18 citations · 18 across the 3 of their papers we have counts for
5 papers
The iWildCam 2021 Competition Dataset
Sara Beery, Arushi Agarwal, Elijah Cole +1
Camera traps enable the automatic collection of large quantities of image data. Ecologists use camera traps to monitor animal populations all over the world. In order to estimate t…
The surprising impact of mask-head architecture on novel class segmentation
Vighnesh Birodkar, Zhichao Lu, Siyang Li +2
Instance segmentation models today are very accurate when trained on large annotated datasets, but collecting mask annotations at scale is prohibitively expensive. We address the p…
A Closed-Form Learned Pooling for Deep Classification Networks
Vighnesh Birodkar, Hossein Mobahi, Dilip Krishnan +1
In modern computer vision tasks, convolutional neural networks (CNNs) are indispensable for image classification tasks due to their efficiency and effectiveness. Part of their supe…
Straight to the point: reinforcement learning for user guidance in ultrasound
Fausto Milletari, Vighnesh Birodkar, Michal Sofka
Point of care ultrasound (POCUS) consists in the use of ultrasound imaging in critical or emergency situations to support clinical decisions by healthcare professionals and first r…
Semantic Redundancies in Image-Classification Datasets: The 10% You Don't Need
Vighnesh Birodkar, Hossein Mobahi, Samy Bengio
Large datasets have been crucial to the success of deep learning models in the recent years, which keep performing better as they are trained with more labelled data. While there h…