Artificial Intelligence
This two files are dataset of throwing handover between two person. It contains 420 samples of 7 people. One of them is the gesture data of catcher before throwing and the other is for after throwing. They have the body and hands position and the score for throwing quality. This files are used to train the destination generation algorithm.
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The dataset that we published in this data repository can be used to build neural networks-based inverse kinematics for NAO robot arms. This dataset is named ARKOMA. ARKOMA is an acronym for ARif eKO MAuridhi, all of whom are the creators of this dataset. This dataset contains input-output data pairs. In this dataset, the input data is the end-effector position and orientation, while the output data is a set of joint angular positions. For further applications, this dataset was split into the training dataset, validation dataset, and testing dataset.
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The stock market is a volatile and nonlinear environment, making it difficult to predict returns accurately. However,
machine learning and deep learning models have been able to
achieve some degree of accuracy in predicting financial time
series. The recurrent neural networks (RNN) are derived from
the feedforward neural networks, a deep learning algorithm.
The cases of gradient vanishing and explosion are commonly
associated with the traditional RNNs. The Long-Short Term
Memory (LSTM) model is capable of eliminating the problems
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<p>Ten individuals in good health were enlisted to execute 16 distinct movements involving the wrist and fingers in real-time. Before commencing the experimental procedure, explicit consent was obtained from each participant. Participants were informed that they had the option to withdraw from the study at any point during the experimental session. The experimental protocol adhered to the principles outlined in the Declaration of Helsinki and received approval from the local ethics committee at the National University of Sciences and Technology, Islamabad, Pakistan.
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This dataset presents a synthetic thermal imaging dataset for Person Detection in Intrusion Warning Systems (PDIWS). The dataset consists of a training set with 2000 images and a test set with 500 images. Each image is synthesized by compounding a subject (intruder) with a background using the modified Poisson image editing method. There are 50 different backgrounds and nearly 1000 subjects divided into five classes according to five human poses: creeping, crawling, stooping, climbing and other. The presence of the intruder will be confirmed if the first four poses are detected.
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1145 Views
Specific emitter identification (SEI) is a promising authentication paradigm in physical layer security (PLS). Despite the significant success of existing SEI schemes, most of them assume that the distributions of the training dataset and the test dataset are consistent. However, in most practical scenarios, when the signal parameters change, the distribution of the samples will changes, resulting in a significant performance degradation.
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311 Views
This data set consists of 3-phase currents of faults and other transient cases for transmission lines connected with PV Farms. PSCAD/EMTDC software is used for the simulation of faults and other transients. Transmission lines connected to photovoltaic (PV) farm protection is crucial for ensuring reliable and safe operation. PV farms generate electricity from sunlight and feed it into the grid via transmission lines. However, factors such as fluctuations in solar irradiance, system faults, and grid instability can lead to voltage and current imbalances.
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560 Views
ommon approaches to stunting prediction, including statistical analysis and machine learning, have poor performance due to shifts in the factors influencing stunting. Causes data cannot be integrated directly when using statistical analysis. At the same time, machine learning causes a decrease in predictive performance down over time. This study proposes a new approach to stunting prediction in infants and toddlers aged 0-5 years using continuous learning methods.
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68 Views
"LaneVisionIITR: A Comprehensive High-Resolution Dataset for Lane Detection recorded at IIT Roorkee ", which is a newly built high-resolution dataset for developing Lane detection dataset for advanced driver assistance systems.
This folder consists of three files for each image:
1. The image captured in .jpg format.
2. Annotations (.json) having left and center line coordinates represented as “L” and “C” respectively.
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429 Views
Most plant diseases have observable symptoms, and the widely used approach to detect plant leaf disease is by visually examining the affected plant leaves. A model which might carry out the feature extraction without any errors will process the classification task successfully. The technology currently faces certain limitations such as a large parameter count, slow detection speed, and inadequate performance in detecting small dense spots. These factors restrict the practical applications of the technology in the field of agriculture.
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839 Views