Artificial Intelligence
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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Recognition and classification of currency is one of the important task. It is a very crucial task for visually impaired people. It helps them while doing day to day financial transactions with shopkeepers while traveling, exchanging money at banks, hospitals, etc. The main objectives to create this dataset were:
1) Create a dataset of old and new Indian currency.
2) Create a dataset of Thai Currency.
3) Dataset consists of high-quality images.
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INDIA is the second-largest fruit and vegetable exporter in the world after China. It ranked first in the production of Bananas, Papayas, and Mangoes. Public datasets of fruits are available but they are limited to general fruit classes and failed to classify the fruits according to the fruit quality. To overcome this problem, we have created a dataset named FruitsGB (Fruits Good/Bad) dataset.
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Recently, self-driving vehicles have been introduced with several automated features including lane-keep assistance, queuing assistance in traffic-jam, parking assistance and crash avoidance. These self-driving vehicles and intelligent visual traffic surveillance systems mainly depend on cameras and sensors fusion systems.
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Load identification have shown significant performance gains in Chinese smart grids. Most existing load identification algorithms are based on electrical characteristics of steady or transient state, which are therefore limited by feature selection and analyzing pattern.
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