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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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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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.
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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The results of studies of the morphological analysis of the text are demonstrated. Application of the technology of automatic processing of Russian-language texts to determine the parts of speech presented in the digi...
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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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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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The expensive fine-grained annotation and data scarcity have become the primary obstacles for the widespread adoption of deep learning-based Whole Slide images (WSI) classification algorithms in clinical practice. Unl...
In the new media environment, the research of video content analysis and recommendation system is particularly important. This paper discusses how to use imageprocessing technology to deeply analyze and accurately re...
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ISBN:
(数字)9798331536169
ISBN:
(纸本)9798331536176
In the new media environment, the research of video content analysis and recommendation system is particularly important. This paper discusses how to use imageprocessing technology to deeply analyze and accurately recommend film and television content. With the diversification of presentation forms and communication channels of film and television content, the problems of information overload and uneven content quality have become increasingly prominent. This study aims to solve these problems and improve the user experience by constructing a video content analysis and recommendation system based on imageprocessing technology. The system includes four core modules: data acquisition, imageprocessing, content analysis and recommendation algorithm. By integrating imageprocessing, machine learning and recommendation algorithm, the whole process from data acquisition to personalized recommendation is implemented efficiently. The experimental results demonstrate that the hybrid recommendation strategy outperforms single algorithms in various evaluation metrics, including accuracy, recall, F1 score, and Mean Reciprocal Rank (MRR), significantly enhancing the precision of recommendations and user satisfaction. This study not only provides a scientific basis and decision support for content creation, distribution, and marketing in the film and television industry but also lays a solid foundation for building more intelligent film and television content recommendation systems.
In order to realize the rapid and stable recognition and automatic tracking of various complex roads by the intelligent vehicles, this paper proposes imageprocessing and cascade Proportion Integration Differentiation...
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ISBN:
(纸本)9781665462198
In order to realize the rapid and stable recognition and automatic tracking of various complex roads by the intelligent vehicles, this paper proposes imageprocessing and cascade Proportion Integration Differentiation (PID) steering and speed control algorithms based on CMOS grayscale cameras in the context of the national college student intelligent vehicle competition. First, the grayscale image of the track is acquired by the grayscale camera. Then, the Otsu method is used to binarize the image, and the information of black boundary guide line is extracted. In order to improve the speed of the race, various track elements in the image are identified and classified, and the deviation between the actual centerline position and the ideal centerline position of the intelligent vehicle is calculated. Third, the discrete incremental cascade PID control algorithm is used to calculate the pulse width modulation (PWM) signal corresponding to the deviation. And the PWM signal is acted on the steering motor through the driving circuit, driving the intelligent vehicle to always drive along the middle road, so as to achieve the purpose of automatic tracking guidance. Experiments prove that the intelligent vehicle of this design can identify complex roads quickly and in a stable way, accurately complete automatic tracking, and obtain higher speed performance.
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