In this paper, we address the problem of recovering a sharp image from its non-uniformly blurred version making use of a known but noisy version of the same scene. The recovery process includes three main steps - moti...
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Increase in the use of mobile phones for scene capturing turns into the exponential increase in the size of digital libraries. Content-Based image Retrieval (CBIR) is an effective solution to handle this enormous data...
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With the continuous development of deep learning in computervision, object detection technology is constantly employed for processing remote sensing images. Especially, ship detection has become a significant and cha...
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ISBN:
(纸本)9781450385084
With the continuous development of deep learning in computervision, object detection technology is constantly employed for processing remote sensing images. Especially, ship detection has become a significant and challenging task due to complex environmental factors (strong waves, clouds interference, etc.) and object issues (orientation, scale variety, density, etc.). Current detection methods pay more attention to the detection accuracy while ignoring the detection speed. In contrast with accuracy, detection speed is more important in some cases such as marine rescue and vessel tracking. Aiming at addressing these problems, we propose an enhanced YOLOv4(C-YOLOv4) which contains the feature fusion attention module (FAM) with a channel correlation loss(C-loss). C-loss is proposed to constrain the relations between object classes and channels while maintaining the intra-class and the inter-class separability. To evaluate the effectiveness of the proposed approach, comprehensive experiments are conducted on a public dataset HRSC2016. According to the experimental results, our proposed approach outperforms the baselines.
Convolutional neural network (CNN) is a well established practice for image classification. In order to learn new classes without forgetting learned ones, CNN models are trained in offline manner which involves re-tra...
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Scanning and storage of documents are regular practices. Retrieval of such documents is necessary to support office work. In this paper, a novel multimodal query based approach for retrieving documents using text, non...
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UAVs have been widely used in military and civilian fields. The research on UAV task assignment mainly involves trajectory planning, task assignment, and specific applications for various scenarios. Moreover, most of ...
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In this work, we describe an automated quality assurance system for pipes in warehouses and yards using simple handheld and mobile equipment like smartphone cameras. Currently, quality inspection for bent and crooked ...
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With rapid advances in imaging devices and internet, millions of images are uploaded on the internet without much information about the image. An efficient method is necessary for detecting the concept of the desired ...
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Pathological examination is the most accurate method for the diagnosis of cancer. Breast cancer histopathology evaluation analyses the chemical and cellular characteristics of the cells of a suspicious breast tumor. A...
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Asymmetric multi-camera systems are growing popular among smartphone manufacturers due to their ability to enhance image quality in applications such as low light imaging and camera zoom. One such multi-camera system ...
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