日期:
2020 年 — 2026 年
2020
2021
2022
2023
2024
2025
2026
影响因子:

Expanding phenological insights: automated phenostage annotation with community science plant images

拓展物候学见解:利用社区科学植物图像进行物候期自动注释

Katal, Negin; Rzanny, Michael; Mäder, Patrick; Boho, David; Wittich, Hans Christian; Tautenhahn, Susanne; Bebber, Anke; Wäldchen, Jana

Opportunistic plant observations reveal spatial and temporal gradients in phenology

机会性植物观察揭示了物候的空间和时间梯度

Rzanny, Michael; Mäder, Patrick; Wittich, Hans Christian; Boho, David; Wäldchen, Jana

Bridging the gap: how to adopt opportunistic plant observations for phenology monitoring

弥合差距:如何利用机会性植物观察进行物候监测

Katal, Negin; Rzanny, Michael; Mäder, Patrick; Römermann, Christine; Wittich, Hans Christian; Boho, David; Musavi, Talie; Wäldchen, Jana

Image-Based Automated Recognition of 31 Poaceae Species: The Most Relevant Perspectives

基于图像的31种禾本科植物自动识别:最相关的视角

Rzanny, Michael; Wittich, Hans Christian; Mäder, Patrick; Deggelmann, Alice; Boho, David; Wäldchen, Jana

Flora Capture: a citizen science application for collecting structured plant observations

植物群落采集:一款用于收集结构化植物观测数据的公民科学应用程序

Boho, David; Rzanny, Michael; Wäldchen, Jana; Nitsche, Fabian; Deggelmann, Alice; Wittich, Hans Christian; Seeland, Marco; Mäder, Patrick

Image-based classification of plant genus and family for trained and untrained plant species

基于图像的植物属和科分类,适用于经过训练和未经训练的植物物种

Seeland, Marco; Rzanny, Michael; Boho, David; Wäldchen, Jana; Mäder, Patrick

Combining high-throughput imaging flow cytometry and deep learning for efficient species and life-cycle stage identification of phytoplankton

结合高通量成像流式细胞术和深度学习技术,高效识别浮游植物的物种和生命周期阶段

Dunker, Susanne; Boho, David; Wäldchen, Jana; Mäder, Patrick