Jenna Kline

Cross-Modal Corroboration for Annotation-Free Wildlife Monitoring

B Prabhulla Chandran Pillai, Varun Viswapriyan, Christopher Stewart, Tanya Berger-Wolf et autres

Scaling wildlife monitoring for real-world conservation deployments requires automated analysis of smart sensors that operate under severe annotation scarcity. We propose leveraging expert knowledge of species activity patterns as an annotation-free validation signal for multimodal monitoring pipelines. We operationalize agreement as the …

us (code pays fourni par la source)

Poster: An Edge-Native Approach to Behavior-Adaptive Navigation in Drone Systems

Jenna Kline, Rugved Katole, Christopher Stewart

Unmanned aerial vehicles, i.e., drones, are well-suited to monitor wildlife behaviors in remote habitats as they can quickly traverse rough terrain inaccessible to humans. However, drone operators must balance (1) potentially aggressive flight tactics to adequately monitor species of interest against (2) …

us (code pays fourni par la source)

Edge-Native, Behavior-Adaptive Drone System for Wildlife Monitoring

Jenna Kline, Rugved Katole, Tanya Y. Berger-Wolf, Christopher Stewart

Wildlife monitoring with drones must balance competing demands: approaching close enough to capture behaviorally-relevant video while avoiding stress responses that compromise animal welfare and data validity. Human operators face a fundamental attentional bottleneck: they cannot simultaneously control drone operations and monitor vigilance …

us (code pays fourni par la source)

Poster: An Edge-to-Cloud Framework for Vigilance-Adaptive Drones

Penelope Covey, Jenna Kline, Christopher Stewart

We present an edge-computing framework for autonomous drones to evaluate and adapt their missions in real time to minimize vigilant behaviors in monitored wildlife. Autonomous drones are increasingly valuable in ecology for capturing high-resolution videos of individual and group behaviors, yet their …

us (code pays fourni par la source)

Edge-Native, Behavior-Adaptive Drone System for Wildlife Monitoring

Jenna Kline, Rugved Katole, Tanya Y. Berger-Wolf, Christopher Stewart

Wildlife monitoring with drones must balance competing demands: approaching close enough to capture behaviorally-relevant video while avoiding stress responses that compromise animal welfare and data validity. Human operators face a fundamental attentional bottleneck: they cannot simultaneously control drone operations and monitor vigilance …

kabr-tools: Automated Framework for Multi-Species Behavioral Monitoring

Jenna Kline, Maksim Kholiavchenko, Samuel Stevens, Nina van Tiel et autres

A comprehensive understanding of animal behavior ecology depends on scalable approaches to quantify and interpret complex, multidimensional behavioral patterns. Traditional field observations are often limited in scope, time-consuming, and labor-intensive, hindering the assessment of behavioral responses across landscapes. To address this, we …

SmartWilds: Multimodal Wildlife Monitoring Dataset

Jenna Kline, Anirudh Potlapally, Tanishka Wani, RT Katole et autres

We present the first release of SmartWilds, a multimodal wildlife monitoring dataset. SmartWilds is a synchronized collection of drone imagery, camera trap photographs and videos, and bioacoustic recordings collected during summer 2025 at The Wilds safari park in Ohio. This dataset supports …

Studying collective animal behaviour with drones and computer vision

Jenna Kline, Saadia Afridi, Edouard G. A. Rolland, Guy Maalouf et autres

Abstract Drones are increasingly popular for collecting behaviour data of group‐living animals, offering inexpensive and minimally disruptive observation methods. Imagery collected by drones can be rapidly analysed using computer vision techniques to extract information, including behaviour classification, habitat analysis and identification of …

us, dk, de (code pays fourni par la source)

Correction: BaboonLand Dataset: Tracking Primates in the Wild and Automating Behaviour Recognition from Drone Videos

Isla Duporge, Maksym Kholiavchenko, Roi Harel, Scott Wolf et autres

us, de, fr (code pays fourni par la source)

Environment-Aware Dynamic Pruning for Pipelined Edge Inference

Austin O’Quinn, Conor Snedeker, Siyuan Zhang, Jenna Kline

IoT and edge-based inference systems require unique solutions to overcome resource limitations and unpredictable environments. In this paper, we propose an environment-aware dynamic pruning system that handles the unpredictability of edge inference pipelines. While traditional pruning approaches can reduce model footprint and …

us (code pays fourni par la source)

BaboonLand Dataset: Tracking Primates in the Wild and Automating Behaviour Recognition from Drone Videos

Isla Duporge, Maksym Kholiavchenko, Roi Harel, Scott Wolf et autres

us, de, fr (code pays fourni par la source)

WildLive: Near Real-time Visual Wildlife Tracking onboard UAVs

Nguyen Ngoc Dat, Matthew I. Watson, Jenna Kline, Guy Maalouf et autres

Live tracking of wildlife via high-resolution video processing directly onboard drones is widely unexplored and most existing solutions rely on streaming video to ground stations to support navigation. Yet, both autonomous animal-reactive flight control beyond visual line of sight and/or mission-specific individual …