Homeostatic synaptic normalization optimizes learning in network models of neural population codes by Jonathan Mayzel, Elad Schneidman

“…Importantly, these RP models have a clear and biologically plausible implementation as shallow neural networks. We present a new class of RP models that are learned by optimizing the randomly selected sparse projections themselves. …”
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Language Learning Strategies Under the PBL Approach: Study of Seventh Graders’ Speaking by Glenis Gamarra-Pautt, Zoila Liliana Giraldo-Martínez

“… This study deeply examines the potential impact of Project-Based Learning (PBL) on the speaking abilities of a group of seventh-grade students at a public school in Cartagena, Colombia, and its connection to language learning strategies. …”
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MRI-Based Meningioma Firmness Classification Using an Adversarial Feature Learning Approach by Miada Murad, Ameur Touir, Mohamed Maher Ben Ismail

“…Specifically, we present two key contributions: (i) an unsupervised feature extraction approach utilizing the Bidirectional Generative Adversarial Network (BiGAN) and (ii) a depth-wise separable deep learning model were designed to map the relevant MRI features with the predefined meningioma firmness classes. …”
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From exclusion to empowerment: learning from the Dalit experience to empower the Bihari community by Bente Fatema

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Holistic Analysis of Differentiated Learning in Pancasila Education at Sekolah Penggerak in Padang City by Fadlihi Asmi, Maria Montessori, Al Rafni, Fatmariza Fatmariza

“… This study aims to describe the implementation of differentiated learning in the Pancasila education subject at “Sekolah Penggerak” (driving schools), analyze the challenges, and identify the efforts made to optimize its implementation using the indicators of content, process, product, and learning environment differentiation, focusing on students’ learning styles. …”
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Nosarara Nosabatutu: A Culturally Rooted Learning Model in the Midst of a Pandemic by Huber Yaspin Tandi, Herlina Herlina, Yuliantini Yuliantini, Lumuan Lumuan, Yusuf Yusuf, Andriyanto Andriyanto, Marites Del Prado Antonio

“…This research presents an innovation in the form of integrating the Nosarara Nosabatutu learning model with the Google Docs platform, which combines technology with local cultural values. …”
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Self-supervised learning reduces label noise in sharp wave ripple classification by Saber Graf, Pierre Meyrand, Cyril Herry, Tiaza Bem, Feng-Sheng Tsai

“…This critically impairs the accuracy and reliability of data classification, presenting significant barriers to extracting meaningful insights. …”
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Deep Learning Method for Wetland Segmentation in Unmanned Aerial Vehicle Multispectral Imagery by Pakezhamu Nuradili, Ji Zhou, Guiyun Zhou, Farid Melgani

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Beyond Handcrafted Features: A Deep Learning Framework for Optical Flow and SLAM by Kamran Kazi, Arbab Nighat Kalhoro, Farida Memon, Azam Rafique Memon, Muddesar Iqbal

“…This paper presents a novel approach for visual Simultaneous Localization and Mapping (SLAM) using Convolution Neural Networks (CNNs) for robust map creation. …”
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How do foreign language learning experiences influence the self-reference effect? by Xiaonan Dong, Jianshe Wu

“…These results suggest that the self-reference effect is present in both L2 beginners and advanced learners but is more pronounced in advanced learners. …”
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Inspection of railway catenary systems using machine learning with domain knowledge integration by Kacper Marciniak, Paweł Majewski, Jacek Reiner

“…This paper presents innovative solutions leveraging domain knowledge to significantly improve the inference quality of machine learning models using existing training data. …”
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HARNESSING MACHINE LEARNING IN HPV DIAGNOSTICS: MODEL PERFORMANCE, EXPLAINABILITY, AND CLINICAL INTEGRATION by Bahar Senel

“…Recent advances in machine learning (ML) have enabled more precise and automated HPV detection and genotyping. …”
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Smart multioutput fast charger for electric vehicles using deep learning controllers by Aayushi Priyadarshini, Shekhar Yadav, Nitesh Tiwari

“…The increasing adoption of electric vehicles has intensified the demand for efficient, high-performance charging solutions to address long charging times and range limitations. This paper presents the development of a smart multioutput Direct-current fast charger leveraging deep learning techniques to enhance electric vehicle battery charging capabilities. …”
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Machine Learning-Based Diabetes Risk Prediction Using Associated Behavioral Features by Ayodeji O. J. Ibitoye, Joseph D. Akinyemi, Olufade F. W. Onifade

“…The likelihood of diabetes in a patient is mostly predicted using machine learning (ML) models on features explicitly available in datasets, while the intrinsic relationship between features viz-a-viz their potential relevance to the presence of diabetes is oftentimes neglected. …”
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Representation Learning for Vision-Based Autonomous Driving via Probabilistic World Modeling by Haoqiang Chen, Yadong Liu, Dewen Hu

“…To address these challenges, we present BYOL-Drive, a novel method that firstly introduces the self-supervised representation-learning paradigm BYOL (Bootstrap Your Own Latent) to implement world modeling. …”
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MDPruner: Meta-Learning Driven Dynamic Filter Pruning for Efficient Object Detection by Lingyun Zhou, Xiaoyong Liu

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Empowering South African educators: Navigating the challenges of digital teaching and learning competencies by Trinity Nyathi, Renjini M. Joseph

“…Orientation: Public basic education institutions in South Africa are presently enduring new challenges about the implementation of digital teaching and learning in the absence of the digital competence required. …”
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Semi-Supervised Learned Autoencoder for Classification of Events in Distributed Fibre Acoustic Sensors by Artem Kozmin, Oleg Kalashev, Alexey Chernenko, Alexey Redyuk

“…Additionally, advanced signal processing algorithms are necessary for accurately determining the location and nature of detected events. In this paper, we present an enhanced approach based on semi-supervised learning for developing event classification models tailored for real-time and continuous perimeter monitoring of infrastructure facilities. …”
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Associative Mechanisms Allow for Social Learning and Cultural Transmission of String Pulling in an Insect. by Sylvain Alem, Clint J Perry, Xingfu Zhu, Olli J Loukola, Thomas Ingraham, Eirik Søvik, Lars Chittka

“…., group-specific behaviors that spread from "innovators" to others in the group via social learning. We first explored whether bumblebees can learn a nonnatural object manipulation task by using string pulling to access a reward that was presented out of reach. …”
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Machine learning evidence towards eradication of malaria burden: A scoping review by Idara JAMES, Veronica OSUBOR

“… Recent advancements have shown that shallow and deep learning models achieve impressive performance accuracies of over 97% and 98%, respectively, in providing precise evidence for malaria control and diagnosis. …”
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