Identification of Subtypes of Post-Stroke and Neurotypical Gait Behaviors Using Neural Network Analysis of Gait Cycle Kinematics by Andrian Kuch, Nicolas Schweighofer, James M. Finley, Alison McKenzie, Yuxin Wen, Natalia Sanchez

“…We first trained a Convolutional Neural Network and a Temporal Convolutional Network to extract features that distinguish impaired from neurotypical gait. …”
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Artificial intelligence links CT images to pathologic features and survival outcomes of renal masses by Ying Xiong, Linpeng Yao, Jinglai Lin, Jiaxi Yao, Qi Bai, Yuan Huang, Xue Zhang, Risheng Huang, Run Wang, Kang Wang, Yu Qi, Pingyi Zhu, Haoran Wang, Li Liu, Jianjun Zhou, Jianming Guo, Feng Chen, Chenchen Dai, Shuo Wang

“…Abstract Treatment decisions for an incidental renal mass are mostly made with pathologic uncertainty. Improving the diagnosis of benign renal masses and distinguishing aggressive cancers from indolent ones is key to better treatment selection. …”
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Harnessing the synergy of statistics and deep learning for BCI competition 4 dataset 4: a novel approach by Gauttam Jangir, Nisheeth Joshi, Gaurav Purohit

“…In this mechanism finger’s movement is mostly performed for every day’s task. It is well known that to capture such movement EEG or ECoG signals are used. …”
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Deep quanvolutional neural networks with enhanced trainability and gradient propagation by Muhammad Kashif, Muhammad Shafique

“…Traditional QuNNs mostly rely on static (non-trainable) quanvolutional layers, limiting their feature extraction capabilities. …”
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Learning a Robust Hybrid Descriptor for Robot Visual Localization by Qingwu Shi, Junjun Wu, Zeqin Lin, Ningwei Qin

“…Finally, our experimental results mostly exceed state-of-the-art 2D image-based localization methods under various challenging environmental conditions in the Extended CMU Seasons and RobotCar Seasons datasets in specific precision metrics.…”
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VdaBSC: A Novel Vulnerability Detection Approach for Blockchain Smart Contract by Dynamic Analysis by Rexford Nii Ayitey Sosu, Jinfu Chen, Edward Kwadwo Boahen, Zikang Zhang

“…Methods currently used for identifying vulnerabilities in smart contracts mostly rely on static analysis methods that search for predefined vulnerability patterns. …”
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Multimodal fusion based few-shot network intrusion detection system by Congyuan Xu, Yong Zhan, Zhiqiang Wang, Jun Yang

“…Existing few-shot learning methods, while reducing reliance on large datasets, mostly handle single-modality data and fail to fully exploit complementary information across different modalities, limiting detection performance. …”
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Multi-stage framework using transformer models, feature fusion and ensemble learning for enhancing eye disease classification by Abdulaziz AlMohimeed

“…However, current methods mostly use single-model architectures, including convolutional neural networks (CNNs), which might not adequately capture the long-range spatial correlations and local fine-grained features required for classification. …”
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Interpretable classification of Levantine ceramic thin sections via neural networks by Sara Capriotti, Alessio Devoto, Simone Scardapane, Silvano Mignardi, Laura Medeghini

“…A dataset of 1424 thin section images from 178 ceramic samples belonging to several archaeological sites across the Levantine area, mostly from the Bronze Age, with few samples dating to the Iron Age, was used to train and evaluate these models. …”
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Improved Surface Electromyogram-Based Hand–Wrist Force Estimation Using Deep Neural Networks and Cross-Joint Transfer Learning by Haopeng Wang, He Wang, Chenyun Dai, Xinming Huang, Edward A. Clancy

“…However, prior studies focused mostly on applying TL within one joint, which limits dataset size and diversity. …”
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Accuracy of artificial intelligence in caries detection: a systematic review and meta-analysis by Alexander Maniangat Luke, Nader Nabil Fouad Rezallah

“…The meta-analysis incorporates fourteen of the 21 articles included in this review. The research mostly uses convolutional neural networks (CNNs) for analyzing images, showing outstanding accuracy, sensitivity, and specificity in detecting caries. …”
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Automated Quality Control of Candle Jars via Anomaly Detection Using OCSVM and CNN-Based Feature Extraction by Azeddine Mjahad, Alfredo Rosado-Muñoz

“…Its ability to generalize effectively from mostly normal samples makes it a practical and valuable solution for real-world industrial inspection systems. …”
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Automatic Road Extraction from Historical Maps Using Transformer-Based SegFormers by Elif Sertel, Can Michael Hucko, Mustafa Erdem Kabadayı

“…While transformer-based segmentation methods have been widely applied to image segmentation tasks, they have mostly focused on satellite images. There is a growing need to explore transformer-based approaches for geospatial object extraction from historical maps, given their superior performance over traditional convolutional neural network (CNN)-based architectures. …”
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MSTCNet: Toward Generalization Improving for Multiframe Infrared Small Target Detection by Ruining Cui, Na Li, Junfu Liu, Huijie Zhao

“…First, we utilize the advantages of convolutional neural networks and recurrent neural networks, integrating them to build a high-performance structure. …”
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Lightweight Indoor Positioning System Based on Multiple Self-Learning Features and Key Frame Classification by C. Wang, K. Bi, B. Zhao, M. Li, Y. Chen, S. Tao, J. Yang

“…Traditional indoor positioning technologies mostly require advanced installation of hardware devices, resulting in high costs and long-term maintenance. …”
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Accurate Sugarcane Detection and Row Fitting Using SugarRow-YOLO and Clustering-Based Spline Methods for Autonomous Agricultural Operations by Guiqing Deng, Fangyue Zhou, Huan Dong, Zhihao Xu, Yanzhou Li

“…Sugarcane is mostly planted in rows, and the accurate identification of crop rows is important for the autonomous navigation of agricultural machines. …”
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Advancing Author Gender Identification in Modern Standard Arabic with Innovative Deep Learning and Textual Feature Techniques by Hanen Himdi, Khaled Shaalan

“…Although studies in Arabic have mostly concentrated on written dialects, such as tweets, there is a paucity of studies addressing Modern Standard Arabic (MSA) in journalistic genres. …”
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Design of a deep fusion model for early Parkinson’s disease prediction using handwritten image analysis by Shyamala K, Navamani T M

“…Abstract Parkinson’s Disease (PD) is a deteriorating condition that mostly affects older people. The lack of conclusive treatment for PD makes diagnosis very challenging. …”
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Polarimetric SAR Ship Detection Using Context Aggregation Network Enhanced by Local and Edge Component Characteristics by Canbin Hu, Hongyun Chen, Xiaokun Sun, Fei Ma

“…In addition, neural network-based detection methods mostly rely on single polarimetric-channel scattering information and fail to fully explore the polarization properties and physical scattering laws of ships. …”
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Machine learning reveals immediate disruption in mosquito flight when exposed to Olyset nets by Yasser M. Qureshi, Vitaly Voloshin, Amy Guy, Hilary Ranson, Philip J. McCall, James A. Covington, Catherine E. Towers, David P. Towers

“…While IS mosquitoes displayed rapid, disordered trajectories and mostly died within 30 min, IR mosquitoes persisted throughout the 2-h experiments but exhibited similarly disturbed behaviour, suggesting resistance does not fully mitigate disruption. …”
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