This paper explores the transformative potential of Foundation Models (FMs) in agriculture, driven by the need for efficient and intelligent decision support systems in the face of growing global population and climate change. It begins by outlining...
Most deep-learning-based vision tasks rely heavily on crowd-labeled data, and a deep neural network (DNN) is usually impacted by the laborious and time-consuming labeling paradigm. Recently, foundation models (FMs) have been presented to learn richer...
In this paper, an experimental torsion resistance-loading system for wind power extended foundation scale models is taken as the research object, and four 1:3 scale model specimens of the foundation ring are tested. The transmission mechanism of torq...
Complex diseases, including cancer, rare genetic disorders, neurodevelopmental and psychiatric conditions, and neurodegenerative diseases, arise from interactions among genetic variation, gene regulation, and cellular states that are difficult to cap...
Foundation models have achieved remarkable success across various domains, but still face critical challenges such as limited data availability, high computational requirements, and rapid knowledge obsolescence. To address these issues, we propose a...
Rapid advancements in foundation models, including Large Language Models, Vision-Language Models, Multimodal Large Language Models, and Vision-Language-Action models, have opened new avenues for embodied AI in mobile service robotics. By combining fo...
For geotechnical structures with a strict control requirement of deformation, the high modulus and non-linear attenuation characteristics of the surrounding soil under small-strain conditions cannot be ignored during performance evaluation; the HSS c...
Deep reinforcement learning (DRL) and large foundation models (FMs) have reshaped modern artificial intelligence (AI) by enabling systems that learn from interaction while leveraging broad generalization and multimodal reasoning capabilities. This su...
Automated monitoring of cattle behavior through computer vision requires robust detection as a foundational step for tracking, re-identification, and behavior analysis. However, training accurate detection models typically demands extensive manually...
A series of centrifuge model tests were conducted to study the interaction between successively constructed adjacent foundation pits. The stress, deformation, and earth pressure on retaining structures and the settlement of the soil between the two a...
With the rapid development of traffic infrastructures in developing countries, the evaluation demands for the vertical capacities of in-service bridges are increasing. The feasibilities of the transient response method (TRM) and index of dynamic stif...
The Richards equation has high plasticity and compatibility. Compared with other curve equations, it has higher applicability and accuracy in describing S-shaped curves. It can describe the changes in the initial growth stage, rapid growth stage, and...
Generative artificial intelligence and foundation models have changed machine learning by allowing systems to produce readable text, realistic images, and other multimodal content with little direct input from a user. Foundation models are large neur...
This paper assesses trending AI foundation models, especially emerging computer vision foundation models and their performance in natural landscape feature segmentation. While the term foundation model has quickly garnered interest from the geospatia...
Vision-language foundation models have transformed medical image segmentation over the past three years. These models pair large image encoders with text prompts, so a single model can segment many anatomical structures, lesion types, and imaging mod...
Foundation models, known as the large-scale, pretrained models capable of generalizing across diverse tasks, have significantly advanced the field of medical image analysis. While most early applications focused on 2D modalities, the unique challenge...
The intriguing rocking behavior of foundations has attracted the attention of both researchers and professionals, owing to its beneficial characteristics such as energy absorption and self-adjusting capability. This paper offers a thorough examinatio...
For lithium-ion batteries, reliable fault detection for charging voltage is essential for operational safety and thermal failure prevention. However, existing battery monitoring solutions face a dual challenge: task-specific models are primarily chal...
Foundation models have shown remarkable generalization ability for few-shot learning (FSL). However, their potential for remote sensing scene classification has not been fully explored. Existing methods mainly adapt a single vision–language mod...
Data centers consumed 415 TWh of electricity in 2024, about 1.5% of global demand, and foundation model training and inference are a growing part of this load. As training and inference continue to grow, energy-efficient foundation models are becomin...
Advancing the capabilities of earthquake nowcasting, the real-time forecasting of seismic activities, remains crucial for reducing casualties. This multifaceted challenge has recently gained attention within the deep learning domain, facilitated by t...
The concept of rocking foundations has been successfully tested and promoted for building and bridge foundations. In this paper, the applicability of rocking foundations to wind turbines is investigated, specifically for wind turbines constructed on...
We investigate the applicability of visual foundation models, a recent advancement in artificial intelligence, for archaeological remote sensing. In contrast to earlier approaches, we employ a strictly zero-shot methodology, testing the hypothesis th...
Foundation deformation prediction on expansive soils involves complex soil-structure interactions and environmental variability. This study develops foundation-specific hybrid modeling approaches for temporal deformation prediction using 974 days of...
Foundation models (FMs) have become a paradigm shift in the field of artificial intelligence, allowing one large-scale pretrained model to be customized for a broad set of downstream tasks using very little task-specific data. These models, which inc...
Due to the high-fidelity mapping of the physical buildings and the intelligent performance shown in their lifecycle, digital twins (DTs) have gained increasing attention in the building sector. Although digital twins based on building information mod...
Finding a template location in a query image is a fundamental problem in many computer vision applications, such as localization of known objects, image registration, image matching, and object tracking. Currently available methods fail when insuffic...
Remote sensing image segmentation is a foundational task in Earth observation. With the rapid growth of remote sensing datasets in terms of scale, modality diversity, semantic openness, and spatio-temporal complexity, the field is evolving from task-...
The advancement of large-scale marine infrastructure demands increasingly accurate prediction of settlement in deep-water foundations. The caisson is an important type of deep-water foundation whose additional settlement induced by superstructure con...
In this study, the cyclic responses of an offshore wind turbine with a tripod foundation installed on an actual site were evaluated in a centrifuge. To understand the behavior of the turbine at the site, the site soil conditions, environmental loads,...
Foundation models are increasingly influencing software engineering research and practice, yet their adoption across the software development life cycle remains uneven and insufficiently characterized. This paper presents a systematic review of 224 r...
Automating activities in unstructured environments, such as construction sites, has been challenging due to unpredictable events, limiting robot adoption compared to structured settings. Recently, pre-trained foundation models, particularly Large Lan...
Automated Valuation Models (AVMs) have progressed from hedonic and spatial statistics to machine-learning architectures, yet most remain optimized for one target, market, and observation period. This review asks whether the foundation model paradigm...
Pile foundation is one of the most widely used deep foundation solutions, and the intelligent informatization of its design process holds significant theoretical and practical value. The innovation of this study lies in the construction of a systemat...
People with blindness and low vision (pBLV) encounter substantial challenges when it comes to comprehensive scene recognition and precise object identification in unfamiliar environments. Additionally, due to the vision loss, pBLV have difficulty in...
Background/Objectives: Glioma diagnosis increasingly depends on the integration of magnetic resonance imaging (MRI), molecular characteristics, and clinical information. Foundation models may support AI-assisted diagnosis through transferable represe...
Cell segmentation plays a key role in a wide range of biomedical imaging applications, from single-cell analysis to pathology assessment. While classical deep learning architectures such as U-Net, StarDist, and HoVer-Net have set strong baselines, th...
Based on the vertical cyclic model test of the cement-fly ash mixing pile (CFMP) composite foundation, the effects of different dynamic load ratios on the long-term bearing characteristics of the composite foundation were studied. From the perspectiv...
Few studies have been published on the dynamic centrifuge model test of cohesive soil under earthquake action. The seismic response of cohesive soil foundation and tunnel was studied by the centrifuge experiment and numerical modelling. Through a com...
In response to the urgent need for rapid and precise post-disaster damage evaluation, this study introduces the Visual Prompt Damage Evaluation (ViPDE) framework, a novel contrastive learning-based approach that leverages the embedded knowledge withi...
Combinatorial Route Optimization (CRO) problems, such as the Vehicle Routing Problem (VRP) or the Travelling Salesman Problem (TSP), are commonly seen in scheduling, logistics, and transportation. While current machine learning (ML) methods can overc...
Diabetes mellitus is a chronic condition that frequently leads to severe complications that are difficult to detect in their early stages using conventional clinical monitoring. This paper presents a data-driven framework for predicting multiple diab...
Large language models (LLMs) and time-series foundation models have advanced traffic forecasting, but almost exclusively on freeway sensors at five-minute, aggregate-flow resolution; their behavior on minute-resolution, movement-level counts at signa...
This paper assesses the contributions of induced tensile stress in the behavior of foundations in order to make a case that tensile stress induced by foundation loading needs to be considered in geotechnical analysis for foundations that apply high l...
This study explores the swelling behavior of strong expansive soil from the Nanyang Section II canal bed of the South-to-North Water Diversion Middle Route Project, with practical relevance to foundation engineering. A total of 45 one-dimensional swe...
Geospatial foundation models (GeoFMs) offer broad generalisation across Earth observation (EO) tasks, particularly under data-limited conditions. However, their large model size and computational requirements remain major barriers to deployment on re...
This paper considers the impact of foundation geometry on the vibrations transferred to a building in the vicinity of a railway line from the aspect of choosing an appropriate foundation type. For this purpose, a 1-g scale physical model is developed...
The physical and mechanical properties of red clay have a significant influence on the bearing characteristics of pile foundations. Therefore, this paper conducted model tests to study the influence of different red clay water content (16~−20%)...
Pile–bucket foundation is a newly developed offshore wind turbine supporting structure created by combining a monopile and a bucket foundation. Current research mainly focuses on its bearing characteristics in homogeneous soil layers (e.g., pur...
To calculate the horizontal displacement of the diaphragm wall and surface settlement caused by foundation pit excavation, the three-parameter Kerr foundation model was applied to a diaphragm wall and derived the flexural differential equations of th...
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