· Identifying medicinal plants separately from other non-edible plants is essential in botany and food industries. The traditional methods of identifying medicinal plants are time-consuming,
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Ecology, pharmacology, agriculture, and conservation require species identification. Identification is difficult when there are several identical species. Flora-with’s 400,000 species need skilled identification. Dichotomous keys might take days to identify a species, especially in biodiversity hotspots. Non-scientists may struggle with this identifying
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· Plant identification can be automated using visual morphological characteristics such as the shape, color, and texture of the leaves and flowers. This paper presents how rare medicinal plants were
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· In Northeast Medicinal Plants, Liz Neves is your trusted guide to finding, identifying, harvesting, and using 111 of the region’s most powerful wild plants. You’ll learn how to safely and ethically forage, and how to use wild plants in herbal medicines including teas, tinctures, and salves.
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This book features 113 botanical entries covering more than 150 different species of botanicals in commerce, plus 87 detailed black-and-white line drawings. It also contains a brief review of basic plant structure, some practical advice on identification, an introduction to botanical nomenclature, a glossary, a reference list, and an index.
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· In this research, an intelligent approach for the identification of Indian medicinal plant leaves is presented. Herein, heterogeneous features extracted from leaves of Indian medicinal herbs serve as input attributes for classifier models. A bilateral approach is employed to bring out heterogeneous features. In the first approach, a framework for
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· Background The identification and enumeration of medicinal plants at high elevations is an important part of accurate yield calculations. However, the current assessment of medicinal plant reserves continues to rely on field sampling surveys, which are cumbersome and time-consuming. Recently, unmanned aerial vehicle (UAV) remote
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Plants play an important role in human life for providing oxygen, food, housing, medicine, energy, housing, and environmental protection. Plants are rich in medicinal esteem and contain dynamic elements for medicinal use because of the global warming populace, lack of expert help for research, lack of government upholding research exercises, and
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· Medicinal plants are the “backbone” of traditional medicine, which means, more than 3.3 billion people in the less developed countries utilize medicinal plants regularly []. 2 Related Work Researchers have been working great on the botanist theory of plantations for a long time.
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The DL model is evaluated using measures including accuracy, precision, and recall. For this reason, the DL model was able to correctly identify medicinal leaves at an accuracy rate of 98.3%. After being thoroughly investigated, the DL model is uploaded to the cloud, and a mobile app is created for the real-time identification of medicinal leaves.
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· Medicinal plants have a long tradition of being cultivated and harvested in India. The Indian Forest is the principal repository for many useful medicinal herbs. As a result of their critical role in maintaining people's life, medicinal plants have traditionally been the subject of intensive research and consideration. Yet, correctly identifying
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The primary processes in identifying medicinal plants were feature extraction and classification. Many beneficial plant species were being destroyed because of professional secrecy, rising population, global warming, a lack of government backing for research operations, and a lack of knowledge about medicinal plants.
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· Medicinal plants can provide immense contribution towards the growth of modern medicine and pharmaceutical industries to protect people from current deadly diseases like cancer and cardiovascular diseases. However, presence of thousands of plant species globally and similarity in their features like color, texture and shape makes their
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· Corresponding Author Yu-Lin LIN ( Institute of Medicinal Plant Development, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing 100193, China) These authors contributed equally to this article. JPH, E-mail: [email protected]; LCS, E-mail: [email protected].
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· This paper proposes a deep learning-based approach to. recognizing and identifying herbal medicinal plants, which. consists of two main components: a dataset and a model. architecture. The dataset
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· Temporal evolution on medical plants publications for Top 12 countries. The first group is the leaders of this research, China and India, with between 800 and 1100 publications per year. China led the research from 1996 to 2010, and from this year to 2016, the leader was India, after which it returned to China.
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· The exact and unfailing categorization of medicinal plants exceeds the capabilities of the average individual because it necessitates in-depth subject expertise and physical detection is cumbersome and imprecise owing to human mistakes. There have been multiple efforts to automate the recognition of medicinal plants using images of
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· Transfer learning models outperformed CNN models for medicinal plant identification with 99.5% accuracy for MobileNet V2 and their disease classification with 90% accuracy for VGG 16. View full-text
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· It becomes an active trend in the recent years. We apply Convolutional Neural Network (CNN) to recognize Vietnamese medicinal plant images in this paper. Different frameworks are evaluated such as
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· This paper proposes a DNN-based approach to recognizing. and identifying herbal medicinal plants, which consists of two. main components: a dataset and a model architecture. The. dataset used in
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· The identification of plant species is fundamental for the effective study and management of biodiversity. In a manual identification process, different characteristics of plants are measured as identification keys which are examined sequentially and adaptively to identify plant species. However, the manual process is
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· The plant offers antibiotic, antiviral, and healthy fungicidal properties. Arizona Dewberry, Rubus, resembles a raspberry, only sour-sweet with seeds. They can be eaten raw, dried, and jellied. Each berry is full of vitamin C, magnesium, and potassium. The leaves made a supposedly helpful tea to the urinary tract.
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· Knowledge of medicinal plant species is necessary to preserve medicinal plants and safeguard biodiversity. The classification and identification of these plants by botanist experts are complex and time-consuming activities.
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· The medicinal plant dataset is captured directly from farms with the specified image acquisition conditions using 5MP, 12MP, 8MP,13MP, and 16MP resolutions. The collected images are compiled into separate folders with the folder name of plant species in both medicinal leaf and plant datasets. 3.4. Data augmentation.
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· The use of medicinal plants has been a longstanding practice in traditional medicine worldwide. Accurately identifying medicinal plants is crucial for determining their medicinal
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The project "Identification of Medicinal Plants using CNN" leverages deep learning techniques to automate the classification of medicinal plants based on their leaf images. This endeavor holds immense promise for the Ayush Ministry and various stakeholders in herbal medicine, botanical research, and environmental conservation.
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· The CNN-based identification for medicinal plants project has significant scope in the field of botany and medicine. The project can assist botanists and researchers in accurately identifying different species of medicinal plants, which can be used for the development of new drugs and medicines. It can also be used to identify the presence of
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Project Description : This project aims to identify Indian medicinal plants using Convolutional Neural Networks (CNN). The project uses a Flask backend to serve the model and provide an interactive interface for users to upload images of plants for identification. Dataset :The dataset used in this project consists of images of various Indian
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· The identification of plant species is fundamental for the effective study and management of biodiversity. In a manual identification process, different characteristics of plants are measured
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· In this study, we investigate the use of federated learning in the identification of medicinal plants. By utilizing two federated learning algorithms, FedAvg [10] and FedProx [7], we specifically study the efficacy of federated learning in training deep learning models on decentralized and distributed datasets of medicinal plant photos.
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