Image Processing
some forest foggy images
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Supplemental material with appendix, results and color profile data.
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One of the weak points of most of denoising algoritms (deep learning based ones) is the training data. Due to no or very limited amount of groundtruth data available, these algorithms are often evaluated using synthetic noise models such as Additive Zero-Mean Gaussian noise. The downside of this approach is that these simple model do not represent noise present in natural imagery.
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This dataset is used for the interference detection in high frequency over-the-horizon (OTH) radar, especially the sky-wave mode. The range-Doppler (RD) grey images are categorized into three types, i.e. the radio frequency interference (RFI), the transient interference (TSI), and no interference (NoI). Two databases are included. The simulated database is constructed based on signal models of interference, clutter and noise. The real database is constructed based on real data from OTH radars.
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The C3I Thermal Automotive Dataset provides > 35,000 distinct frames along with annotated thermal frames for the development of smart thermal perception system/ object detection system that will enable the automotive industry and researchers to develop safer and more efficient ADAS and self-driving car systems. The overall dataset is acquired, processed, and open-sourced in challenging weather and environmental scenarios. The dataset is recorded from a lost-cost yet effective 640x480 uncooled LWIR thermal camera.
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2787 Views
In this paper, we propose a framework for 3D human pose estimation using a single 360° camera mounted on the user's wrist. Perceiving a 3D human pose with such a simple setup has remarkable potential for various applications (e.g., daily-living activity monitoring, motion analysis for sports training). However, no existing method has tackled this task due to the difficulty of estimating a human pose from a single camera image in which only a part of the human body is captured, and because of a lack of training data.
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Activated Sludge Phase-contrast Microscopic Image
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The anomaly detection in photovoltaic (PV) cell electroluminescence (EL) image is of great significance for the vision-based fault diagnosis. Many researchers are committed to solving this problem, but a large-scale open-world dataset is required to validate their novel ideas. We build a PV EL Anomaly Detection (PVEL-AD) dataset for polycrystalline solar cell, which contains 36,543 near-infrared images with various internal defects and heterogeneous background. This dataset contains anomaly-free images and anomalous images with 10 different categories.
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Document layout analysis (DLA) plays an important role for identifying and classifying the different regions of digital documents in the context of Document Understanding tasks. In light of this, SciBank seeks to provide a considerable amount of data from text (abstract, text blocks, caption, keywords, reference, section, subsection, title), tables, figures and equations (isolated equations and inline equations) of 74435 scientific articles pages. Human curators validated that these 12 regions were properly labeled.
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This CoFSM dataset contains the supplemental material of TIP3157450 (Multimodal remote sensing image datasets). The CoFSM dataset contains six types of modal images (multi temporal-optical, infrared-optical, depth-optical, map-optical, SAR-optical andnight-day). Each modal type includes 10 groups of images, and each set of images has corresponding ground truth points.
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445 Views