Showing 1 - 20 results of 1,418 for search '(( learning deep decrease ) OR ( b ((large decrease) OR (larger decrease)) ))', query time: 0.53s Refine Results
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    The introduction of mutualisms into assembled communities increases their connectance and complexity while decreasing their richness. by Gui Araujo (22170819)

    Published 2025
    “…When they stop being introduced in further assembly events (i.e. introduced species do not carry any mutualistic interactions), their proportion slowly decreases with successive invasions. (B) Even though higher proportions of mutualism promote higher richness, introducing this type of interaction into already assembled large communities promotes a sudden drop in richness, while stopping mutualism promotes a slight boost in richness increase. …”
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    Deep reinforcement learning process. by Sen Cao (6017846)

    Published 2025
    “…This study introduces an improved adaptive signal control approach using an enhanced dual-layer deep Q-network (EXP-DDQN), specifically tailored for intelligent connected environments. …”
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    Biases in larger populations. by Sander W. Keemink (21253563)

    Published 2025
    “…<p>(<b>A</b>) Maximum absolute bias vs the number of neurons in the population for the Bayesian decoder. …”
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    Dynamic Analysis of Membrane Emulsification: An In Situ Observation and Calculation with Deep Learning Model by Ke Zhou (131917)

    Published 2025
    “…In this study, a novel in situ observation device was developed, which couples a visible membrane module with a high-speed microscope system. Additionally, a deep learning model was embedded to realize the first visualization of the dynamic droplet formation process under demanding conditions. …”
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    Geographical distribution of large cities and small cities. by Saul Estrin (8629173)

    Published 2024
    “…The Figure reveals two patterns: 1) the maximum level of innovation is higher in large cities (2.53) than in small cities (2.02); 2) among large cities in <b>a</b>, innovation levels in general decrease with nightlight density. …”
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    Architecture of deep neural networks. by Ahmed Muqdad Alnasrallah (21647492)

    Published 2025
    “…This study proposes an IDS model for the IoMT that integrates advanced feature selection techniques and deep learning to enhance detection performance. The proposed model employs Information Gain (IG) and Recursive Feature Elimination (RFE) in parallel to select the top 50% of features, from which intersection and union subsets are created, followed by a deep autoencoder (DAE) to reduce dimensionality without losing important data. …”
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