3 citations · 9 across the 22 of their papers we have counts for
6 papers · 1 filter
Eroding Trust In Aerial Imagery: Comprehensive Analysis and Evaluation Of Adversarial Attacks In Geospatial Systems
Michael Lanier, Aayush Dhakal, Zhexiao Xiong +3
In critical operations where aerial imagery plays an essential role, the integrity and trustworthiness of data are paramount. The emergence of adversarial attacks, particularly tho…
LD-SDM: Language-Driven Hierarchical Species Distribution Modeling
Srikumar Sastry, Xin Xing, Aayush Dhakal +3
We focus on species distribution modeling using global-scale presence-only data, leveraging geographical and environmental features to map species ranges, as in previous studies. H…
A Partially Supervised Reinforcement Learning Framework for Visual Active Search
Anindya Sarkar, Nathan Jacobs, Yevgeniy Vorobeychik
Visual active search (VAS) has been proposed as a modeling framework in which visual cues are used to guide exploration, with the goal of identifying regions of interest in a large…
BirdSAT: Cross-View Contrastive Masked Autoencoders for Bird Species Classification and Mapping
Srikumar Sastry, Subash Khanal, Aayush Dhakal +2
We propose a metadata-aware self-supervised learning~(SSL)~framework useful for fine-grained classification and ecological mapping of bird species around the world. Our framework u…
Vision-Language Pseudo-Labels for Single-Positive Multi-Label Learning
Xin Xing, Zhexiao Xiong, Abby Stylianou +3
This paper presents a novel approach to Single-Positive Multi-label Learning. In general multi-label learning, a model learns to predict multiple labels or categories for a single…
FroSSL: Frobenius Norm Minimization for Efficient Multiview Self-Supervised Learning
Oscar Skean, Aayush Dhakal, Nathan Jacobs +1
Self-supervised learning (SSL) is a popular paradigm for representation learning. Recent multiview methods can be classified as sample-contrastive, dimension-contrastive, or asymme…