Results 161 to 170 of about 102,675 (264)

A rapid approach for discriminating <i>Ganoderma</i> species using attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy integrated with chemometric analysis and convolutional neural network (CNN). [PDF]

Front Chem
Chen SY, Low CY, Loh JY, Tew WY, Ouyang LY, Ong PS, Yan CS, Loh HW, Chen Y, Xu W, Xu W, Yoon TL, Yam MF.   +12 more
europepmc   +1 more source

Linear and Programmable Long‐Term Plasticity in PECVD Amorphous SiC Memristors

Advanced Electronic Materials, EarlyView.
Stoichiometry‐engineered PECVD amorphous SiC memristors exhibit highly linear and programmable long‐term synaptic plasticity with a nonlinearity as low as 0.08. By controlling the local bonding environment, stable multilevel conductance updates are achieved, enabling robust neural‐network classification on MNIST and CIFAR‐10 and highlighting amorphous ...
Qin Liu, Omesh Kapur, Bohao Ding, Fangnan Chen, Bingkai Ding, Ruomeng Huang, C. H. Kees de Groot   +6 more
wiley   +1 more source

Convolutional neural network (CNN) configuration using a learning automaton model for neonatal brain image segmentation. [PDF]

PLoS One
Sarafraz I, Agahi H, Mahmoodzadeh A.
europepmc   +1 more source

X‐Ray TID Suppresses Inhibitory Plasticity of SnO‐Based Memristors and Its Impact on Neuromorphic Computation

Advanced Electronic Materials, EarlyView.
X‐ray irradiation suppresses inhibitory plasticity in SnO‐based volatile memristors, reducing nonlinearity and variability while improving neuromorphic learning accuracy. Despite a reduced dynamic range, irradiated devices achieve more stable and linear synaptic updates, leading to enhanced CNN performance.
Aiden Graham, Zohreh Hajiabadi, Alexander H. Wang, Asep Nugroho, Om K. Prasad, Uma Sankar Rout, Christian Patzig, Irwan Purnama, Liam Godfrey, Marcello Borri, Bingkai Ding, Harold M. H. Chong, Firman M. Simanjuntak   +12 more
wiley   +1 more source

TC-CNN: Trajectory Compression based on Convolutional Neural Network

Proceedings of the 2nd International Conference on Deep Learning Theory and Applications, 2021
Yulong Wang, Jingwang Tang, Zhe Jia
openaire   +1 more source

Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories

Advanced Energy Materials, EarlyView.
In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen, Zheyu Zhang, Kelvian T. Mularso, Bonghyun Jo, Hyun Suk Jung   +4 more
wiley   +1 more source

Self-Trained Convolutional Neural Network (CNN) for Tuberculosis Diagnosis in Medical Imaging. [PDF]

Cureus
Sarawagi K, Pagrotra A, Dhiman H, Singh N.   +3 more
europepmc   +1 more source

Combining Multi-Dimensional Convolutional Neural Network (CNN) With Visualization Method for Detection of Aphis gossypii Glover Infection in Cotton Leaves Using Hyperspectral Imaging. [PDF]

Front Plant Sci, 2021
Yan T, Xu W, Lin J, Duan L, Gao P, Zhang C, Lv X.   +6 more
europepmc   +1 more source

Artificial Intelligence–Based Surgical Phase Analysis Enables Objective Assessment of Surgeon Skill in Robotic Distal Gastrectomy: A Multicenter Study

Annals of Gastroenterological Surgery, EarlyView.
ABSTRACT Aim Artificial intelligence (AI)–based surgical video analysis can automate time‐consuming manual assessments and enable objective characterization of surgical workflows. We aimed to construct a large, multicenter, fully annotated dataset of robotic distal gastrectomy (RDG) videos and evaluate the feasibility and performance of an AI model for
Masaru Komatsu, Daichi Kitaguchi, Yoichi Ninomiya, Yuya Takabe, Mitsumasa Yoshida, Masahiro Yura, Nobuyoshi Takeshita, Takahiro Kinoshita, Masaaki Ito   +8 more
wiley   +1 more source

A lightweight convolutional neural network (CNN) model for diatom classification: DiatomNet. [PDF]

PeerJ Comput Sci
Gunduz H, Gunal S.
europepmc   +1 more source