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DEEP CONVOLUTIONAL NEURAL NETWORKS FOR WEED DETECTION IN AGRICULTURAL CROPS USING OPTICAL AERIAL IMAGES [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2020 The presence of weeds in agricultural crops has been one of the problems of greatest interest in recent years as they consume natural resources and negatively affect the agricultural process. For this purpose, a model has been implemented to segment weed
W. Ramirez +3 more
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SOUL: Scala Oversampling and Undersampling Library for imbalance classification
SoftwareX, 2021 The improvements in technology and computation have promoted a global adoption of Data Science. It is devoted to extracting significant knowledge from high amounts of information by means of the application of Artificial Intelligence and Machine Learning
Néstor Rodríguez +4 more
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SVDNVLDA: predicting lncRNA-disease associations by Singular Value Decomposition and node2vec
BMC Bioinformatics, 2021 Background Numerous studies on discovering the roles of long non-coding RNAs (lncRNAs) in the occurrence, development and prognosis progresses of various human diseases have drawn substantial attentions.
Jianwei Li +5 more
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IEEE Access, 2020 A high percentage of information that propagates through a social network is sourced from different exogenous sources. E.g., individuals may form their opinions about products based on their own experience or reading a product review, and then share that
Suman Kundu +3 more
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Context-Based User Typicality Collaborative Filtering Recommendation
Human-Centric Intelligent Systems, 2021 Since contextual information significantly affecting users’ decisions, it has attracted widespread attention. User typicality indicates the preference of user for different item types, which could reflect the preference of user at a higher abstraction ...
Jinzhen Zhang +3 more
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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021 The detection of critical infrastructures in large territories represented by aerial and satellite images is of high importance in several fields such as in security, anomaly detection, land use planning, and land use change detection.
Francisco Perez-Hernandez +4 more
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Feature ranking and rank aggregation for automatic sleep stage classification: a comparative study
BioMedical Engineering OnLine, 2017 Background Nowadays, sleep quality is one of the most important measures of healthy life, especially considering the huge number of sleep-related disorders. Identifying sleep stages using polysomnographic (PSG) signals is the traditional way of assessing
Shirin Najdi +2 more
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Selective kernel networks for weakly supervised relation extraction
CAAI Transactions on Intelligence Technology, 2021 The purpose of relation extraction is to identify the semantic relations between entities in sentences that contain two entities. Recently, many variants of the convolution neural network (CNN) have been introduced to relation extraction for the ...
Ziyang Li +4 more
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IEEE Access, 2019 Neural somas perform most of the metabolic activities in the neuron and support the chemical process that generates the basic elements of the synapses, and consequently the brain activity.
Sergio Luengo-Sanchez +2 more
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A Many Objective-Based Feature Selection Model for Anomaly Detection in Cloud Environment
IEEE Access, 2020 With the development of cloud computing technology (CCT), the processing of network traffic data becomes particularly important. However, the existing intrusion detection systems (IDS) are not efficient enough in analyzing network traffic data for ...
Zhixia Zhang +4 more
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