To address the slow convergence speed of genetic algorithms (GAs) in solving the mobile robot path planning problem, this study proposes a genetic algorithm with quality of population evolution (QPEGA). In QPEGA, the ...
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Recently, federated learning (FL) has been increasingly appealing in distributed signal processing and machine learning. Nevertheless, the practical challenges of label deficiency and client heterogeneity form a bottl...
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Through computers, artists have found a way to enhance their production, discovering new ways for communicating their productions and devising new forms of expression. Being able to make the most of these facilities r...
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In order to comply with the trend of intelligent visual communication, this study proposed an innovative visual communication scenario based on imageprocessingalgorithms. The framework aims to optimize traditional k...
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Agriculture plays a foremost role in countries growth. The physical recognition of disease in the plant is more timeconsuming and necessity of expert labor is high. One of the most vital aspect in agriculture field is...
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Preventing unintentional leakage of information about the training set has high relevance for many machine learning tasks, such as medical image segmentation. While differential privacy (DP) offers mathematically rigo...
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ISBN:
(纸本)9781665405409
Preventing unintentional leakage of information about the training set has high relevance for many machine learning tasks, such as medical image segmentation. While differential privacy (DP) offers mathematically rigorous protection, the high output dimensionality of segmentation tasks prevents the direct application of state-of-the-art algorithms such as Private Aggregation of Teacher Ensembles (PATE). In order to alleviate this problem, we propose to learn dimensionality-reducing transformations to map the prediction target into a bounded lower-dimensional space to reduce the required noise level during the aggregation stage. To this end, we assess the suitability of principal component analysis (PCA) and autoencoders. We conclude that autoencoders are an effective means to reduce the noise in the target variables.
Today's machine learning is considered as one of the artificial intelligence technologies used in many ways. Its functions are very accurate, from receiving the given input data to calculating, measuring and outpu...
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Steganography is the practice of hiding information by embedding it as secret data within various types of digital media to strengthen security. Numerous algorithms have been proposed for image steganography with a co...
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Unlike diseases of the human body, plant diseases don't camouflage themselves within the body of the crop. The leaves reflect the infection with a change in color, shape, texture or a combination of the three. Hen...
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Intestinal parasitic infections in animals can cause a range of symptoms, including diarrhea, weight loss, anemia, and malnutrition. This project aims to classify parasitic eggs belonging to the Monezia and Strongyles...
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