Research graph
References from YOLO-FSD: A lightweight deep learning framework for crested ibis (Nipponia nippon) detection and segmentation in complex natural environments. Local targets link to admitted publications; unresolved targets remain external evidence.
Evaluate and simulate the reproduction and survival of a reintroduced population in an endangered bird species Crested ibis (Nipponia nippon)
2025 · External reference
Recovery of Japanese crested ibis in Qin-Ling range
1981 · External reference
Reproductive success of the Crested Ibis Nipponia nippon
10.1017/s0959270906000499 · 2006 · External reference
Spatial optimization of ecological-urban interface areas based on Nipponia nippon population dispersal: a case study of Chenggu and Yangxian in Shaanxi Province
2026 · External reference
Unresolved reference
External reference
Birds as bioindicators of environmental health
2025 · External reference
Multi-source remote sensing data for monitoring natural reserves: a case study on the Shaanxi Hanzhong Crested Ibis National Nature Reserve, China
10.1080/17538947.2025.2528655 · 2025 · External reference
Changes in the habitat preference of Crested Ibis (Nipponia nippon) during a period of rapid population increase
10.3390/ani11092626 · 2021 · External reference
Home range and habitat utilization of the crested ibis in the breeding period
2003 · External reference
Post-fledging dispersal and habitat use of a reintroduced population of the Crested Ibis (Nipponia nippon)
10.1186/s40657-014-0007-5 · 2014 · External reference
Evaluation of ongoing Crested Ibis (Nipponia nippon) reintroduction using an integrated population model and bayesian population viability analysis
10.1111/ibi.13071 · 2022 · External reference
Machine and deep learning for wetland mapping and bird-habitat monitoring: a systematic review of remote-sensing applications (2015–April 2025)
10.3390/rs17213605 · 2025 · External reference
Benchmarking wild bird detection in complex forest scenes
10.1016/j.ecoinf.2024.102466 · 2024 · External reference
High accuracy individual identification model of crested ibis (Nipponia nippon) based on autoencoder with self-attention
10.1109/access.2020.2973243 · 2020 · External reference
A methodological literature review of acoustic wildlife monitoring using artificial intelligence tools and techniques
10.3390/su15097128 · 2023 · External reference
CDA-Net: cross dimensional attention network for wetland bird detection
2025 · External reference
DFEFM: fusing frequency correlation and mel features for robust edge bird audio detection
10.1016/j.avrs.2025.100232 · 2025 · External reference
Hierarchical image classification using transfer learning to improve deep learning model performance for amazon parrots
10.1038/s41598-025-88103-3 · 2025 · External reference
Acoustic detection of a nocturnal bird with deep learning: the challenge of low signal-to-noise ratio
10.1016/j.ecolind.2025.114475 · 2025 · External reference
Detection of small birds in large images by combining a deep detector with semantic segmentation
2016 · External reference
Classification of endangered bird species of Nepal using deep learning
10.47001/irjiet/2024.805029 · 2024 · External reference
A temporal boosted YOLO-based model for birds detection around wind farms
10.3390/jimaging7110227 · 2021 · External reference
An improved bird detection method using surveillance videos from Poyang Lake based on YOLOv8
10.3390/ani14233353 · 2024 · External reference
YOLOv11: an overview of the key architectural enhancements
2024 · External reference
Unsupervised bidirectional contrastive reconstruction and adaptive fine-grained channel attention networks for image dehazing
10.1016/j.neunet.2024.106314 · 2024 · External reference
YOLO-FaceV2: a scale and occlusion aware face detector
10.1016/j.patcog.2024.110714 · 2024 · External reference
Generalized Intersection over Union: a metric and a loss for bounding box regression
2019 · External reference
Current state and the future of the crested ibis (Nipponia nippon): a case study by population viability analysis
10.1046/j.1440-1703.1998.00267.x · 1998 · External reference
Automatically identifying, counting, and describing wild animals in camera-trap images with deep learning
10.1073/pnas.1719367115 · 2018 · External reference
Deep learning object detection methods for ecological camera trap data
2018 · External reference
LabelMe: a database and web-based tool for image annotation
10.1007/s11263-007-0090-8 · 2008 · External reference
Is your training data really ground truth? A quality assessment of manual annotation for individual tree crown delineation
10.3390/rs16152786 · 2024 · External reference
A study of cross-validation and bootstrap for accuracy estimation and model selection
1995 · External reference
A survey on image data augmentation for deep learning
10.1186/s40537-019-0197-0 · 2019 · External reference
Super convergence cosine annealing with warm-up learning rate
2022 · External reference
Mask R-CNN
2017 · External reference
DETRs beat YOLOs on real-time object detection
2024 · External reference
Unresolved reference
2022 · External reference
YOLOv6 v3.0: a full-scale reloading
2023 · External reference
YOLOv7: trainable bag-of-freebies sets new state-of-the-art for real-time object detectors
2023 · External reference
A review on YOLOv8 and its advancements
10.1007/978-981-99-7962-2_39 · 2024 · External reference
SAM-adapter: adapting segment anything in underperformed scenes
2023 · External reference
SAM 2: segment anything in images and videos
2024 · External reference
