2021 china mobile classifier plant
The carbon budget of China: 1980–2021
The Chinese government reported five NGHGIs for the years of 1994, 2005, 2010, 2012, and 2014 spanning a 21-year period. According to the first NGHGI, in 1994 China emitted 3.07 Gt CO 2 from energy and IPPU, and LULUCF contributed 0.41 Gt CO 2 sink (Table 2).After about 10 years, in 2005, the CO 2 emission from energy, IPPU, and …
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Plant Disease Detection and Classification by Deep Learning—A Review
Deep learning is a branch of artificial intelligence. In recent years, with the advantages of automatic learning and feature extraction, it has been widely concerned by academic and industrial circles. It has been widely used in image and video processing, voice processing, and natural language processing. At the same time, it has also become a research …
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Plant Disease Detection and Classification by Deep
10.1109/ACCESS.2021.3069646, IEEE Access ... Shanxi Agricultural University, Taigu, 030800, China . 2. College of Agricultural Engineering, Shanxi Agricultural University, Taigu, 030800, China ...
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Mapping annual 10-m maize cropland changes in China during 2017–2021
To overcome the temporal variations of plants, the proposed framework takes Sentinel-2 sequence images as input and utilizes deep neural networks and random forest as classifiers to map maize in a ...
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Plant disease detection and classification techniques: a …
One of the essential components of human civilization is agriculture. It helps the economy in addition to supplying food. Plant leaves or crops are vulnerable to different diseases during agricultural cultivation. The diseases halt the growth of their respective species. Early and precise detection and classification of the diseases may reduce the …
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Plant Disease Detection and Classification by Deep Learning—A Review
This review provides the research progress of deep learning technology in the field of crop leaf disease identification in recent years and presents the current trends and challenges for the detection of plant leaf disease using deep learning and advanced imaging techniques. Deep learning is a branch of artificial intelligence. In recent years, with the advantages of …
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Review on Convolutional Neural Network (CNN) Applied to Plant …
Crop production can be greatly reduced due to various diseases, which seriously endangers food security. Thus, detecting plant diseases accurately is necessary and urgent. Traditional classification methods, such as naked-eye observation and laboratory tests, have many limitations, such as being time consuming and subjective. …
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Microbial communities assembly in wastewater treatment plants in China …
Raw sequence data were processed as previously described (Wang et al., 2021). Clean sequences were clustered into OTUs at 97 % identity using UPARSE (v7.0.1090). The taxonomy of each operational taxonomic unit (OTU) representative sequence was classified against the SILVA database (v138) with 70 % confidence threshold using the RDP …
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Improving Deep Learning-based Plant Disease Classification …
Well-known CNN models (i.e. EfficientNetB0, MobileNetV2, ResNet50, InceptionV3, and VGG19) were applied to do transfer learning for plant disease …
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Revolutionizing agriculture with artificial intelligence: plant …
"Plant disease detection and classification using deep learning model," in 2021 IEEE Third International Conference on Inventive Research in Computing Applications (ICIRCA), Coimbatore, India, 1285–1291. doi: 10.1109/ICIRCA51532.2021.9544729
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Electronics | Free Full-Text | A Survey on Different Plant …
Early detection and identification of plant diseases from leaf images using machine learning is an important and challenging research area in the field of agriculture. There is a need for such kinds of research studies in India because agriculture is one of the main sources of income which contributes seventeen percent of the total gross domestic …
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MACHINE LEARNING TECHNIQUES IN PLANT DISEASE …
Azim et al., (2021), developed a feature extracting method for the rice plant leaf disease classification. In this work, 3 types of diseases affecting the rice leaves are detect ed. The unwa nted ...
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MobileNetV3 for Image Classification
Convolution neural network (CNN) is a kind of deep neural networks, which extracts image features through multiple convolution layers and is widely used in image classifications. With the increasing number of image data processed by mobile devices, application of neural network for mobile terminals becomes popular. However, these …
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Survey of feature extraction and classification techniques to …
The purpose of a classifier is to identify the image by placing the image into a pre-defined category based on the feature vector. The classifier is first trained by a set of training data. The more the number of training images, the better accuracy of the classifier can be achieved. A classifier must achieve results in the minimum possible time.
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Improved MobileNetV2 crop disease identification model for …
The final experimental results show that the improved MobilNetV2 model achieves 99.53% accuracy in the PlantVillage crop disease dataset, which is 0.3% …
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Medicinal Plant Parts Identification and Classification using …
Each plant has an equal number of leaf images (300 images) but the number of plants categorized in each 97 Misganaw Aguate et al. Ethiop.J.Sci.Sustain.Dev., Vol. 8 (2), 2021 The focal length of the camera (distance between leaves and camera) is taken depending on the broadness and narrowness of the plant leaves; The white background of the ...
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Identification and Classification of Rice Plant Disease Using …
2021 18th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP) | 978-1-6654-1364-0/21/$31.00 ©2021 IEEE | DOI: 10.1109/ICCWAMTIP53232.2021. ...
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Washing and Classifying | Washing Systems
The SW 200 is a twin screw fine material washer/ classifier/dewaterer. The recommended maximum material size is 3/8" (10mm). The approximate capacity of the SW 200 Sandscrew is 100-200 TPH. ... MOBILE SAND SCREW PLANTS - M 165 S / M 166 S / M 206 S. M 165 S. M 166 S. M 206 S. washing systems offer a range of sand …
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Plant Disease Detection and Classification Using Deep …
[Show full abstract] on image-based plant disease classification using deep learning techniques. The report begins by providing an overview of plant diseases and their impact on agriculture.
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Frontiers | A mobile-based system for maize plant leaf …
The state-of-the-art YOLOv8n model for maize plant disease detection and classification is used. The best-trained model is integrated with the user-friendly smartphone application for the real-time detection of maize disease to facilitate the end user.
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Automated plant leaf disease detection and classification …
This paper proposes an automated plant leaf disease detection and classification model using optimal mobile network based convolutional neural network (OMNCNN) model. ... revealed that the proposed plant classification method achieved 90.94 % of top-1 accuracy and 86.21 % of F1-score. The accuracies of the proposed …
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A Review of Machine Learning Approaches in Plant Leaf …
To identify the recent advancements in the development of plant disease detection and classification system based on Machine Learning (ML) and Deep Learning (DL) models. In this study, we have collected more than 45 papers published during the year 2017-2020 from the peer-reviewed journals of different databases such as Scopus and Web of …
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Plant Diseases Classification using Machine Learning
Plant Diseases Classification using Machine Learning. Tan Soo Xian 1 and Ruzelita Ngadiran 1,2. Published under licence by IOP Publishing Ltd Journal of Physics: Conference Series, Volume 1962, The 1st International Conference on Engineering and Technology (ICoEngTech) 2021 15-16 March 2021, Perlis, Malaysia Citation Tan Soo …
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A Plant Disease Classification Algorithm Based on Attention …
Plant growth is inevitably affected by diseases, and one effective method of disease detection is through the observation of leaf changes. To solve the problem of disease detection in complex backgrounds, where the distinction between plant diseases is hindered by large intra-class differences and small inter-class differences, a complete …
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Image Recognition of Crop Diseases and Insect Pests Based …
Our goal is to train a classifier through DCNN to classify images of crop diseases and insect pests into different levels according to their quality. The …
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Mapping rapeseed in China during 2017-2021 using …
Similarly, the average F1-score of the two models only decreased 0.08% and 0.28% compared to the all-model. Thus, classifiers trained by the generated samples from other years are able to map rapeseed in the years without generated samples, suggesting that the 2017–2018 rapeseed delineated by the classifier for 2019–2021 is also reliable.
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Automated plant leaf disease detection and classification …
This paper proposes an automated plant leaf disease detection and classification model using optimal mobile network based convolutional neural network …
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Mapping annual 10-m maize cropland changes in China …
In this paper, we collect numerous samples to produce annual 10-m maize cropland maps in China from 2017 to 2021 with a machine learning based …
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Plant Disease Detection and Classification by Deep Learning
Plant diseases affect the growth of their respective species, therefore their early identification is very important. Many Machine Learning (ML) models have been employed for the detection and classification of plant diseases but, after the advancements in a subset of ML, that is, Deep Learning (DL), this area of research …
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PLANT DISEASE DETECTION USING CONVOLUTIONAL NEURAL NETWORK …
Plant disease is the key issue for the farmers, which leads to lesser income and minimal outcome. Pest affected crop also results in small agricultural production of the country.
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