AIMC Topic: Biodiversity

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Towards the fully automated monitoring of ecological communities.

Ecology letters
High-resolution monitoring is fundamental to understand ecosystems dynamics in an era of global change and biodiversity declines. While real-time and automated monitoring of abiotic components has been possible for some time, monitoring biotic compon...

Understanding External Influences on Target Detection and Classification Using Camera Trap Images and Machine Learning.

Sensors (Basel, Switzerland)
Using machine learning (ML) to automate camera trap (CT) image processing is advantageous for time-sensitive applications. However, little is currently known about the factors influencing such processing. Here, we evaluate the influence of occlusion,...

The Impact of Data Augmentations on Deep Learning-Based Marine Object Classification in Benthic Image Transects.

Sensors (Basel, Switzerland)
Data augmentation is an established technique in computer vision to foster the generalization of training and to deal with low data volume. Most data augmentation and computer vision research are focused on everyday images such as traffic data. The a...

Revealing the real-time diversity and abundance of small mammals by using an Intelligent Animal Monitoring System (IAMS).

Integrative zoology
It is challenging to reveal the real-time spatio-temporal change of diversity and abundance of animals in natural systems by using traditional methods. The rapid advancement of new technologies such as the Internet of Things, artificial intelligence,...

Meeting sustainable development goals via robotics and autonomous systems.

Nature communications
Robotics and autonomous systems are reshaping the world, changing healthcare, food production and biodiversity management. While they will play a fundamental role in delivering the UN Sustainable Development Goals, associated opportunities and threat...

Maximizing citizen scientists' contribution to automated species recognition.

Scientific reports
Technological advances and data availability have enabled artificial intelligence-driven tools that can increasingly successfully assist in identifying species from images. Especially within citizen science, an emerging source of information filling ...

Lessons from other disciplines for setting management thresholds for biodiversity conservation.

Conservation biology : the journal of the Society for Conservation Biology
Successful, state-dependent management, in which the goal of management is to maintain a system in a desired state, involves defining the boundaries between different states. Once these boundaries have been defined, managers require a strategic actio...

Confronting Deep-Learning and Biodiversity Challenges for Automatic Video-Monitoring of Marine Ecosystems.

Sensors (Basel, Switzerland)
With the availability of low-cost and efficient digital cameras, ecologists can now survey the world's biodiversity through image sensors, especially in the previously rather inaccessible marine realm. However, the data rapidly accumulates, and ecolo...

Modeling CRISPR gene drives for suppression of invasive rodents using a supervised machine learning framework.

PLoS computational biology
Invasive rodent populations pose a threat to biodiversity across the globe. When confronted with these invaders, native species that evolved independently are often defenseless. CRISPR gene drive systems could provide a solution to this problem by sp...

DiversityScanner: Robotic handling of small invertebrates with machine learning methods.

Molecular ecology resources
Invertebrate biodiversity remains poorly understood although it comprises much of the terrestrial animal biomass, most species and supplies many ecosystem services. The main obstacle is specimen-rich samples obtained with quantitative sampling techni...