Related papers: Harnessing Artificial Intelligence for Wildlife Co…
Recent developments in artificial intelligence (AI) have permeated through an array of different immersive environments, including virtual, augmented, and mixed realities. AI brings a wealth of potential that centers on its ability to…
Artificial Intelligence (AI) is revolutionizing assistive technologies. It offers innovative solutions to enhance the quality of life for individuals with visual impairments. This review examines the development, applications, and impact of…
Knowledge over the number of animals in large wildlife reserves is a vital necessity for park rangers in their efforts to protect endangered species. Manual animal censuses are dangerous and expensive, hence Unmanned Aerial Vehicles (UAVs)…
This paper investigates the issue of real-world identification to fulfill better species protection. We focus on plant species identification as it is a classic and hot issue. In tradition plant species identification the samples are…
The ability of a researcher to re-identify (re-ID) an individual animal upon re-encounter is fundamental for addressing a broad range of questions in the study of ecosystem function, community and population dynamics, and behavioural…
Artificial intelligence (AI) systems are becoming critical components of today's IT landscapes. Their resilience against attacks and other environmental influences needs to be ensured just like for other IT assets. Considering the…
Agriculture faces a growing challenge with wildlife wreaking havoc on crops, threatening sustainability. The project employs advanced object detection, the system utilizes the Mobile Net SSD model for real-time animal classification. The…
Artificial Intelligence is increasingly pervasive across domains, with ever more complex models delivering impressive predictive performance. This fast technological advancement however comes at a concerning environmental cost, with…
The convergence of artificial intelligence (AI) and Earth observation (EO) technologies has brought geoscience and remote sensing into an era of unparalleled capabilities. AI's transformative impact on data analysis, particularly derived…
With the advent of multispectral imagery and AI, there have been numerous works on automatic plant segmentation for purposes such as counting, picking, health monitoring, localized pesticide delivery, etc. In this paper, we tackle the…
Deep artificial neural networks, trained with labeled data sets are widely used in numerous vision and robotics applications today. In terms of AI, these are called reflex models, referring to the fact that they do not self-evolve or…
Artificial intelligence (AI) models trained on published scientific findings have been used to invent valuable materials and targeted therapies, but they typically ignore the human scientists who continually alter the landscape of…
This study revisits the findings of Carl et al., who evaluated the pre-trained Google Inception-ResNet-v2 model for automated detection of European wild mammal species in camera trap images. To assess the reproducibility and…
The urgent need for renewable energy expansion, particularly wind power, is hindered by conflicts with wildlife conservation. To address this, we developed BirdRecorder, an advanced AI-based anti-collision system to protect endangered…
This paper introduces an automated vision system for animal detection in trail-camera images taken from a field under the administration of the Texas Parks and Wildlife Department. As traditional wildlife counting techniques are intrusive…
The threat hunting lifecycle is a complex atmosphere that requires special attention from professionals to maintain security. This paper is a collection of recent work that gives a holistic view of the threat hunting ecosystem, identifies…
Artificial Intelligence (AI) has received tremendous attention from academia, industry, and the general public in recent years. The integration of geography and AI, or GeoAI, provides novel approaches for addressing a variety of problems in…
Atmospheric sciences are crucial for understanding environmental phenomena ranging from air quality to extreme weather events, and climate change. Recent breakthroughs in sensing, communication, computing, and Artificial Intelligence (AI)…
Wildlife populations in Africa face severe threats, with vertebrate numbers declining by over 65% in the past five decades. In response, image classification using deep learning has emerged as a promising tool for biodiversity monitoring…
Life finds a way. For sessile organisms like plants, the need to adapt to changes in the environment is even more poignant. For humanity, the need to develop crops that can grow in diverse environments and feed our growing population is an…