arXiv (All)
open access
BarkNet-Lite: A Lightweight Texture and Colour Network with the BarkBD Benchmark for Bark-Based Tree Species Recognition in Bangladesh
Tree species recognition supports forest inventory and biodiversity monitoring but still depends on scarce taxonomic expertise. Bark is visible year-round at ground level, yet bark recognition has concentrated on temperate floras and on large ImageNet-pre-trained backbones. We address both gaps. Fir
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Knowledge-guided machine learning for predicting the carbon sequestration potential of natural forests in Heilongjiang Province#796445
- Deep Evidential Regression for Sparse Forest Height Estimation from Multimodal Satellite Imagery#1109119
- You only look once-based neural network and grading method for peach leaf shot hole disease detection under natural conditions.#418379
- Analyse des indicateurs forestiers prescrits dans le cadre du Règlement pour la restauration de la nature (RRN) : pertinence pour la biodiversité, faisabilité de leur suivi, situation actuelle et tendances#15486
- Estimating stand metrics in mountainous temperate forests using UAS and satellite imagery: multiple linear regression or artificial neural networks?#347323
Record · ID 984511
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive