Showing 1 - 16 results of 16 for search 'sparse subset detection', query time: 0.08s Refine Results
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    Prewhitening Followed by Sampling Versus Sampling Followed by Prewhitening for Detection by Kaushallya Adhikari, Steven Kay, Russell Costa

    Published 2024-01-01
    “…However, when performing detection using only a subset of the Nyquist samples, the equivalence breaks down. …”
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    Article
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    Harnessing feature pruning with optimal deep learning based DDoS cyberattack detection on IoT environment by Eunmok Yang, Sooyong Jeong, Changho Seo

    Published 2025-05-01
    “…Besides, the feature pruning process is performed using an improved pelican optimization algorithm (IPOA), which enables the choice of an optimal subset of features. Meanwhile, DDoS attacks are recognized using a sparse denoising autoencoder (SDAE) model. …”
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    Article
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    A Novel Sparse False Data Injection Attack Method in Smart Grids with Incomplete Power Network Information by Huixin Zhong, Dajun Du, Chuanjiang Li, Xue Li

    Published 2018-01-01
    “…Finally, an effective sparse imperfect strategy is proposed by converting the choice of measurements into a subset selection problem, which is solved by the locally regularized fast recursive (LRFR) algorithm to effectively improve the sparsity of attack vectors. …”
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    Article
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    Deep learning-based feature selection for detection of autism spectrum disorder by Ibrahim Nafisah, Nermine Mahmoud, Ahmed A. Ewees, Mohamed G. Khattap, Abdelghani Dahou, Safar M. Alghamdi, Ibrahim A. Fares, Mohammed Azmi Al-Betar, Mohammed Azmi Al-Betar, Mohamed Abd Elaziz, Mohamed Abd Elaziz

    Published 2025-06-01
    “…Feature selection is enhanced through an optimized Hiking Optimization Algorithm (HOA) that integrates DynamicOpposites Learning (DOL) and Double Attractors to improve convergence toward the optimal subset of features.ResultsThe proposed model is evaluated using multiple ASD datasets. …”
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    Article
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    A Two-Stage Bayesian Receiver for Massive Grant-Free OFDM-NOMA With Interfering Pilot Symbols by Fakher Sagheer, Frederic Lehmann, Antoine O. Berthet

    Published 2025-01-01
    “…Massive grant-free non-orthogonal multiple access (NOMA) enables low-latency data transmission for a subset of coexisting user terminals, which may not be known a priori, and operates in an uncoordinated manner. …”
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    Public detection of lead plumbing and perceptions of municipal and well drinking water safety in the United States by Danielle E Lin Hunter, Valerie Ann Johnson, Emily Z Berglund, Caren B Cooper

    Published 2025-01-01
    “…We found 15% of homes had no detectable lead, 63% had trace levels (0.1–1 ppb), about 20% had detectable lead (between 1.0 and 15 ppb), and 5 households were at or above the action level of 15 ppb. …”
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    Deep learning with leagues championship algorithm based intrusion detection on cybersecurity driven industrial IoT systems by Saud S. Alotaibi, Turki Ali Alghamdi

    Published 2025-08-01
    “…Furthermore, the CLAFS-ODLCD method employs the CLAFS approach to choose optimal feature subset. Moreover, the detection and classification of the cyberattacks are accomplished by implementing the stacked sparse autoencoder (SSAE) approach. …”
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    Article
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    Integrating hybrid bald eagle crow search algorithm and deep learning for enhanced malicious node detection in secure distributed systems by Feras Mohammed Al-Matarneh

    Published 2025-04-01
    “…Besides, the HBECSA-DLMND method utilizes the HBECSA technique to choose a better subset of features. Meanwhile, the convolutional sparse autoencoder (CSAE) model detects malicious nodes. …”
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    Article
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    Enhancing Crack Segmentation With Limited Data: SinGAN-Based Synthesis and Blending of Textures and Cracks by Farhan Mahmood, Myrto Inglezou, Panagiotis Chatzakos, Antonis Porichis

    Published 2025-01-01
    “…Another aspect of our research is the validation of the synthesized dataset’s utility in improving crack detection and segmentation. Utilizing a subset of “CrackSeg9k” dataset as a benchmark, we employed two state-of-the-art crack segmentation methods, Pix2pix and DeepLabv3+, to evaluate the efficacy of our approach. …”
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    Optimizing Swine Oral Fluid Sampling Procedures for Growing Pigs in Commercial Settings by Grzegorz Tarasiuk, Marta D. Remmenga, Kathleen C. O’Hara, Marian K. Talbert, Sarah Mielke, Marisa L. Rotolo, Pam Zaabel, Danyang Zhang, Jeffrey J. Zimmerman

    Published 2024-12-01
    “…Pen-based oral fluids are used extensively for surveillance and disease detection in swine, but there is sparse information on the sampling process itself. …”
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    Central connectivity of transient receptor potential melastatin 8-expressing axons in the brain stem and spinal dorsal horn. by Yun Sook Kim, Jun Hong Park, Su Jung Choi, Jin Young Bae, Dong Kuk Ahn, David D McKemy, Yong Chul Bae

    Published 2014-01-01
    “…While synaptic boutons arising from Aδ and non-peptidergic C afferents usually receive many axoaxonic contacts and form complex synaptic arrangements, TRPM8+ boutons arising from afferents of the same classes of fibers showed a unique synaptic connectivity; simple synapses with one or two dendrites and sparse axoaxonic contacts. These findings suggest that TRPM8-mediated cold is conveyed via a specific subset of C and Aδ afferent neurons and is processed in a unique manner and differently in the TSN and DH.…”
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    An integrated model of multiple-condition ChIP-Seq data reveals predeterminants of Cdx2 binding. by Shaun Mahony, Matthew D Edwards, Esteban O Mazzoni, Richard I Sherwood, Akshay Kakumanu, Carolyn A Morrison, Hynek Wichterle, David K Gifford

    Published 2014-03-01
    “…We demonstrate that our framework enables the simultaneous modeling of sparse condition-specific binding changes, sequence dependence, and replicate-specific noise sources. …”
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    Learning on Bandwidth Constrained Multi-Source Data With MIMO-Inspired DPP MAP Inference by Xiwen Chen, Huayu Li, Rahul Amin, Abolfazl Razi

    Published 2024-01-01
    “…Particularly, DPP-based Maximum A Posteriori (MAP) inference is used to identify subsets with the highest diversity. However, a commonly adopted presumption of all data samples being available at one point hinders its applicability to real-world scenarios where data samples are distributed across distinct sources with intermittent and bandwidth-limited connections. …”
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    PROX1: a lineage tracer for cortical interneurons originating in the lateral/caudal ganglionic eminence and preoptic area. by Anna Noren Rubin, Nicoletta Kessaris

    Published 2013-01-01
    “…In the developing rodent cortex a sparse population of cells thought to correspond to late-generated cortical pyramidal neuron precursors expresses PROX1. …”
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