Artificial Intelligence (AI) and Agribusiness: From Automation to Augmentation in a Global Context
Agribusiness, EarlyView.
Alexis H. Villacis
wiley +1 more source
This paper presents a computer vision (deep learning) pipeline integrating YOLOv8 and YOLOv9 for automated detection, segmentation, and analysis of rosette cellulose synthase complexes in freeze‐fracture electron microscopy images. The study explores curated dataset expansion for model improvement and highlights pipeline accuracy, speed ...
Siri Mudunuri +6 more
wiley +1 more source
Discrepancy-Guided Semantic Segmentation with Boundary Detail Enhancement for Traffic Scenes. [PDF]
Yu C, Yang X, Shen S.
europepmc +1 more source
Automating AI Discovery for Biomedicine Through Knowledge Graphs and Large Language Models Agents
This work proposes a novel framework that automates biomedical discovery by integrating knowledge graphs with multiagent large language models. A biologically aligned graph exploration strategy identifies hidden pathways between biomedical entities, and specialized agents use this pathway to iteratively design AI predictors and wet‐lab validation ...
Naafey Aamer +3 more
wiley +1 more source
Comparative performance analysis of U-Net and DeepLabV3+ for semantic segmentation in traffic environments. [PDF]
Ramyashree +4 more
europepmc +1 more source
Harnessing Digital Microstructure for Simulation‐Guided Optimization of Permanent Magnets
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 +4 more
wiley +1 more source
Vision-Based Topology-Consistent Structural Parsing of Hand-Drawn Circuit Diagrams. [PDF]
Wang H, Wu Y, Liu X, Li W.
europepmc +1 more source
Cell Segmentation Beyond 2D—A Review of the State‐of‐the‐Art
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 +6 more
wiley +1 more source
A Multi-Module Fusion Framework for Restoring Human and Machine Vision Quality in Compressed Video. [PDF]
He K, Xiang K, Gao Y, Yu Y, Zhou J.
europepmc +1 more source
AI Powered Biobanks From Static Archives to Dynamic Discovery Engines
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 +5 more
wiley +1 more source

