Results 51 to 60 of about 449,358 (260)
Advanced Functional Materials, EarlyView.Automat optical inspection (AOI) techniques in semiconductor fabrication can be leveraged in battery manufacturing, enabling scalable detection and analysis of electrode‐ and cell‐level imperfections through AI‐driven analytics and a digital‐twin framework.
Jianyu Li, Ertao Hu, Wei Wei, Feifei Shi
wiley +1 more source
Geometric Deep Learning for Protein–Protein Interaction Predictions
IEEE Access, 2022 This work introduces novel approaches, based on geometrical deep learning, for predicting protein–protein interactions. A dataset containing both interacting and non-interacting proteins is selected from the Negatome Database.
Gabriel St-Pierre Lemieux +3 more
doaj +1 more source
Video Description using Bidirectional Recurrent Neural Networks
, 2016 Although traditionally used in the machine translation field, the encoder-decoder framework has been recently applied for the generation of video and image descriptions.
Bolaños, Marc +3 more
core +1 more source
Amyloidogenic Peptide Fragments Designed From Bacterial Collagen‐like Proteins Form Hydrogel
Advanced Functional Materials, EarlyView.This study identified amyloidogenic sequence motifs in bacterial collagen‐like proteins and exploited these to design peptides that self‐assemble into β‐sheet fibers and form hydrogels. One hydrogel supported healthy fibroblast growth, showing promise for biocompatible materials. Our work demonstrates that bacterial sequences can be harnessed to create
Vamika Sagar +5 more
wiley +1 more source
Spike buffer: improve deep network performance by offset mechanism
The Journal of Engineering, 2020 For a well-designed neural network model, it is difficult to further improve its performance. This study proposes an offset mechanism called spike buffer, which can effectively improve the performance of the designed convolutional neural networks.
Daihui Li, Shangyou Zeng, Chengxu Ma
doaj +1 more source
Analysis and training of a traffic sign recognition neural network model
Вестник Дагестанского государственного технического университета: Технические науки, 2023 Objective. The purpose of the research is to develop and train a neural network model based on convolutional neural networks for effective recognition of road signs in images.Method.
A. U. Mentsiev +2 more
doaj +1 more source
Multi‐Scale Interface Engineering of MXenes for Multifunctional Sensory Systems
Advanced Functional Materials, EarlyView.MXenes, as two‐dimensional transition metal carbides and nitrides, demonstrate remarkable capabilities for multifunctional sensing applications. This review systematically examines multi‐scale interface engineering approaches that enhance sensing performance, enable diverse detection functionalities, and improve system‐level compatibility in MXene ...
Jiaying Liao, Sin‐Yi Pang, Jianhua Hao
wiley +1 more source
Branching quantum convolutional neural networks
Physical Review Research, 2022 Neural-network-based algorithms have garnered considerable attention for their ability to learn complex patterns from very-high-dimensional data sets towards classifying complex long-range patterns of entanglement and correlations in many-body quantum ...
Ian MacCormack +4 more
doaj +1 more source
Computation, 2023 Convolutional neural networks (CNNs) are one of the main types of neural networks used for image recognition and classification. CNNs have several uses, some of which are object recognition, image processing, computer vision, and face recognition.
Mohammad Mustafa Taye
doaj +1 more source
Abnormal Event Detection in Videos using Spatiotemporal Autoencoder
, 2017 We present an efficient method for detecting anomalies in videos. Recent applications of convolutional neural networks have shown promises of convolutional layers for object detection and recognition, especially in images.
Chong, Yong Shean, Tay, Yong Haur
core +1 more source