of the segmentation obtained using a deep-learning-based model.

Brain Segmentation Segmentation

Cannot find the paper you are looking for? You can Submit a new open access paper.