Brain Tumor Classification of Medical Images based on Transfer Pre-trained Learning Models by Mohamed H Ghaleb Abdkhaleq Abdkhaleq, Ibraheem Al-Jadir, Loay George, Yuri Yuryevich Gromov, Eliseev Aleksey Igorevich

“…Transfer learning greatly facilitates the classification of different forms of brain tumors visible in medical imaging, enabling the achievement of this target. Utilizing pre-trained neural network models capitalizes on their comprehension of visual attributes and patterns by adjusting to the specific activity with efficiency and accuracy. …”
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Research on Simultaneous Localization and Intrusion Detection Methodology for Intelligent Trains Based on Multisource Fusion by ZENG Xiang, JIANG Guotao, LYU Yu, LI Cheng, PAN Wenbo, LUO Ziqi

“…Finally, time synchronization is established between the LiDAR and visual data, based on train localization information and IMU data. …”
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Fast and Accurate Video Analysis and Visualization of Classroom Activities Using Multiobjective Optimization of Extremely Low-Parameter Models by Venkatesh Jatla, Sravani Teeparthi, Ugesh Egala, Sylvia Celedon-Pattichis, Marios S. Pattichis

“…We then introduce a separable, extremely low-parameter system for video activity recognition that can be optimally trained using the derived datasets without the need for transfer learning from larger systems trained on large datasets. …”
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Building performance simulation for sensemaking in architectural pedagogy by Martha Bohm

“…Students used BPS to design buildings, using visual audits to build trust in the results about performance; precision was downplayed in favor of actionable information. …”
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Challenges of Disaster Assessment of Readiness and Training Guideline (DART) in Iran’s Primary Health Care by Hamzeh Zarei, Mohammad H. Yarmohammadian, Nikoo Yamani, Golrokh Atighechian, Fatemeh Rezaei

“…Background: DART (Disaster Assessment of Readiness and Training program) is one of the five Disaster Risk Reduction Management Programs (DRRMP) in Primary Health Care (PHC) of Iran. …”
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Analysis of a Novel Training Game with Eye Tracking and Electromyography for Autonomous Wheelchair Control by Peter Smith, Matt Dombrowski, Viviana Rivera, Maanya Pradeep, Delaney Gunnell, John Sparkman, Albert Manero

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The efficacy of training on the four quadrant brain processes on cognitive functions of students with mathematical disorders by zohreh sadat moeini, farnaz Keshavarzi Arshadi, Masoud Gholam Ali Lavasani, SAEED hasanzadeh

“…Results: The results of the research showed that the training package on the four quadrant brain processing skills had a significant effect on cognitive functions and subscales of visual-spatial ability, fluid reasoning, active memory, and processing speed of students with mathematical learning disorders. …”
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Gamelan Notation Reading Training for Elementary School Students at SDN Kedunglosari, Tembelang, Jombang by Wahyudi Wahyudi, Ayu Titis Rukmana Sari, Sutrisno Sahari, Bagus Amirul Mukmin, Wahid Ibnu Zaman, Abdul Aziz Hunaifi, Kukuh Andri Aka, Ronny Mahardika

“…The main objective was to provide basic understanding of the numerical symbols (1–7) in Javanese gamelan notation and to improve students' ability to read and perform gamelan notation collaboratively. The methods used included demonstrative and participatory approaches through hands-on practice, tone-based educational games, and visual media. …”
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Parameter-efficient adaptation with multi-channel adversarial training for far-field speech recognition by Tong Niu, Yaqi Chen, Dan Qu, Hengbo Hu, ChengRan Liu

“…Abstract Despite notable advancements in automatic speech recognition (ASR) technologies, issues such as background noise, reverberation, and speaker distance still degrade the performance of far-field speech recognition (FSR). Although large-scale pre-trained models have shown promise, their adaptation to FSR is hampered by high training costs and risks of overfitting. …”
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The Choice of Training Data and the Generalizability of Machine Learning Models for Network Intrusion Detection Systems by Marcin Iwanowski, Dominik Olszewski, Waldemar Graniszewski, Jacek Krupski, Franciszek Pelc

“…This paper studies the generalizability of models trained on such datasets. This issue is crucial given the application of such a model to actual internet traffic because high-performance measures obtained on datasets do not necessarily imply similar efficiency on the real traffic. …”
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Students' performance prediction employing Decision Tree by Abtahi Ahmed, Farzana Akter Nipa, Wasi Uddin Bhuyian, Khaled Md Mushfique, Kamrul Islam Shahin, Huu-Hoa Nguyen, Dewan Md. Farid

“…Traditional machine learning algorithms perform quite well in general, with SVM giving a best accuracy of around 95% with academic data, while training and testing the model without academic data still gives a good performance of 93%. …”
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Students' performance prediction employing Decision Tree by Abtahi Ahmed, Farzana Akter Nipa, Wasi Uddin Bhuyian, Khaled Md Mushfique, Kamrul Islam Shahin, Huu-Hoa Nguyen, Dewan Md. Farid

“…Traditional machine learning algorithms perform quite well in general, with SVM giving a best accuracy of around 95% with academic data, while training and testing the model without academic data still gives a good performance of 93%. …”
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Tracking the development of technical-tactical skills in judo athletes with visual impairments over four Paralympic cycles (2012-2024) by Rafael Kons, Vinicius Gulias, Nathalie Azeredo Bahiense Gomes

“…The findings provide valuable aspects into the technical-tactical performance of judo athletes with visual impairments, highlighting the consistency of technique preferences across multiple Paralympic Games. …”
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Tracking the development of technical-tactical skills in judo athletes with visual impairments over four Paralympic cycles (2012-2024) by Rafael Kons, Vinicius Gulias, Nathalie Azeredo Bahiense Gomes

“…The findings provide valuable aspects into the technical-tactical performance of judo athletes with visual impairments, highlighting the consistency of technique preferences across multiple Paralympic Games. …”
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Learning to search. The importance of eye movements in the decrease of response times during a visual choice reaction time task by Aleksandra Kroll, Monika Mak, Jerzy Samochowiec

“…While extensive research has been conducted on the possible response time correlates, the role of eye movements in visual tasks is yet unclear. Here we report data to support the role of eye movements during visual choice reaction time training. …”
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Prostate Cancer Detection by Novice Micro-Ultrasound Users Enrolled in a Training Program by Hannes Cash, Sebastian Hofbauer, Neal Shore, Christian P. Pavlovich, Stephan Bulang, Martin Schostak, Erik Planken, Joris J. Jaspars, Ferdinand Luger, Laurence Klotz, Georg Salomon

“…ObjectiveMicro-ultrasound is an imaging modality used to visualize and target prostate cancer during transrectal or transperineal biopsy. …”
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Development, validation, and visualization of a web-based nomogram for predicting chronic kidney disease incidence at health examination centers by Chuxuan Luo, Lanjun Fu, Lin Liu, Maosheng Chen, Kunliang Chen, Yiwen Li, Bo Lin, Juan Jin, Bin Zhu, Qiang He, Lina Shao

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GOME-NGU: Visual Navigation Under Sparse Reward via Goal-Oriented Memory Encoder With Never Give Up by Ji Sue Lee, Jun Moon

“…For both 1) and 2), training was conducted using NVIDIA Isaac Gym, and validation was performed by migrating to Isaac Sim. …”
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Dual-Alignment CLIP: Task-Specific Alignment of Text and Visual Features for Few-Shot Remote Sensing Scene Classification by Dongmei Deng, Ping Yao

“…To address these issues, we design a multilevel image–text feature alignment (MITA) component to align the multimodal embeddings with visual-guided text features from instance, class, and random level, and an image–image feature alignment (IIA) component to reliably measure the similarity between images by remapping these visual features from image–text alignment embedding space to image–image alignment feature space. …”
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Transfer Learning based Image Classification of Diseased Tomato Leaves with Optimal Fine-Tuning combined with Heat Map Visualization by Sivakumar Palanıswamy, Vijayakumar Vaıthyam Rengarajan, Sandhya Devi Ramıah Subburaj

“…The most identified limitation in the study of plant pathology is the availability of datasets with visual symptoms that covers all the possible diseases of one crop or plant species. …”
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