data of fishing operations from beidou, AIS and policy.

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Opportunity++ is a precisely annotated dataset designed to support AI and machine learning research focused on the multimodal perception and learning of human activities (e.g. short actions, gestures, modes of locomotion, higher-level behavior).

Instructions: 

Complete documentation is provided in the readme.

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The 5K EPP Dataset includes 5007 photos of water crystaks classified in 13 categories. This dataset was created under the leaderhip of Prof. Masaru Emoto.

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Human intention is an internal, mental characterization for acquiring desired information. Frominteractive interfaces, containing either textual or graphical information, intention to perceive desiredinformation is subjective and strongly connected with eye gaze. In this work, we determine such intention byanalyzing real-time eye gaze data with a low-cost regular webcam.

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Dementia classification from Magnetic Resonance Images by Machine Learning

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Our datasets_PAGML isbased on two public benchmark datasets SHREC2013 and SHREC2014. Sketches are the same as the original datasets. Each 3D shape in the the original datasets is represented as 12 views.

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This dataset is the supplementary material of an IEEE RAL paper named "Design of Fully Controllable and Continuous Programmable Surface Based on Machine Learning". It includes the z-displacement data derived from the FEA simulation, voltage input data derived from Matlab, and dataset for inverse application. The detailed description can be found in that paper.

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This dataset is composed by both real and sythetic images of power transmission lines, which can be fed to deep neural networks training and applied to line's inspection task. The images are divided into three distinct classes, representing power lines with different geometric properties. The real world acquired images were labeled as "circuito_real" (real circuit), while the synthetic ones were identified as "circuito_simples" (simple circuit) or "circuito_duplo" (double circuit). There are 290 total images for each class, 232 inteded for training and 58 aimed for validation/testing.

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The data has been collected using direct questionnaires from the patients of Sylhet Diabetes Hospital in Sylhet, Bangladesh and approved by a doctor.

This dataset is available in UCI Machine Learning Repository. 

 

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The data was collected and represents the historical data of 6 currency pairs measured in 4-hour intervals: 4 major pairs such as GBP/USD, EUR/USD, USD/CHF, USD/JPY and 2 minor pairs such as EUR/GBP and GBP/JPY.The data set covers the period from 01-2000 to 07-2020   Three files exists: the sequence dataset, the label dataset, and the legenda.The legenda reports the follwoing information:BBSignal, BBBreakoutSignal, LabelStrategy:
SIGNAL_NONE=0
SIGNAL_BUY=1
SIGNAL_SELL=2
BarType and HAType:
BAR_NONE=0
BAR_BULL=1
BAR_BEAR=2

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