breadth
发表于 2025-3-23 11:23:28
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locus-ceruleus
发表于 2025-3-23 16:41:02
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同谋
发表于 2025-3-23 19:51:01
Real-Life Agricultural Data Retrieval for Large-Scale Annotation Flow Optimization,More advanced architectures such as transformers have also not been applied to this data before. This chapter presents a solution to speed up annotation time by providing annotators semantically similar images to their target image. An image retrieval task is conducted to map crop images to a single
Basal-Ganglia
发表于 2025-3-23 22:45:15
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fodlder
发表于 2025-3-24 03:22:43
Agri-Food Products Quality Assessment Methods,essment. It can provide qualitative and quantitative data under single analysis. This chapter ensures a critical review on spectroscopic and imaging techniques combined chemo metric analysis, which achieves better accuracy of 99% for food quality analysis, role of machine learning and deep learning
indignant
发表于 2025-3-24 07:12:30
,ESMO-based Plant Leaf Disease Identification: A Machine Learning Approach,detects and classifies input plant leaf data as healthy or diseased using SVM and kNN classifier, where SVM gives better accuracy of 93.67%. The obtained results indicate that the proposed methodology outperforms the other algorithms in obtaining good classification accuracy.
大喘气
发表于 2025-3-24 12:54:00
Apple Leaves Diseases Detection Using Deep Convolutional Neural Networks and Transfer Learning,isease classes. The dataset is improved and expanded using various data augmentation techniques on the training images. Experimental analysis on the Plant Pathology 2021-FGVC8 dataset shows that our proposed model achieves remarkable precision, recall, and .1-score of 0.9743, 0.9541, and 0.9625, res
thwart
发表于 2025-3-24 15:12:58
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小歌剧
发表于 2025-3-24 21:06:27
Early Stage Prediction of Plant Leaf Diseases Using Deep Learning Models, CNN-SVM classifier is shown to be a fast, extremely efficient method for classifying specific imaging features into desired disease classes, as well as giving preferable results over the plain CNN and other classifiers, such as the support vector machine (SVM) for large datasets. Finally, the exper
rectocele
发表于 2025-3-25 00:37:10
2524-7565 . The remaining six chapters concentrates on optimized disease recognition through computer vision-based machine and deep learning strategies..978-981-16-9993-1978-981-16-9991-7Series ISSN 2524-7565 Series E-ISSN 2524-7573