Søgeresultater - HE Yong-jun

At present, view-based 3D model classification is a research hotspot. However, current methods produce many redundant views, and all views are treated equally, ignoring their differences and importance. To solve the above problems, we propose a multi-view fusion 3D model classification method. This...

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The pathology-assisted diagnosis system adopts the method of placing a filter on the slice to filter the light source and obtain the monochromatic parallel light, which is used to calculate the optical density parameter of the image to reflect the content of a certain substance in the slice.But the...

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3D model retrieval based on representative views was proposed. On the view representation of the 3D model, in order to fully represent the model and reduce redundant information, we firstly adopt Light Field Descriptor (LFD) to generate 2D views, and then use K-MEANS to get representative views from...

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Query-by-humming is an important branch of audio retrieval, and it can provide users with a new and convenient experience.During the retrieval process, since there are unignorable differences between different humming of the same song, it is difficult to obtain ideal results by accurate matching of...

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The identification of cervical abnormal cells using deep learning methods usually requires a large amount of training data, but these data inevitably use different samples of cervical abnormal cells to participate in model training, and naturally miss the positive and abnormal intracellular controls...

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With the development of artificial intelligence technology, the automatic reading system plays an increasingly important role in assisting the diagnosis of pathologists, improving the accuracy of pathology diagnosis and reducing labor intensity. Accurate segmentation of the nucleus is the primary fa...

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The development of deep learning has effectively improved the accuracy of cervical cell classification. The training of deep neural networks requires a large amount of labeled data. However, the labeling of cervical cell images requires specialized physicians and the labeling workload is heavy and c...

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In recent years, deep learning technology has shown great potential in bearing fault diagnosis based on vibration signals.However, in the fault diagnosis method based on deep learning, the traditional single network topology feature extraction has weak discrimination and low noise robustness, and th...

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Currently, there are two challenges in identifying abnormal cervical cells using deep learning: (1) cervical cells are diverse and cervical cell images vary from person to person. (2 ) Cervical cells show long-tailed distribution, which affects the classification accuracy of cervical cells. In this...

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In recent year， automatic microscope imaging technology has been widely used in the field of automatic reading. The selection of focusing window is a key technology in the autofocus algorithm, which directly affects the performance of autofocus algorithm. Traditional focusing window selection method...

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Abnormal cell detection is a key technique for intelligent assisted diagnosis of cervical cancer, which directly affects the performance of the detection system. However, most cervical abnormal cells exist in the form of clusters. Cells adhere to each other, complex and diverse, which brings challen...

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In recent years, deep learning has been widely used in defect detection. At present, the method can detect large defects, but it is still unable to detect the fine defects accurately. In order to solve this problem, this paper proposes a new method of printing defect detection based on deep convolut...

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