114 citations · 131 across the 5 of their papers we have counts for
6 papers · 1 filter
Local Context Normalization: Revisiting Local Normalization
Anthony Ortiz, Caleb Robinson, Dan Morris +4
Normalization layers have been shown to improve convergence in deep neural networks, and even add useful inductive biases. In many vision applications the local spatial context of…
A deep active learning system for species identification and counting in camera trap images
Mohammad Sadegh Norouzzadeh, Dan Morris, Sara Beery +3
Biodiversity conservation depends on accurate, up-to-date information about wildlife population distributions. Motion-activated cameras, also known as camera traps, are a critical…
The iWildCam 2019 Challenge Dataset
Sara Beery, Dan Morris, Pietro Perona
Camera Traps (or Wild Cams) enable the automatic collection of large quantities of image data. Biologists all over the world use camera traps to monitor biodiversity and population…
Efficient Pipeline for Camera Trap Image Review
Sara Beery, Dan Morris, Siyu Yang
Biologists all over the world use camera traps to monitor biodiversity and wildlife population density. The computer vision community has been making strides towards automating the…
Human-Machine Collaboration for Fast Land Cover Mapping
Caleb Robinson, Anthony Ortiz, Kolya Malkin +5
We propose incorporating human labelers in a model fine-tuning system that provides immediate user feedback. In our framework, human labelers can interactively query model predicti…
Synthetic Examples Improve Generalization for Rare Classes
Sara Beery, Yang Liu, Dan Morris +5
The ability to detect and classify rare occurrences in images has important applications - for example, counting rare and endangered species when studying biodiversity, or detectin…