Výsledky vyhledávání - Brain Based Learning Module

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  1. 1

    THE CIREMAI MOUNTAIN CURRICULUM IN A BRAIN-BASED LEARNING E-MODULE: AN EFFORT TO ENHANCE STUDENTS’ MATHEMATICAL CREATIVE THINKING ABILITY Autor Adiastuty, Nuranita, Aeni, Dilla Dzahrotul, Syafari, Rahayu

    ISSN: 2086-0234, 2579-7530
    Vydáno: 09.09.2025
    “…This study aims to develop a Brain-Based Learning (BBL) e-module based on the Gunung Ciremai Curriculum to enhance junior high school students' mathematical creative thinking on plane figures…”
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    Journal Article
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    Development of Teaching-Based Modules Brain Based Learning by Using Games in Mathematics Learning at Yapis Ranting 2 Middle School Timika Autor Hanudin, Sub, Herwin, Herwin, Rasul, A. Rasul

    ISSN: 2715-8799, 2715-9108
    Vydáno: 01.12.2024
    Vydáno v Abdi Masyarakat (01.12.2024)
    “…The aim of this research is to determine the feasibility of developing a brain-based learning mathematics module using a crossword puzzle game as seen from the level of validity, practicality and effectiveness…”
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    Improving Students Mathematical Critical Thinking Ability With Learning Modules Using Brain-Based Learning Models Autor Asfar, Nisa Ulkhairat, Permana, Dony, Fauzan, Ahmad, Yarman, Yarman

    ISSN: 2580-3573, 2580-2437
    Vydáno: 06.06.2022
    Vydáno v Numerical (Online) (06.06.2022)
    “… Mathematical critical thinking skills focus on activities in analyzing a more specific idea. Developing a learning module using a brain-based learning model is necessary to improve mathematical critical thinking skills…”
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    Optimization Driven Spike Deep Belief Neural Network classifier: a deep-learning based Multichannel Spike Sorting Neural Signal Processor (NSP) module for high-channel-count Brain Machine Interfaces (BMIs) Autor Reddy, Vanga Karunakar, Melingi, Sunil Babu, Kumar, Ch. V. M. S. N. Pavan, Kumar, K. Ashok, Mojjada, Ramesh Kumar

    ISSN: 0269-2821, 1573-7462
    Vydáno: Dordrecht Springer Netherlands 01.11.2023
    Vydáno v The Artificial intelligence review (01.11.2023)
    “…An Optimization Driven Spike Deep Belief Neural Networks is a type of neural network that is inspired by the functioning of the human brain…”
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    Convolutional Block Attention Module-based Deep Learning Model for MRI Brain Tumor Identification (ResNet-CBAM) Autor Shyamala, N., Mahaboobbasha, S.

    Vydáno: IEEE 18.09.2024
    “… A deep learning approach utilizing the ResNet-50 model integrated with Convolutional Block Attention Module (CBAM…”
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    Konferenční příspěvek
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    D-LMBmap: a fully automated deep-learning pipeline for whole-brain profiling of neural circuitry Autor Li, Zhongyu, Shang, Zengyi, Liu, Jingyi, Zhen, Haotian, Zhu, Entao, Zhong, Shilin, Sturgess, Robyn N., Zhou, Yitian, Hu, Xuemeng, Zhao, Xingyue, Wu, Yi, Li, Peiqi, Lin, Rui, Ren, Jing

    ISSN: 1548-7091, 1548-7105, 1548-7105
    Vydáno: New York Nature Publishing Group US 01.10.2023
    Vydáno v Nature methods (01.10.2023)
    “… To address these challenges, we developed D-LMBmap, an end-to-end package providing an integrated workflow containing three modules based on deep-learning algorithms for whole-brain connectivity mapping…”
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    A Transfer Learning-Based Approach for Brain Tumor Classification with Attention Module Autor Khan, Md. Ariful Haque, Hossain, Md Shakhawat

    Vydáno: IEEE 13.02.2025
    “… This study presents a system for classifying brain tumors using a transfer learning model enhanced by a self-attention mechanism…”
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    Leveraging Brain Modularity Prior for Interpretable Representation Learning of fMRI Autor Wang, Qianqian, Wang, Wei, Fang, Yuqi, Yap, Pew-Thian, Zhu, Hongtu, Li, Hong-Jun, Qiao, Lishan, Liu, Mingxia

    ISSN: 0018-9294, 1558-2531, 1558-2531
    Vydáno: United States IEEE 01.08.2024
    “…). However, existing learning-based methods cannot adequately utilize such brain modularity prior…”
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    ARM-Net: Improved MRI brain tumor segmentation method based on attentional mechanism and residual module Autor MingHu

    ISSN: 2032-9253, 2032-9253
    Vydáno: Ghent European Alliance for Innovation (EAI) 26.07.2024
    “… It proposes ARM-Net: an improved method for MRI brain tumor segmentation based on attention mechanisms and residual…”
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    The Effectiveness of OsiriX and the Anatomage Virtual Dissection Table in Enhancing Neuroanatomy and Neuroradiology Teaching Autor Sadiq, Zuhair, Laswi, Ibrahim, Raoof, Ameed

    ISSN: 1179-7258, 1179-7258
    Vydáno: Dove Medical Press Limited 01.01.2023
    “…: This aim of this study is to assess the effectiveness of online case- based learning modules in teaching medical students about the anatomy and radiology of different types of brain tumors. Methods…”
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    Brain signals of a Surprise-Actor-Critic model: Evidence for multiple learning modules in human decision making Autor Liakoni, Vasiliki, Lehmann, Marco P., Modirshanechi, Alireza, Brea, Johanni, Lutti, Antoine, Gerstner, Wulfram, Preuschoff, Kerstin

    ISSN: 1053-8119, 1095-9572, 1095-9572
    Vydáno: United States Elsevier Inc 01.02.2022
    Vydáno v NeuroImage (Orlando, Fla.) (01.02.2022)
    “… Current brain imaging of learning modules is limited by (i) simple experimental paradigms, (ii…”
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    Localization and Registration of 2D Histological Mouse Brain Images in 3D Atlas Space Autor Sadeghi, Maryam, Ramos-Prats, Arnau, Neto, Pedro, Castaldi, Federico, Crowley, Devin, Matulewicz, Pawel, Paradiso, Enrica, Freysinger, Wolfgang, Ferraguti, Francesco, Goebel, Georg

    ISSN: 1539-2791, 1559-0089, 1559-0089
    Vydáno: New York Springer US 01.07.2023
    Vydáno v Neuroinformatics (Totowa, N.J.) (01.07.2023)
    “…To accurately explore the anatomical organization of neural circuits in the brain, it is crucial to map the experimental brain data onto a standardized system of coordinates…”
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    Deep Dag Learning of Effective Brain Connectivity for FMRI Analysis Autor Yu, Yue, Kan, Xuan, Cui, Hejie, Xu, Ran, Zheng, Yujia, Song, Xiangchen, Zhu, Yanqiao, Zhang, Kun, Nabi, Razieh, Guo, Ying, Zhang, Chao, Yang, Carl

    ISSN: 1945-7928, 1945-8452
    Vydáno: United States IEEE 01.04.2023
    “…), which are noisy and can lead to inferior results for GNN models. To better adapt GNNs for fMRI analysis, we propose DABNet, a Deep DAG learning framework based on Brain Networks for fMRI analysis…”
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    Assessing the carbon footprint of soccer events through a lightweight CNN model utilizing transfer learning in the pursuit of carbon neutrality Autor Liu, Zhewei, Guo, Dayong

    ISSN: 2296-701X, 2296-701X
    Vydáno: Frontiers Media S.A 24.07.2023
    Vydáno v Frontiers in ecology and evolution (24.07.2023)
    “… context.MethodsOur proposed lightweight CNN model uses a downsampling module based on the human brain for efficient information processing and a transfer learning-based module to speed up the training progress…”
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    An improved attention module based on nnU-Net for segmenting primary central nervous system lymphoma (PCNSL) in MRI images1 Autor Zhao, Chen, Song, Jianping, Yuan, Yifan, Chu, Ying-Hua, Hsu, Yi-Cheng, Huang, Qiu

    ISSN: 1095-9114, 1095-9114
    Vydáno: United States 2024
    “… an improved attention module based on nnUNet for automated segmentation. We collected 114 T1 MRI images of patients in the Huashan Hospital, Shanghai…”
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    Integration of cooperative and opposing molecular programs drives learning-associated behavioral plasticity Autor Nelson, Jessica C., Shoenhard, Hannah, Granato, Michael

    ISSN: 1553-7404, 1553-7390, 1553-7404
    Vydáno: United States Public Library of Science 27.03.2023
    Vydáno v PLoS genetics (27.03.2023)
    “… an unexpected level of complexity. How the vertebrate brain integrates these various pathways to accomplish habituation learning, whether they act independently or intersect with one another, and whether they act via divergent…”
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    A whole brain probabilistic generative model: Toward realizing cognitive architectures for developmental robots Autor Taniguchi, Tadahiro, Yamakawa, Hiroshi, Nagai, Takayuki, Doya, Kenji, Sakagami, Masamichi, Suzuki, Masahiro, Nakamura, Tomoaki, Taniguchi, Akira

    ISSN: 0893-6080, 1879-2782, 1879-2782
    Vydáno: United States Elsevier Ltd 01.06.2022
    Vydáno v Neural networks (01.06.2022)
    “… This approach is based on two ideas: (1) brain-inspired AI, learning human brain architecture to build human-level intelligence, and (2…”
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