About this Research Topic
The field of plant species classification has long been a cornerstone of botanical research, yet it faces significant challenges due to the vast number of species and the subtle differences between them. Traditional methods of plant identification are often time-consuming and require expert knowledge, which is impractical given the sheer diversity of plant life. Additionally, the threat of extinction looms over many plant species, necessitating urgent and effective conservation strategies. Recent advancements in information and communication technologies have opened new avenues for "Smart Phytoprotection," leveraging intelligent technologies like deep learning to enhance plant species classification. Despite these advancements, there remain gaps in the application of these technologies, particularly in their ability to handle complex backgrounds and optimize feature extraction. This research topic aims to address these gaps by exploring the latest techniques and methodologies in smart plant conservation.
This research topic aims to deepen our understanding of smart plant species classification techniques, focusing on the application of deep learning for plant recognition and classification. The primary objectives include answering specific questions about the efficacy of deep learning methods in plant identification, testing hypotheses related to the optimization of these algorithms, and exploring their practical applications in conservation efforts. By fostering interdisciplinary discussions, we hope to advance the sustainable development and utilization of biological resources, thereby contributing to the bioeconomy and promoting harmonious coexistence between humans and nature.
To gather further insights into the boundaries of smart plant species classification, we welcome articles addressing, but not limited to, the following themes:
- Fast plant image recognition based on deep learning
- Research and implementation of plant image recognition methods
- Optimization of deep learning algorithms for object detection
- Plant recognition algorithms considering complex backgrounds
This research topic seeks to compile a comprehensive collection of studies that not only highlight the latest advancements but also address the practical challenges faced in the field of plant species classification.
This research topic aims to deepen our understanding of smart plant species classification techniques, focusing on the application of deep learning for plant recognition and classification. The primary objectives include answering specific questions about the efficacy of deep learning methods in plant identification, testing hypotheses related to the optimization of these algorithms, and exploring their practical applications in conservation efforts. By fostering interdisciplinary discussions, we hope to advance the sustainable development and utilization of biological resources, thereby contributing to the bioeconomy and promoting harmonious coexistence between humans and nature.
To gather further insights into the boundaries of smart plant species classification, we welcome articles addressing, but not limited to, the following themes:
- Fast plant image recognition based on deep learning
- Research and implementation of plant image recognition methods
- Optimization of deep learning algorithms for object detection
- Plant recognition algorithms considering complex backgrounds
This research topic seeks to compile a comprehensive collection of studies that not only highlight the latest advancements but also address the practical challenges faced in the field of plant species classification.
Keywords: Phytoprotection, Deep Learning, Plant Recognition, Species Classification, Conservation
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
