Real time weed identification with enhanced mobilevit model for mobile devices by Xiaoyan Liu, Qingru Sui, Zhihui Chen

“…This capability allows it to accurately distinguish subtle differences between weeds and crops by leveraging a minimal number of modules. …”
Get full text

MFSE-TransUNet: A Thyroid Nodule Ultrasound Image Segmentation Network Integrated With Dynamic Feature Calibration and Edge Enhancement by Ye Lu, Jiaojiao Jing, Wenbo Zhang, Yali Kong

“…Although the existing TransUNet balances local and global features through a hybrid CNN-Transformer architecture, it still faces the following challenges in thyroid nodule segmentation: firstly, the fixed convolutional kernels struggle to adapt to nodule morphological diversity; Secondly, existing multi-scale feature fusion methods fail to consider hierarchical contribution differences; Furthermore, significant edge information is easily lost during upsampling. …”
Get full text

Improvement in positional accuracy of neural-network predicted hydration sites of proteins by incorporating atomic details of water-protein interactions and site-searching algorith... by Kochi Sato, Masayoshi Nakasako

“…Despite the effectiveness of the probability distribution, the positional differences of the predicted positions obtained from the local maxima as predicted sites remained inadequate in reproducing the hydration sites in the crystal structure models. …”
Get full text

Cell-TRACTR: A transformer-based model for end-to-end segmentation and tracking of cells. by Owen M O'Connor, Mary J Dunlop

“…Alongside this model, we introduce the Cell-HOTA metric, an extension of the Higher Order Tracking Accuracy (HOTA) metric that we adapted to assess cell division. Cell-HOTA differs from standard cell tracking metrics by offering a balanced and easily interpretable assessment of detection, association, and division accuracy. …”
Get full text

Real-Time Interference Mitigation for Reliable Target Detection with FMCW Radar in Interference Environments by Youlong Weng, Ziang Zhang, Guangzhi Chen, Yaru Zhang, Jiabao Chen, Hongzhan Song

“…The staged distillation approach alleviates the training difficulties associated with substantial differences between the teacher and student networks. …”
Get full text

Real-Time Player Engagement Measurement Using Nonintrusive Game Telemetry by Ammar Rashed, Shervin Shirmohammadi, Mohamed Hefeeda

“…Further cross-domain validation of the framework, as is and without transfer learning, with the games FIFA’23 and Street Fighter V, leads to 66% accuracy, demonstrating the model’s stable performance despite the significant differences in the test domains. Interestingly, our results suggest that objective gameplay metrics may better reflect engagement than subjective player assessments, with skill estimates showing significant correlation with self-reports.…”
Get full text

Motion Classification With Embroidery Bend Sensors Using Multiple Zigzag-Stitch for Loose-Fitting Garments by Kaisei Minami, Yasuhiro Akiyama, Takuya Umedachi

“…The model successfully learned the differences in signal amplitude and frequency as distinguishing features of each activity, resulting in an average classification accuracy of 99.02% across the ten types of activities.…”
Get full text

CF-YOLO for small target detection in drone imagery based on YOLOv11 algorithm by Chengcheng Wang, Yuqi Han, Chenggui Yang, Mingjie Wu, Zaiqing Chen, Lijun Yun, Xuesong Jin

“…Abstract Images captured from a drone’s perspective are significantly impacted in terms of target detection algorithm performance due to the notable differences in target scales and the presence of numerous small target objects lacking detailed information. …”
Get full text

Controlled and Real-Life Investigation of Optical Tracking Sensors in Smart Glasses for Monitoring Eating Behavior Using Deep Learning: Cross-Sectional Study by Simon Stankoski, Ivana Kiprijanovska, Martin Gjoreski, Filip Panchevski, Borjan Sazdov, Bojan Sofronievski, Andrew Cleal, Mohsen Fatoorechi, Charles Nduka, Hristijan Gjoreski

“…ResultsStatistical tests of mean sensor activations revealed statistically significant differences across all 6 comparison pairs (P<.001) involving 2 sensors (cheeks and temple) and 3 facial activities (eating, clenching, and speaking). …”
Get full text

AI-based body composition analysis of CT data has the potential to predict disease course in patients with multiple myeloma by Franz Wegner, Malte Maria Sieren, Hanna Grasshoff, Lennart Berkel, Christoph Rowold, Marcel Philipp Röttgerding, Soleiman Khalil, Sam Mogadas, Felix Nensa, René Hosch, Gabriela Riemekasten, Anna Franziska Hamm, Nikolas von Bubnoff, Jörg Barkhausen, Roman Kloeckner, Cyrus Khandanpour, Theo Leitner

“…The BCA algorithm, powered by a convolutional neural network, quantified tissue compartments and bone density based on routine CT scans. …”
Get full text

Learning Power Systems Waveform Incipient Patterns Through Few-Shot Meta-Learning by Lixian Shi, Qiushi Cui, Yang Weng, Yigong Zhang, Shilong Chen, Jian Li, Wenyuan Li

“…Next, at the meta-training stage, an adaptability-enhancing weighting initialization strategy is constructed to address the data differences between the meta-training stage and IF detection stage. …”
Get full text

Architecture-Aware Augmentation: A Hybrid Deep Learning and Machine Learning Approach for Enhanced Parkinson’s Disease Detection by Madjda Khedimi, Tao Zhang, Hanine Merzougui, Xin Zhao, Yanzhang Geng, Khamsa Djaroudib, Pascal Lorenz

“…These results highlight that hybrid models respond differently to augmentation, and careful selection of augmentation strategies is necessary for optimizing model performance. …”
Get full text

Predictive analytics in education- enhancing student achievement through machine learning by Sunawar khan, Tehseen Mazhar, Tariq Shahzad, Muhammad Amir khan, Wajahat Waheed, Ahsen Waheed, Habib Hamam

“…Additionally, key predictive factors such as studied credits, entrance results, and regional differences were identified, offering a comprehensive understanding of student performance. …”
Get full text

TCN-MAML: A TCN-Based Model with Model-Agnostic Meta-Learning for Cross-Subject Human Activity Recognition by Chih-Yang Lin, Chia-Yu Lin, Yu-Tso Liu, Yi-Wei Chen, Hui-Fuang Ng, Timothy K. Shih

“…However, real-world deployment faces two major challenges: (1) significant cross-subject signal variability due to physical and behavioral differences among individuals, and (2) limited labeled data, which restricts model generalization. …”
Get full text

Research on YOLOv5 Oracle Recognition Algorithm Based on Multi-Module Fusion by Xinhang Zhang, Zhenhua Ma, Yaru Zhang, Huiying Ru

“…However, traditional methods and some deep learning models have limited ability to capture the complex forms and fine details of oracle bone script, which makes it difficult to fully detect subtle differences between characters. Additionally, models trained on such data tend to struggle with recognizing rare or unseen characters, often leading to recognition errors. …”
Get full text

Optimizing physical education schedules for long-term health benefits by Liang Tan, Qin Chen, Jianwei Wu, Mingbang Li, Tianyu Liu

“…However, traditional approaches to optimizing PE schedules may not adequately account for individual differences in demographics and activity patterns.MethodsThis study proposes an efficient method for optimizing PE schedules using deep learning (DL) techniques. …”
Get full text

From Tables to Computer Vision: Transforming HPDC Process Data into Images for CNN-Based Deep Learning by A. Burzyńska

“…This paper proposes a methodology for leveraging convolutional neural networks (CNNs) in conjunction with advanced data preprocessing to facilitate optimal quality control decision-making in high pressure casting (HPDC) processes. …”
Get full text

Artificial intelligence in degenerative cervical disease: A systematic review of MRI-based diagnostic models by Qian Du, Xinxin Shao, Minbo Zhang, Guangru Cao

“…Sample sizes varied significantly, ranging from 28 to 900 patients. MRI protocols also differed across studies, with variations in field strengths, slice thicknesses, and sequences used. …”
Get full text

Machine Learning for Fire Safety in the Built Environment: A Bibliometric Insight into Research Trends and Key Methods by Mehmet Akif Yıldız

“…In order to evaluate the contribution of qualified publications to science more accurately, citation counts were analyzed using normalized citation counts that balanced differences in publication fields and publication years. …”
Get full text

Comparative Deep Learning–Based Facial Image Analysis for Early Autism Prediction in School-Aged Children by Sarah Sabeeh

“…All models significantly outperformed the chance baseline (p < 0.05), though pairwise differences in accuracy did not reach statistical significance at the α = 0.05 level. …”
Get full text