Machine Learning
Semantic scene segmentation has primarily been addressed by forming representations of single images both with supervised and unsupervised methods. The problem of semantic segmentation in dynamic scenes has begun to recently receive attention with video object segmentation approaches. What is not known is how much extra information the temporal dynamics of the visual scene carries that is complimentary to the information available in the individual frames of the video.
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By querying open data of notorious scientific databases via representational state transfers, and subsequently enforcing data management practices with a dynamic topic modeling approach on the referred metadata available, this work achieves a feasible form of article set analysis and classification. Research trends for a given field in specific moments are identified, and also the referred trends evolution throughout the years.
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This dataset is used to train learners in our paper entitled: Hybrid Learning Aided Inactive Constraints Filtering Algorithm to Enhance AC OPF Solution Time
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A Indústria enfrenta desafios graves e fracassa sem competitividade. Atacando esta problemática, conferiu-se o oferecimento de maior eficiência a processos industriais para promover a produtividade, elevar a qualidade e impulsionar mudanças. A solução desenvolvida incluiu dispositivos com sensores não invasivos, simples de instalar, que contabilizam os itens sendo transportados em linhas de produção.
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This dataset contains four types of geospatial events coverage in Indonesian news online portal: flood, traffic jam, earthquake, and fire. The corpus itself was composed of 926 manually annotated, disambiguated, and event extracted sentences that was filtered from 83 of 645,679 documents of our earlier news corpus based on four major geospatial events: flood, earthquake, fire, and accidents.
Source: detik.com, kompas.com, cnnindonesia.com
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Power transmission system losses can typically represent from five to ten percent of the total generation, a quantity worth millions of dollars per year. The purpose of loss allocation in the context of pool dispatch is to assign to each individual generation and load the responsibility of paying for part of the system transmission losses. Since the system losses are non-separable, non-linear functions of the real power generation and loads, the allocation of transmission loss is a challenging and contentious issue in a fully deregulated system.
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This repository introduces a novel dataset for the classification of Chronic Obstructive Pulmonary Disease (COPD) patients and Healthy Controls. The Exasens dataset includes demographic information on 4 groups of saliva samples (COPD-HC-Asthma-Infected) collected in the frame of a joint research project, Exasens (https://www.leibniz-healthtech.de/en/research/projects/bmbf-project-exasens/), at the Research Center Borstel, BioMaterialBank Nord (Borstel, Germany).
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This is the dataset used in our journal paper, submitted to: IEEE Transactions on Dependable and Secure Computing, Special Issue on Explainable Artificial Intelligence for Cyber Threat Intelligence (XAI-CTI) Applications.
Submitted = 12-Jan-2021 (under review)
ID = TDSCSI-2021-01-0045
Source codes are available at IEEE Code Ocean:
Hatma Suryotrisongko (2020) Botnet DGA [Source Code]. https://doi.org/10.24433/CO.4005597.v2
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This is the raw MMG data.
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