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Chapter and Conference Paper
Domain Adversarial Interaction Network for Cross-Domain Fault Diagnosis
Intelligent fault diagnosis has been widely used in the industry and plays a crucial role in the health management of machinery. In recent years, unsupervised domain adaptation (UDA) has been applied to fault ...
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Chapter and Conference Paper
Semi-supervised Learning with Nearest-Neighbor Label and Consistency Regularization
Semi-supervised learning, a system dedicated to making networks less dependent on labeled data, has become a popular paradigm due to its strong performance. A common approach is to use pseudo-labels with unlab...
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Chapter and Conference Paper
Deep Adaptively Feature Extracting Network for Cervical Squamous Lesion Cell Detection
Cervical cancer is one of the most widespread malignancies affecting women’s health worldwide today. However, the task of detection is particularly difficult due to the complex background of the cervical smear...
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Chapter and Conference Paper
An Efficient Particle YOLO Detector for Urine Sediment Detection
Urine sediment detection is an essential aid in assessing kidney health. Traditional machine learning approaches treat urine sediment particle detection as an image classification task, segmenting particles fo...
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Chapter and Conference Paper
Automatic Identification for Projector Brand and Model Number
The projector production process needs to pack manufactured projectors. The key step of projector packing is to check whether the brand and model number of the projector is correct or not, for avoiding the pro...
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Chapter and Conference Paper
Bone Marrow Cell Segmentation Based on Improved U-Net
Automatic segmentation of bone marrow cells plays an important role in the diagnosis of many blood diseases such as anemia and leukemia. Due to the complex morphology and wide variety of bone marrow cells, the...
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Chapter and Conference Paper
High-Altitude Pedestrian Detection Based on Improved YOLOv3
As one of the main tasks in the field of computer vision, pedestrian detection aims to find out all pedestrians in the image or video. The existing YOLOv3 is a relatively mature object detection method. Howeve...
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Chapter and Conference Paper
An Improved Unsupervised White Blood Cell Classification via Contrastive Learning
The classification and counting of white blood cells (WBCs, leukocytes) in blood smears are of great significance for clinicopathological diagnosis. Therefore, the classification of WBCs in the images is a bas...
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Chapter and Conference Paper
Correlation-Aware Deep Generative Model for Unsupervised Anomaly Detection
Unsupervised anomaly detection aims to identify anomalous samples from highly complex and unstructured data, which is pervasive in both fundamental research and industrial applications. However, most existing ...
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Chapter and Conference Paper
Leukocyte Segmentation via End-to-End Learning of Deep Convolutional Neural Networks
Identification and analysis of leukocytes (white blood cells, WBC) in blood smear images play a vital role in the diagnosis of many diseases, including infections, leukemia, and acquired immune deficiency syn...
