Learning models for predicting pavement friction based on non-contact texture measurements: Comparative assessment by Xiuquan Lin, You Zhan, Zilong Nie, Joshua Qiang Li, Xinyu Zhu, Allen A. Zhang

“…By assessing the importance of the 38 parameter variables, the most critical 21 variables were selected for model development. …”
Get full text

Multimodal sleep staging network based on obstructive sleep apnea by Jingxin Fan, Jingxin Fan, Jingxin Fan, Mingfu Zhao, Li Huang, Li Huang, Bin Tang, Bin Tang, Lurui Wang, Zhong He, Zhong He, Xiaoling Peng

“…The Multi-Scale Feature Extraction Module (MFEM) employs convolutional layers with varying dilation rates to capture spatial patterns from fine to coarse granularity. …”
Get full text

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. …”
Get full text

Deep quanvolutional neural networks with enhanced trainability and gradient propagation by Muhammad Kashif, Muhammad Shafique

“…Abstract In this paper, we explore methods to enhance the performance of one of the frequently used variants of Quantum Convolutional Neural Networks, known as Quanvolutional Neural Networks (QuNNs) by introducing trainable quanvolutional layers and addressing the challenges associated with training multi-layered or deep QuNNs. …”
Get full text

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.…”
Get full text

Maui: modular analytics of UAS imagery for specialty crop research by Kathleen Kanaley, Maylin J. Murdock, Tian Qiu, Ertai Liu, Schuyler E. Seyram, Dominik Starzmann, Lawrence B. Smart, Kaitlin M. Gold, Yu Jiang

“…Of the five canopy segmentation methods we tested, a supervised deep convolutional neural network (DeepLabv3) and a vision foundation model (SAM) produced the most accurate crop masks for the vineyard and hemp images, with mean intersection over union (mIoU) values of 0.85 and 0.95, respectively. …”
Get full text

Near real-time LOD prediction using ConvLSTM model through integrating IGS rapid LOD and effective angular momentum by Kehao Yu, Xiaoya Wang, Zhao Li, Jian Wang, Lihua Li, Weiping Jiang, Kai Yang, Jingwen Long, Yunzhao Li

“…To address the aforementioned issues, we propose an algorithm for predicting LOD that adopts a convolutional long-short-term memory (ConvLSTM) method with different base sequence lengths based on the LOD series from the IERS EOP C04, effective angular momentum (EAM) datasets and GNSS near-real-time (NRT) LOD data from the International GNSS Services (IGS) Rapid Products. …”
Get full text

Role of Biological Age in the Determination of Long‐Term Cause‐Specific Death Following Percutaneous Coronary Interventions by Mandeep Singh, Paul A. Friedman, Rajiv Gulati, Abdallah El Sabbagh, Bradley R. Lewis, Amrit Kanwar, Claire E. Raphael, Mohammed A. Al‐Hijji, Zachi I. Attia, Atta Behfar, James L. Kirkland

“…Age‐Gap was calculated as the difference between chronological age and age estimated by artificial intelligence ECG using a convolutional neural network. The full biological age model included deficits, functional impairments, and Age‐Gap >2 SD. …”
Get full text

Wheat Powdery Mildew Severity Classification Based on an Improved ResNet34 Model by Meilin Li, Yufeng Guo, Wei Guo, Hongbo Qiao, Lei Shi, Yang Liu, Guang Zheng, Hui Zhang, Qiang Wang

“…The model architecture was also optimized by modifying the first convolutional layer (conv1)—replacing the original 7 × 7 kernel with a 3 × 3 kernel, adjusting the stride to 1, and setting padding to 1—to better capture fine-grained leaf textures and edge features. …”
Get full text

Scalable AI-driven air quality forecasting and classification for public health applications by Mohammad Wasil Jalali, Bahir Saidi, Habibullah Farahmand, Mohammad Aref Rezvan Panah, Eda Nur Saruhan

“…Abstract Background Air pollution remains one of the most pressing public health and environmental issues, particularly in developing countries like Afghanistan, where reliable air quality monitoring infrastructure is lacking. …”
Get full text

Post marketing safety assessment of the novel postpartum depression drug, Zuranolone: evidence from real-world pharmacovigilance analysis based on the FDA adverse event reporting s... by Duoqin Huang, Zixin Luo, Xi Gong, Kang Zou, Yu Peng, Shaoying Zeng

“…A total of 142 Preferred Terms (PTs) were identified across 18 System Organ Classes (SOCs). Most reports originated from the United States, with various health professionals and consumers being the main reporters. …”
Get full text

Leveraging edge computing and deep learning for the real-time identification of bean plant pathologiesBean Plant Pathologies Dataset for Deep Learning Tasks by Andrew Katumba, Wayne Steven Okello, Sudi Murindanyi, Joyce Nakatumba-Nabende, Moses Bomera, Ben Wycliff Mugalu, Amos Acur

“…Beans are essential crops globally, standing out as one of the most consumed and nourishing legumes, thereby playing a significant role in human nutrition and food security. …”
Get full text

Oral atogepant mitigates spreading depolarization-induced pain and anxiety behavior in mice by Melih Z. Kaya, Pradeep Banerjee, Cenk Ayata, Andrea M. Harriott

“…Abstract Background Spreading depolarization (SD) is the most likely cause of migraine aura and may be linked to trigeminal nociception. …”
Get full text

Graph Neural Network Learning on the Pediatric Structural Connectome by Anand Srinivasan, Rajikha Raja, John O. Glass, Melissa M. Hudson, Noah D. Sabin, Kevin R. Krull, Wilburn E. Reddick

“…While graph neural networks (GNNs), specifically graph convolutional networks (GCNs), have gained popularity lately for their effectiveness in learning on graph data, achieving strong performance in adult sex classification tasks, their application to pediatric populations remains unexplored. …”
Get full text

The Influence of Viewing Geometry on Hyperspectral-Based Soil Property Retrieval by Yucheng Gao, Lixia Ma, Zhongqi Zhang, Xianzhang Pan, Ziran Yuan, Changkun Wang, Dongsheng Yu

“…Hyperspectral technology has been widely applied to the retrieval of soil properties, such as soil organic matter (SOM) and particle size distribution (PSD). However, most previous studies have focused on hyperspectral data acquired from the nadir direction, and the influence of viewing geometry on hyperspectral-based soil property retrieval remains unclear. …”
Get full text

A multimodal deep learning architecture for predicting interstitial glucose for effective type 2 diabetes management by Muhammad Salman Haleem, Daphne Katsarou, Eleni I. Georga, George E. Dafoulas, Alexandra Bargiota, Laura Lopez-Perez, Miguel Rujas, Giuseppe Fico, Leandro Pecchia, Dimitrios Fotiadis, Gatekeeper Consortium

“…The CGM time series were processed using a stacked Convolutional Neural Network (CNN) and a Bidirectional Long Short-Term Memory (BiLSTM) network followed by an attention mechanism. …”
Get full text

Novel Approaches for the Early Detection of Glaucoma Using Artificial Intelligence by Marco Zeppieri, Lorenzo Gardini, Carola Culiersi, Luigi Fontana, Mutali Musa, Fabiana D’Esposito, Pier Luigi Surico, Caterina Gagliano, Francesco Saverio Sorrentino

“…Background: If left untreated, glaucoma—the second most common cause of blindness worldwide—causes irreversible visual loss due to a gradual neurodegeneration of the retinal ganglion cells. …”
Get full text

Hybrid Machine Learning Model for Efficient Botnet Attack Detection in IoT Environment by Mudasir Ali, Mobeen Shahroz, Muhammad Faheem Mushtaq, Sultan Alfarhood, Mejdl Safran, Imran Ashraf

“…Botnet attack emerged as one of the most harmful attacks. Botnet identification is becoming challenging due to the numerous attack vectors and the ongoing evolution of viruses. …”
Get full text

CNN Based Fault Classification and Predition of 33kw Solar PV System with IoT Based Smart Data Collection Setup by K. Punitha, G. Sivapriya, T. Jayachitra

“…By analysing data from sensors and system logs, ML algorithms can identify patterns indicative of faults or inefficiencies, such as shading, soiling, or equipment malfunctions, often before they become serious issues. Convolutional Neural Networks (CNNs) are a class of deep learning algorithms most commonly applied. …”
Get full text

Inequalities in Mild Cognitive Impairment Risk Among Chinese Middle-Aged and Older Adults: Insights from an Integrated Learning Model by Bi S, Guo D, Tan H, Chen Y, Li G

“…Education emerged as the most critical predictor, followed by Instrumental Activities of Daily Living (IADL) and gender. …”
Get full text