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processing algorithm » processing algorithms (Expand Search)
modeling algorithm » scheduling algorithm (Expand Search)
maya algorithm » jaya algorithm (Expand Search)
pre processing » _ processing (Expand Search), image processing (Expand Search)
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Full-fledged semantic indexing and querying model designed for seamless integration in legacy RDBMS
Published 2018“…We then provide a general keyword query model with specially tailored query processing algorithms built on top of SemIndex, in order to produce semantic-aware results, allowing the user to choose the results' semantic coverage and expressiveness based on her needs. …”
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A Survey of Audio Enhancement Algorithms for Music, Speech, Bioacoustics, Biomedical, Industrial, and Environmental Sounds by Image U-Net
Published 2023“…We will discuss the need for AE, U-Net comparison to other DNNs, the benefits of converting the audio to 2D, input representations that are useful for different AE applications, the architecture of vanilla U-Net and the pre-trained models, variations in vanilla architecture incorporated in different E models, and the state-of-the-art AE algorithms based on U-Net in various applications. …”
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Genetic and heuristic algorithms for regrouping service sites. (c2000)
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Combining offline and on-the-fly disambiguation to perform semantic-aware XML querying
Published 2023“…Most methods rely on the concept of Lowest Comment Ancestor (LCA) between two or multiple structural nodes to identify the most specific XML elements containing query keywords posted by the user. Yet, few of the existing approaches consider XML semantics, and the methods that process semantics generally rely on computationally expensive word sense disambiguation (WSD) techniques, or apply semantic analysis in one stage only: performing query relaxation/refinement over the bag of words retrieval model, to reduce processing time. …”
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Content-Symmetrical Multidimensional Transpose of Image Sequences for the High Efficiency Video Coding (HEVC) All-Intra Configuration
Published 2025“…This work proposes a pre- and post-coding solution using the content-symmetrical multidimensional transpose of raw video sequences. …”
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Pre-production movie rating prediction using machine learning. (c2017)
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A kernelization algorithm for d-Hitting Set
Published 2010“…For a given parameterized problem, π, a kernelization algorithm is a polynomial-time pre-processing procedure that transforms an arbitrary instance of π into an equivalent one whose size depends only on the input parameter(s). …”
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Defense against adversarial attacks: robust and efficient compressed optimized neural networks
Published 2024“…This study compresses the generative pre-trained transformer (GPT) by 65%, saving time and memory without causing performance loss. …”
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SemIndex+: A semantic indexing scheme for structured, unstructured, and partly structured data
Published 2018“…We provide a general keyword query model allowing the user to choose the results’ semantic coverage and expressiveness based on her needs. …”
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Segmenting Handwritten Arabic Text
Published 2002“…The algorithm then generates pre-segmentation points for these blocks. …”
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A Neuro-Heuristic Approach for Segmenting Handwritten Arabic Text
Published 2001“…The algorithm then generates pre-segmentation points for these blocks. …”
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Salak Image Classification Method Based Deep Learning Technique Using Two Transfer Learning Models
Published 2022“…The dataset consists of 1000 images which having 250 of images for each type of salak. Pre-processing on the dataset is required to standardize the dataset by resizing the image into 224 * 224 pixels, convert into jpg format and augmentation. …”
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A neuro-heuristic approach for segmenting handwritten Arabic text. (c2001)
Published 2001Get full text
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Design of A Theoretical Framework For A Real-Time Fire Evacuation Guidance System
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A novel hybrid methodology for fault diagnosis of wind energy conversion systems
Published 2023“…The proposed technique involved two major steps: feature selection and fault classification. Feature selection pre-processing is an important step to increase the accuracy of the classification algorithm and decrease the dimensionality of a dataset. …”
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