Results 161 to 170 of about 226,428 (269)

LLM‐Based Scientific Assistants for Knowledge Extraction: Which Design Choices Matter?

Advanced Intelligent Discovery, EarlyView.
A comprehensive framework for optimizing Large Language Models in domain‐specific applications is introduced. The LLM Playground integrates Prompt Engineering, knowledge augmentation, and advanced reasoning strategies to enable systematic comparison of architectures and base models.
David Exler, Manuel Raimann, Marc Münker, Maxim Rosin, Joaquin E. Urrutia Gómez, Christof M. Niemeyer, Markus Reischl, Luca Rettenberger   +7 more
wiley   +1 more source

SRDFNet: Semantic Refinement and Differential Features for High-Resolution Change Detection. [PDF]

Sensors (Basel)
Zhao W, Lu D, Zhao Y, Chen K.
europepmc   +1 more source

Harnessing Digital Microstructure for Simulation‐Guided Optimization of Permanent Magnets

Advanced Intelligent Discovery, EarlyView.
An experimental‐to‐computational workflow is presented that transforms experimental 3D focused ion beam‐scanning electron microscopy data into a simulation‐ready digital microstructure for multiphase functional materials. Using heavy‐rare‐earth‐free Nd–Fe–B magnets as a model system, the approach quantifies grain connectivity across complex secondary ...
Nikita Kulesh, Anton Bolyachkin, Hajime Nakamura, Tadakatsu Ohkubo, Hossein Sepehri‐Amin   +4 more
wiley   +1 more source

Cross-domain zero-shot semantic segmentation for unstructured environments via EVA-CLIP model, ensemble prompt engineering, and optimized text-image matching. [PDF]

PLoS One
Zhou N, Zhao X, Zhou F, Li J, Yue X.
europepmc   +1 more source

Cell Segmentation Beyond 2D—A Review of the State‐of‐the‐Art

Advanced Intelligent Discovery, EarlyView.
Cell segmentation underpins many biological image analysis tasks, yet most deep learning methods remain limited to 2D despite the inherently 3D nature of cellular processes. This review surveys segmentation approaches beyond 2D, comparing 2.5D and fully 3D methods, analyzing 31 models and 32 volumetric datasets, and introducing a unified reference ...
Fabian Schmeisser, Haseeb Muhammad, Junaid Younas, Gillian Lovell, Bianca Migliori, Andreas Dengel, Sheraz Ahmed   +6 more
wiley   +1 more source

An integrative NLP framework identifies multilevel linguistic phenotypes of schizophrenia across tasks. [PDF]

Psychol Med
Nakamura H, Kano Y, Sugihara G, Takemura R, Yamaguchi Y, Shimizu M, Takagi S, Iizuka M, Tashiro S, Kitazawa M, Sento A, Takahashi H, Taishiro K.   +12 more
europepmc   +1 more source

Artificial Intelligence (AI) and Agribusiness: From Automation to Augmentation in a Global Context

Agribusiness, EarlyView.
Alexis H. Villacis
wiley   +1 more source

AI Powered Biobanks From Static Archives to Dynamic Discovery Engines

Advanced Intelligent Discovery, EarlyView.
Large language models (LLMs) provide a potential framework for transforming biobanks from static data repositories into intelligent discovery engines. By enabling unified representation and analysis of multimodal biomedical data, LLM‐based systems facilitate dynamic risk prediction, biomarker identification, and mechanistic interpretation, thereby ...
Wenzhen Yin, Yutian Feng, Wenrui Ma, Yuxin Su, Li Min, Juan Liu   +5 more
wiley   +1 more source

YOLIP: An Enhanced Framework for UAV-Assisted Wildlife Monitoring Based on YOLO Integrated with the CLIP Model. [PDF]

Sensors (Basel)
Hu R, Chen Y, Xu K, Zhang L, Yue C, Pi H, Chen X, Lin X.   +7 more
europepmc   +1 more source

Composition‐Aware Cross‐Sectional Integration for Spatial Transcriptomics

Advanced Intelligent Discovery, EarlyView.
Multi‐section spatial transcriptomics demands coherent cell‐type deconvolution, domain detection, and batch correction, yet existing pipelines treat these tasks separately. FUSION unifies them within a composition‐aware latent framework, modeling reads as cell‐type–specific topics and clustering in embedding space.
Qishi Dong, Zijian Huang, Xuanwu Wang, Zhenghui Feng, Wei Liu, Bingding Huang   +5 more
wiley   +1 more source