Early identification and detection of plant diseases is essential for preventing diseases during plant growth and is also the core of precise and intelligent management of crop diseases and insect pests. This paper fi...
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ISBN:
(纸本)9798350352634;9798350352627
Early identification and detection of plant diseases is essential for preventing diseases during plant growth and is also the core of precise and intelligent management of crop diseases and insect pests. This paper first introduces the plant disease type, plant disease data set and pretreatment technology, and then elaborates on the research status of deep learning identification and detection algorithm, and existing problems, finally points out that although deep learning in plant disease identification and detection shows great potential, but still face such as complex environment robustness, disease identification, data set deviation and diversity is the main challenge.
In this paper, the method of deep learning is applied for plant species identification, with a special emphasis on Convolutional Neural Network VGG16 for feature extraction and classification. Identification of plants...
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In densely populated countries like India, traffic violations are a major concern, especially among motorcyclists, leading to accidents and significant loss of life and property. A prevalent issue is the failure to we...
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This study addresses the challenges of cheating and illegal access in online exams, maintaining academic integrity with an AI-powered web-based monitoring *** we uses COCO-SSD to detect misconduct such as many faces, ...
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The research combines Deep Q-learning(DQN) with a Mininet-based network simulation and Scapy intrusions detection system (IDS) for malicious traffic prioritizing. The RL agent continuously learns to act based on real-...
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This study developed a forensic identification model for traumatic brain injury based on deep learning algorithms to improve the accuracy and efficiency of forensic imaging analysis. Through large-scale data training,...
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We address the challenge of enhancing federated learning with small datasets by proposing an adaptive differential privacy technique and a dynamic learning rate optimization algorithm. Our method adds adaptive noise t...
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ISBN:
(纸本)9798350352634;9798350352627
We address the challenge of enhancing federated learning with small datasets by proposing an adaptive differential privacy technique and a dynamic learning rate optimization algorithm. Our method adds adaptive noise to protect data privacy and uses historical momentum information to improve stability and convergence speed. Extensive experiments demonstrate that our approach significantly improves model performance, accelerates the learning process, and ensures privacy, offering a practical solution for federated learning with small datasets.
As edge-based decisions continue to grow in demand, organizations are increasingly seeking user data, raising privacy concerns. Federated learning (FL) addresses this problem but is typically dependent on computationa...
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Lung cancer continues to be a leading cause of death, and hence there is a significant need for early detection to improve survival rates. This current research addresses some loopholes existing in the current diagnos...
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The classification of celestial objects such as stars, galaxies, and quasars is one of astronomy's most difficult and fundamental problems. Due to the technological advancement of telescopes and observatories, the...
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