Results 181 to 190 of about 86,867 (310)

Uncertainty‐Guided Selective Adaptation Enables Cross‐Platform Predictive Fluorescence Microscopy

open access: yesAdvanced Intelligent Discovery, EarlyView.
Deep learning models often fail when transferred to new microscopes. A novel framework overcomes this by selectively adapting the early layers governing low‐level image statistics, while freezing deep layers that encode morphology. This uncertainty‐guided approach enables robust, label‐free virtual staining across diverse systems, democratizing ...
Kai‐Wen K. Yang   +9 more
wiley   +1 more source

Design, Control, and Clinical Applications of Magnetic Actuation Systems: Challenges and Opportunities

open access: yesAdvanced Intelligent Systems, Volume 7, Issue 3, March 2025.
This review aims to provide a broad understanding for interdisciplinary researchers in engineering and clinical applications. It addresses the development and control of magnetic actuation systems (MASs) in clinical surgeries and their revolutionary effects in multiple clinical applications.
Yingxin Huo   +3 more
wiley   +1 more source

Retinal Vessel Segmentation: A Comprehensive Review From Classical Methods to Deep Learning Advances (1982–2025)

open access: yesAdvanced Intelligent Systems, EarlyView.
Four decades of retinal vessel segmentation research (1982–2025) are synthesized, spanning classical image processing, machine learning, and deep learning paradigms. A meta‐analysis of 428 studies establishes a unified taxonomy and highlights performance trends, generalization capabilities, and clinical relevance.
Avinash Bansal   +6 more
wiley   +1 more source

Design‐for‐Benchmarking in Soft Robotics: Navigating Component‐System Dichotomy

open access: yesAdvanced Intelligent Systems, EarlyView.
Soft robotics faces a profound evaluation challenge: the Component‐System Dichotomy, where isolated component tests fail to predict integrated performance. This article presents a systematic survey of critical reporting gaps across actuation, sensing, and control.
Matteo Lo Preti   +4 more
wiley   +1 more source

Interpreting How Neural Networks Infer Scatterer Geometry from Echolocation Echoes

open access: yesAdvanced Intelligent Systems, EarlyView.
Neural networks enable echolocation‐based shape classification but remain difficult to interpret due to their black‐box nature. This work presents a feature‐importance metric to uncover the echo regions driving decisions in shape‐specialized networks.
Ganesh U. Patil   +2 more
wiley   +1 more source

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