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This dataset is dedicated to the work " GeoSAM: Enhancing SAM with Sparse and Dense Visual Prompting for Automated Mobility Infrastructure Segmentation

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467 Views

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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229 Views

The existing datasets lack the diversity required to train the model so that it performs equally well in real fields  under varying environmental conditions. To address this limitation, we propose to collect a small number of in-field data and use the GAN to generate synthetic data for training the deep learning network. To demonstrate the proposed method, a maize dataset 'IIITDMJ_Maize'  was collected using a drone camera under different weather conditions, including both sunny and cloudy days. The recorded video was processed to sample image frames that were later resized to 224 x 224.

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50 Views

This simulation dataset contains five types of data: resolutions, vessels, vessel stenosis, tumors, and shape combinations. There are a total of 1000 original binary images. Besides, we set different gray values on images with multiple connected domains to simulate different concentration of magnetic nanoparticles. Next, the images are subjected to operations such as image inversion and image rotation. The final dataset contains 20,000 images. we applied the X-space method based on the X-space theory and we generated the simulated image of magnetic particle imaging.

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109 Views

Data diversity and volume are crucial to the success of training deep learning models, while in the medical imaging field, the difficulty and cost of data collection and annotation are especially huge. Specifically in robotic surgery, data scarcity and imbalance have heavily affected the model accuracy and limited the design and deployment of deep learning-based surgical applications such as surgical instrument segmentation.

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194 Views

*** The paper published on Multimedia Tools and Applications (Springer) - 2024 ***

*** Title: "SPRITZ-PS: Vlaidation of Synthetic Face Images Using A Large Dataset of Printed Docuemnts"***

*** Authors: Ehsan Nowroozi, Yoosef Habibi, and Mauro Conti ***

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541 Views

Object detection via images has advanced quickly over the last few decades, their detection accuracy, categorization, and localization are not consistent. Achieving fast and accurate detection of fashion products in the e-commerce environment is very important for selecting the right category. This is closely related to customer satisfaction and happiness which is a critical aspect. 

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769 Views