mirror of
https://github.com/zoo-apps/papers.git
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zeekayandHanzo Dev
6658236499
Leadership and team cards, board and founding prose, an AI persona modelled on a named individual, contributor and partner entries, and personal correspondence addresses all named one person. The organisation carries them now. Other people keep their names. Where a card, a board list or a founding line named someone else alongside, they stay exactly as they were; only the one entry was removed, and prose that listed two names now reads with one. Sample and fixture data uses the placeholder name these tests already use elsewhere, so the IAM username defect the notes describe still reads as written. The zoo/yapp MIT notice names the foundation that publishes it. Co-authored-by: Hanzo Dev <[email protected]>
82 lines
3.3 KiB
TeX
82 lines
3.3 KiB
TeX
\documentclass[11pt,letterpaper]{article}
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\usepackage{shared/zoocover}
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% Packages
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\usepackage[utf8]{inputenc}
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\usepackage[T1]{fontenc}
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\usepackage{amsmath,amssymb,amsthm}
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\usepackage{algorithm}
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\usepackage{algorithmic}
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\usepackage{graphicx}
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\usepackage{hyperref}
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\usepackage{xcolor}
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\usepackage{booktabs}
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\usepackage{tikz}
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\usetikzlibrary{shapes,arrows,positioning,calc}
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\usepackage{listings}
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\usepackage{caption}
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\usepackage{subcaption}
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% geometry loaded by zoocover
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\usepackage{multirow}
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\usepackage{enumitem}
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% Theorem environments
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\newtheorem{theorem}{Theorem}[section]
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\newtheorem{lemma}[theorem]{Lemma}
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\newtheorem{proposition}[theorem]{Proposition}
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\newtheorem{corollary}[theorem]{Corollary}
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\newtheorem{definition}{Definition}[section]
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\newtheorem{example}{Example}[section]
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% Custom commands
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\newcommand{\Zoo}{\textsc{Zoo}}
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\newcommand{\ConservAI}{\textsc{ConservAI}}
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\newcommand{\mAP}{\text{mAP}}
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\newcommand{\IoU}{\text{IoU}}
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\newcommand{\FPR}{\text{FPR}}
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% Hyperref setup
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\hypersetup{
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colorlinks=true,
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linkcolor=blue,
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citecolor=blue,
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urlcolor=blue
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}
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% Title
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\title{\textbf{Conservation AI: Deep Learning for Wildlife Population\\Monitoring and Habitat Assessment}\\
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\large Antje Worring, Zoo Labs Foundation Paper ZOO-2026-001}
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\author{
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Antje Worring, Zoo Labs Foundation Research\\
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\texttt{[email protected]}\\[6pt]
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\textit{Antje Worring, Zoo Labs Foundation Research (501c3)}\\
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\url{https://zoo.ngo}
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}
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\date{November 2022}
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\begin{document}
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\zoocoverpage
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\begin{abstract}
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Camera trap networks produce millions of images annually across global conservation sites, yet the vast majority remain unprocessed due to the labor-intensive nature of manual species identification. We present \ConservAI{}, an integrated deep learning pipeline for automated wildlife population monitoring and habitat quality assessment built on the \Zoo{} decentralized science infrastructure. Our system combines a hierarchical species recognition model achieving 96.3\% top-1 accuracy across 847 species, a density-aware population estimation module with 8.2\% mean absolute error on standardized transects, and a multi-spectral habitat quality index derived from satellite imagery fused with ground-truth camera trap observations. The architecture employs a novel \emph{Temporal Context Attention} mechanism that leverages sequential camera trap activations to disambiguate visually similar species and reject false triggers with 99.1\% precision. We evaluate on the Snapshot Serengeti, Wildlife Insights, and LILA BC benchmark datasets, demonstrating state-of-the-art performance while requiring 3.7$\times$ less compute than comparable systems. All models, training code, and evaluation protocols are released as open-source components of the \Zoo{} Data Commons.
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\textbf{Keywords}: camera trap analysis, species recognition, population estimation, habitat assessment, conservation AI, decentralized science
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\end{abstract}
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\tableofcontents
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\input{sections/01-introduction}
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\input{sections/02-related-work}
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\input{sections/03-system-architecture}
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\input{sections/04-experimental-evaluation}
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\input{sections/05-decentralized-deployment-on-zoo-infrastr}
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\input{sections/06-case-study-serengeti-ecosystem-assessmen}
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\input{sections/07-limitations-and-future-work}
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\input{sections/08-conclusion}
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\input{sections/99-acknowledgments}
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\end{document}
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