Image Processing
This dataset includes various gauge blocks of different heights at different positions. This includes two sets of data with no targets and different measurement heights. Each data consists of 16 phase-shifting images and their corresponding Gray code images.
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This dataset includes various gauge blocks of different heights at different positions. This includes two sets of data with no targets and different measurement heights. Each data consists of 16 phase-shifting images and their corresponding Gray code images.
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11 Views
Structural analysis of minuscule height objects holds paramount significance in fields such as industrial manufacturing and medical testing. Currently, 3D reconstruction method based on shape from focus (SFF) has emerged as an efficacious approach for acquiring submicron-level height change information. A novel multi-field SFF(MF-SFF) framework incorporates pulse-controlled continuous acquisition methods and parallel chain processing (PCP) strategy, effectively addressing challenges associated with minuscule height objects.
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OCD description. Cell lines A172 and U251: human glioblastoma; MCF7: human breast cancer; MRC5: human lung fibroblast; SCC25: human squamous cell carcinoma. Cultivation condition CTR: cells belonging to the control group - without the addition of chemotherapy; TMZ: cells treated with 50 μM temozolomide in some cultivation step.
Split
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LDRText is a large-scale and diverse dataset that suitable for scene text image super-resolution and recognition tasks
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155 Views
This dataset is derived from Sentinel-2 satellite imagery.
The main goal is to employ this dataset to train and classify images into two classes: with trees, and without trees.
The structure of the dataset is 2 folders named: "tree" (images containing trees) and "no-trees" (images without presence of trees).
Each folder contains 5200 images of this type.
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434 Views
This paper presents a deep learning model for fast and accurate radar detection and pixel-level localization of large concealed metallic weapons on pedestrians walking along a sidewalk. The considered radar is stationary, with a multi-beam antenna operating at 30 GHz with 6 GHz bandwidth. A large modeled data set has been generated by running 2155 2D-FDFD simulations of torso cross sections of persons walking toward the radar in various scenarios.
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With the fast growth of deep learning, trainable frameworks have been presented to restore hazy images. However, the capability of most existing learning-based methods is limited since the parameters learned in an end-
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355 Views
In international contexts, natural scenes may include text in multiple languages. Especially, Latin and Arabic scene character image dataset is essential for training models to accurately detect and recognize text regions within real-world images. This is crucial for applications such as text translation, image search, content analysis, and autonomous vehicles that need to interpret text in different languages.
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370 Views