Artificial Intelligence
There are 84168 blogs in the dataset.
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A total of 10,003 images of product design submissions of Hardware Product Design Competitionwere collected to form the product design image database, which has 835 samples of awarded class (high aesthetic level), 4,990 samples of qualified class (middle aesthetic level) and 4,178 samples of eliminated class (low aesthetic level). The Product Design Aesthetic Database includes dataset of image features extracted by the optimal method VGG-19.
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Real-World Multimodal Foodlog Database (RWMF) database is built for evaluating the multimodal retrieval algorithm in real-life dietary environment, and it has 7500 multimodal pairs in total, where each image can be related to multiple texts and each text can be related to multiple images. Details of this database can be found in this paper: Pengfei Zhou, Cong Bai, Kaining Ying, Jie Xia, Lixin Huang, RWMF: Real-World Multimodal Foodlog Database, ICPR 2020
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This dataset concludes source data which is professional fact descriptions from Chinese law office website and target data which is non-professional fact descriptions from daily spoken language.
The dataset is for transfer learning in law domain.
The dataset also concludes processed dictionary and .npy files.
The task of transfer learning is to predict the accusation based on the description.
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Music and animal's basic emotions associated with acoustic signals.
Files associated with animals’ sounds mainly were based on the records from Volodins Bioacoustic Group Homepage
http://www.bioacoustica.org/index_eng.html
http://www.bioacoustica.org/gallery/gallery_rus.html
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Mosquito bites result in the deaths of more than 1 million people every year. Certain species of mosquitos like Aedes are the main vector of arboviruses that cause Dengue, Malaria and Yellow fever. Image based mosquito species classification can be helpful to implement strategies to prevent the spread of mosquito borne disease. Automated mosquito species classification can aid in laborious and time consuming task of entomologists besides enhancing accuracy.
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Model .h5 files and .pb files for robustly detecting glaucoma from optical coherence tomography (OCT) images and for interpretability analysis via testing with concept activation vectors (TCAVs by Been Kim et al.). Further details described in paper "Robust and Interpretable Convolutional Neural Networks to Detect Glaucoma in OCT Images" in preparation/under review.
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This paper aims to improve the existing techniques on X-ray image inspection of aerial engine by using artificial intelligence (AI) based object detection model. This technique seeks to augment and improve existing automated non-destructive testing (NDT) diagnosis of metal structure of engine parts. Traditional jet-engine maintenance and overhaul processes are resorted to NDT to find defects in internal welds. An application of deep learning for NDT technology can effectively identify presence and location of up to eight types of defects, leading to enhanced work quality and efficiency.
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