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This dataset was collected from real-world recycling plants, primarily consisting of crushed glass from disassembled display devices. The dataset contains images of flat glass mixed with solid glass, colored glass, plastic film, and aluminum foil. The colored glass originated from frame areas, while the aluminum foil came from cable shielding materials. Additional objects, such as solid glass and plastic films, were sourced from other recycled materials like glass bottles and packaging.
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140 Views
This dataset contains 570 JPEG images of electricity meters taken from varied locations within the IIT BHU campus, including the GTFRC and residential apartments. It showcases a broad range of real-world scenarios, with each image demonstrating different challenges such as varying lighting conditions, levels of focus and clarity, and a wide range of capture angles. These attributes test and enhance the robustness of technologies designed to interpret meter readings from photographs under diverse conditions.
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511 Views
This dataset is a valuable resource for researchers and developers working on various applications related to illumination and visual effects. It contains a diverse collection of images that feature complex lighting scenarios, making it particularly useful for tasks such as illumination estimation, scene relighting, and object insertion. The images are carefully curated to include both single-color and multicolor lighting conditions, providing a wide range of examples for different lighting effects.
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241 Views
The dataset consists of around 335K real images equally distributed among 7 classes. The classes represent different levels of rain intensity, namely "Clear", "Slanting Heavy Rain", "Vertical Heavy Rain", "Slanting Medium Rain", "Vertical Medium Rain", "Slanting Low Rain", and "Vertical Low Rain". The dataset has been acquired during laboratory experiments and simulates a low-altitude flight. The system consists of a visual odometry system comprising a processing unit and a depth camera, namely an Intel Real Sense D435i.
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211 Views
Dataset of images of dragon fruit plants, collected from different media and taken from a dragon fruit field in Rio Branco, Brazil, with a total of 600 images classified among 300 photos of sick plants, with fish eyes among others and 300 photos of healthy plants. For many of the photos, a simple smartphone
camera was used to capture the images.
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929 Views
SeaIceWeather Dataset
This is the SeaIceWeather dataset, collected for training and evaluation of deep learning based de-weathering models. To the best of our knowledge, this is the first such publicly available dataset for the sea ice domain. This dataset is linked to our paper titled: Deep Learning Strategies for Analysis of Weather-Degraded Optical Sea Ice Images. The paper can be accessed at: https://doi.org/10.1109/jsen.2024.3376518
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326 Views
Any damage that affects the normal functioning of the lungs is termed as a lung disease,
which can prove fatal if not detected early. To address this challenge, two innovative techniques proposed
for the lung disease classification, supporting medical professionals to diagnose and provides preventive
measures at an early stage. The proposed Model 1 integrates a custom MobileNetV2L2 architecture, that
builds upon the MobileNetV2 framework through fine-tuning and customization. This model incorporates a
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934 Views
Completely contactless user identification using palm images acquired from the mobile and handheld devices is a challenging research problem. This database has been acquired from over 600 different subjects, which is the largest to-date and is also made available in public domain to advance much needed research in this area.
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314 Views
This is the dataset used in the paper "Application of improved lightweight network and Choquet fuzzy ensemble technology for soybean disease identification". This data set contains 6 types of soybean disease leaves collected from Xiangyang Farm, Nengjiang Farm and Jiusan Farm of Northeast Agricultural University in Heilongjiang Province from early June to late September 2019. All images are collected in natural scenes. A total of 1620 disease images of soybean leaves were collected.
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215 Views
This is the dataset used in the paper "Application of improved lightweight network and Choquet fuzzy ensemble technology for soybean disease identification". This data set contains 6 types of soybean disease leaves collected from Xiangyang Farm, Nengjiang Farm and Jiusan Farm of Northeast Agricultural University in Heilongjiang Province from early June to late September 2019. All images are collected in natural scenes. A total of 1620 disease images of soybean leaves were collected.
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48 Views