Results 221 to 230 of about 2,605,876 (309)

Assessment of In Vitro Nano‐Cytotoxicity Through Fluorescence Microscopy via Neural Network‐Based Live/Dead Cell Classification

open access: yesAdvanced Intelligent Systems, EarlyView.
FluoAI is a two‐stage, label‐free method for quantifying nanomaterial‐induced cytotoxicity from conventional fluorescence microscopy images. Mask R‐CNN segmentation and DenseNet‐121 classification provide rapid live/dead classification matching human accuracy.
Ugur C. Topkiran   +6 more
wiley   +1 more source

Probing the content of semantic representations in body-selective regions. [PDF]

open access: yesImaging Neurosci (Camb)
Yashiro R   +3 more
europepmc   +1 more source

Artificial Intelligence for Advanced Functional Materials: Progress and Emerging Frontiers

open access: yesAdvanced Intelligent Systems, EarlyView.
Artificial intelligence is transforming the discovery of functional materials by linking synthesis, characterization, simulation, and design in unified workflows. Advances in machine learning, autonomous experimentation, and foundation models are accelerating innovation across energy, electronics, and biomedicine, while revealing new frontiers for ...
Cristiano Malica   +38 more
wiley   +1 more source

A Generalizable Framework for Building Executable Domain‐Specific Large Language Models Under Data Scarcity: Demonstration on Semiconductor Technology Computer‐Aided Design Simulation

open access: yesAdvanced Intelligent Systems, EarlyView.
A schema‐first alignment framework builds compact, executable domain‐specific language models under data scarcity. Large‐scale synthetic question‐answer generation instills domain knowledge, and a code‐centric IR‐to‐DPO pipeline aligns generation with tool‐executable syntax.
Di Wang   +4 more
wiley   +1 more source

EduFairBench: reproducible evaluation of large language models for educational assessment. [PDF]

open access: yesFront Artif Intell
Villegas-Ch W   +3 more
europepmc   +1 more source

Exploiting Edge Semantics in Job Shop Scheduling Problem With Heterogeneous Graph Transformers

open access: yesAdvanced Intelligent Systems, EarlyView.
A heterogeneous graph transformer (HGT) is introduced for reinforcement learning‐based job shop scheduling by explicitly distinguishing precedence and machine‐contention relations through edge‐type‐specific attention. The proposed framework learns richer scheduling representations, improves decision quality over homogeneous graph models, and highlights
Bulent Soykan, Fatih Kasimoglu
wiley   +1 more source

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