Search Results - Brain Based Learning Module
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THE CIREMAI MOUNTAIN CURRICULUM IN A BRAIN-BASED LEARNING E-MODULE: AN EFFORT TO ENHANCE STUDENTS’ MATHEMATICAL CREATIVE THINKING ABILITY
ISSN: 2086-0234, 2579-7530Published: 09.09.2025Published in Jurnal pendidikan matematika dan IPA (Online) (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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Development of Teaching-Based Modules Brain Based Learning by Using Games in Mathematics Learning at Yapis Ranting 2 Middle School Timika
ISSN: 2715-8799, 2715-9108Published: 01.12.2024Published in 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
ISSN: 2580-3573, 2580-2437Published: 06.06.2022Published in 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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Learning Module Based on Brain Management and Mind Mapping to Train Mathematical Connection Abilities in Plane Geometry Course
ISSN: 1411-2531, 2685-5488Published: 2023Published in Jurnal Pendidikan MIPA (2023)Get full text
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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)
ISSN: 0269-2821, 1573-7462Published: Dordrecht Springer Netherlands 01.11.2023Published in 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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PENGEMBANGAN MODUL BERBASIS BRAIN BASED LEARNING PADA POKOK BAHASAN BARISAN DAN DERET ARITMATIKA TERHADAP PEMAHAMAN KONSEP SISWA: PENGEMBANGAN MODUL BERBASIS BRAIN BASED LEARNING PADA POKOK BAHASAN BARISAN DAN DERET ARITMATIKA TERHADAP PEMAHAMAN KONSEP SISWA
ISSN: 2721-5539, 2721-5539Published: 19.05.2024Published in MEGA: Jurnal Pendidikan Matematika (19.05.2024)“…This study aims to develop a Brain Based Learning – based module on the subject of arithmetic sequences and series onstudentsâ…”
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Convolutional Block Attention Module-based Deep Learning Model for MRI Brain Tumor Identification (ResNet-CBAM)
Published: IEEE 18.09.2024Published in 2024 5th International Conference on Smart Electronics and Communication (ICOSEC) (18.09.2024)“… A deep learning approach utilizing the ResNet-50 model integrated with Convolutional Block Attention Module (CBAM…”
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Conference Proceeding -
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D-LMBmap: a fully automated deep-learning pipeline for whole-brain profiling of neural circuitry
ISSN: 1548-7091, 1548-7105, 1548-7105Published: New York Nature Publishing Group US 01.10.2023Published in 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
Published: IEEE 13.02.2025Published in 2025 International Conference on Electrical, Computer and Communication Engineering (ECCE) (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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Conference Proceeding -
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The development of Organization of Living Things module through the use of mnemonic and mind mapping using a brain-based learning approach for junior high school Natural Science learning in coastal areas
ISSN: 2338-6630, 2541-5646Published: 29.12.2019Published in JURNAL BIOEDUKATIKA (29.12.2019)Get full text
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Leveraging Brain Modularity Prior for Interpretable Representation Learning of fMRI
ISSN: 0018-9294, 1558-2531, 1558-2531Published: United States IEEE 01.08.2024Published in IEEE transactions on biomedical engineering (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
ISSN: 2032-9253, 2032-9253Published: Ghent European Alliance for Innovation (EAI) 26.07.2024Published in EAI Endorsed Transactions on e-Learning (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
ISSN: 1179-7258, 1179-7258Published: Dove Medical Press Limited 01.01.2023Published in Advances in medical education and practice (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
ISSN: 1053-8119, 1095-9572, 1095-9572Published: United States Elsevier Inc 01.02.2022Published in 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
ISSN: 1539-2791, 1559-0089, 1559-0089Published: New York Springer US 01.07.2023Published in 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
ISSN: 1945-7928, 1945-8452Published: United States IEEE 01.04.2023Published in Proceedings (International Symposium on Biomedical Imaging) (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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Conference Proceeding Journal Article -
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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
ISSN: 2296-701X, 2296-701XPublished: Frontiers Media S.A 24.07.2023Published in 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
ISSN: 1095-9114, 1095-9114Published: United States 2024Published in Journal of X-ray science and technology (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
ISSN: 1553-7404, 1553-7390, 1553-7404Published: United States Public Library of Science 27.03.2023Published in 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
ISSN: 0893-6080, 1879-2782, 1879-2782Published: United States Elsevier Ltd 01.06.2022Published in 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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