Search Results for author: Sara Beery

Found 15 papers, 5 papers with code

ElephantBook: A Semi-Automated Human-in-the-Loop System for Elephant Re-Identification

no code implementations29 Jun 2021 Peter Kulits, Jake Wall, Anka Bedetti, Michelle Henley, Sara Beery

African elephants are vital to their ecosystems, but their populations are threatened by a rise in human-elephant conflict and poaching.

Image-to-Image Translation of Synthetic Samples for Rare Classes

no code implementations23 Jun 2021 Edoardo Lanzini, Sara Beery

The natural world is long-tailed: rare classes are observed orders of magnitudes less frequently than common ones, leading to highly-imbalanced data where rare classes can have only handfuls of examples.

Classification Image-to-Image Translation

Can poachers find animals from public camera trap images?

no code implementations21 Jun 2021 Sara Beery, Elizabeth Bondi

To protect the location of camera trap data containing sensitive, high-target species, many ecologists randomly obfuscate the latitude and longitude of the camera when publishing their data.

The iWildCam 2021 Competition Dataset

no code implementations7 May 2021 Sara Beery, Arushi Agarwal, Elijah Cole, Vighnesh Birodkar

The challenge is to classify species and count individual animals across sequences in the test cameras.

Object Detection

The iWildCam 2020 Competition Dataset

no code implementations21 Apr 2020 Sara Beery, Elijah Cole, Arvi Gjoka

Can we leverage data from other modalities, such as citizen science data and remote sensing data?

Context R-CNN: Long Term Temporal Context for Per-Camera Object Detection

2 code implementations CVPR 2020 Sara Beery, Guanhang Wu, Vivek Rathod, Ronny Votel, Jonathan Huang

In this paper we propose a method that leverages temporal context from the unlabeled frames of a novel camera to improve performance at that camera.

Video Object Detection Video Understanding

A deep active learning system for species identification and counting in camera trap images

no code implementations22 Oct 2019 Mohammad Sadegh Norouzzadeh, Dan Morris, Sara Beery, Neel Joshi, Nebojsa Jojic, Jeff Clune

However, the accuracy of results depends on the amount, quality, and diversity of the data available to train models, and the literature has focused on projects with millions of relevant, labeled training images.

Active Learning Decision Making +1

The iWildCam 2019 Challenge Dataset

no code implementations15 Jul 2019 Sara Beery, Dan Morris, Pietro Perona

We use the Caltech Camera Traps dataset, collected from the American Southwest, as training data.

Transfer Learning

Efficient Pipeline for Camera Trap Image Review

1 code implementation15 Jul 2019 Sara Beery, Dan Morris, Siyu Yang

Biologists all over the world use camera traps to monitor biodiversity and wildlife population density.

Classification General Classification

Synthetic Examples Improve Generalization for Rare Classes

no code implementations11 Apr 2019 Sara Beery, Yang Liu, Dan Morris, Jim Piavis, Ashish Kapoor, Markus Meister, Neel Joshi, Pietro Perona

The ability to detect and classify rare occurrences in images has important applications - for example, counting rare and endangered species when studying biodiversity, or detecting infrequent traffic scenarios that pose a danger to self-driving cars.

Few-Shot Learning Self-Driving Cars

The iWildCam 2018 Challenge Dataset

no code implementations11 Apr 2019 Sara Beery, Grant van Horn, Oisin Mac Aodha, Pietro Perona

Camera traps are a valuable tool for studying biodiversity, but research using this data is limited by the speed of human annotation.

Recognition in Terra Incognita

1 code implementation ECCV 2018 Sara Beery, Grant van Horn, Pietro Perona

The challenge is learning recognition in a handful of locations, and generalizing animal detection and classification to new locations where no training data is available.

Classification General Classification

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