4 papers
HyperCLIP: Adapting Vision-Language models with Hypernetworks
Victor Akinwande, Mohammad Sadegh Norouzzadeh, Devin Willmott +3
Self-supervised vision-language models trained with contrastive objectives form the basis of current state-of-the-art methods in AI vision tasks. The success of these models is a d…
Dynamic Batch Norm Statistics Update for Natural Robustness
Shahbaz Rezaei, Mohammad Sadegh Norouzzadeh
DNNs trained on natural clean samples have been shown to perform poorly on corrupted samples, such as noisy or blurry images. Various data augmentation methods have been recently p…
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…
Automatically identifying, counting, and describing wild animals in camera-trap images with deep learning
Mohammed Sadegh Norouzzadeh, Anh Nguyen, Margaret Kosmala +4
Having accurate, detailed, and up-to-date information about the location and behavior of animals in the wild would revolutionize our ability to study and conserve ecosystems. We in…