Results 151 to 160 of about 665,919 (292)

Deep Learning‐Assisted Design of Mechanical Metamaterials

open access: yesAdvanced Intelligent Discovery, EarlyView.
This review examines the role of data‐driven deep learning methodologies in advancing mechanical metamaterial design, focusing on the specific methodologies, applications, challenges, and outlooks of this field. Mechanical metamaterials (MMs), characterized by their extraordinary mechanical behaviors derived from architected microstructures, have ...
Zisheng Zong   +5 more
wiley   +1 more source

Computer Vision Pipeline for Image Analysis for Freeze‐Fracture Electron Microscopy: Rosette Cellulose Synthase Complexes Case

open access: yesAdvanced Intelligent Discovery, EarlyView.
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

Toward Capacitive In‐Memory‐Computing: A Device to Systems Level Perspective on the Future of Artificial Intelligence Hardware

open access: yesAdvanced Intelligent Discovery, EarlyView.
Capacitive, charge‐domain compute‐in‐memory (CIM) stores weights as capacitance,eliminating DC sneak paths and IR‐drop, yielding near‐zero standbypower. In this perspective, we present a device to systems level performance analysis of most promising architectures and predict apathway for upscaling capacitive CIM for sustainable edge computing ...
Kapil Bhardwaj   +2 more
wiley   +1 more source

A Flexible and Energy‐Efficient Compute‐in‐Memory Accelerator for Kolmogorov–Arnold Networks

open access: yesAdvanced Intelligent Systems, EarlyView.
This article presents KA‐CIM, a compute‐in‐memory accelerator for Kolmogorov–Arnold Networks (KANs). It enables flexible and efficient computation of arbitrary nonlinear functions through cross‐layer co‐optimization from algorithm to device. KA‐CIM surpasses CPU, ASIC, VMM‐CIM, and prior KAN accelerators by 1–3 orders of magnitude in energy‐delay ...
Chirag Sudarshan   +6 more
wiley   +1 more source

Worm‐Inspired Soft Robots With Modular Outfit‐Changing for Intelligent Multienvironment Adaptation

open access: yesAdvanced Intelligent Systems, EarlyView.
This study proposes a worm‐inspired soft robot capable of locomotion across multiple environments through a modular “outfit‐changing” strategy. The robot integrates pneumatically actuated peristaltic segments with interchangeable external modules, enabling efficient motion on ground surfaces, within pipelines, through granular media, and underwater ...
Xiaomin Liu   +6 more
wiley   +1 more source

Methods for Setting Device Specifications for Analog In‐Memory Computing Inference

open access: yesAdvanced Intelligent Systems, EarlyView.
Non‐volatile memories (NVMs) are being developed for analog in‐memory computing for energy‐efficient, high‐speed deep learning inference. As technology is moving to industry adoption, a method to define required NVM specifications is critical for improving performance and reducing manufacturing cost.
Zhenyu Wu   +3 more
wiley   +1 more source

Evaluation of Mechanical Properties of Phase‐Separated Cellulose Filler/Poly(Lactic Acid)/Elastomer Composites via Microstructure‐Informed Physics Simulation and In Situ Synchrotron X‐Ray Micro‐CT

open access: yesJournal of Applied Polymer Science, EarlyView.
Phase‐separation microstructure and mechanical properties of a ternary biocomposite evaluated by integrated AFM, AFM‐informed FEM, and in situ X‐ray CT. ABSTRACT This study investigates phase‐separated cellulose filler/poly(lactic acid) (PLA)/elastomer ternary composites to enhance the mechanical performance of bioplastics. Atomic force microscopy (AFM)
Yoshiaki Kawagoe   +8 more
wiley   +1 more source

Prospecting of Architectural Features Using LiDAR‐UAV Technology, Deep Neural Networks and Visualization Techniques: A Case Study in Kuélap and Cambolín (NW Peru)

open access: yesArchaeological Prospection, EarlyView.
ABSTRACT High‐resolution and accurate synoptic images of terrestrial topography, even in densely forested areas, have proven valuable for archaeology by enabling the identification and characterization of relief patterns associated with ancient human activities. This study presents a novel approach that integrates digital terrain models (DTMs) obtained
Jhon A. Zabaleta‐Santisteban   +13 more
wiley   +1 more source

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