Results 91 to 100 of about 86,091 (310)

Solid Harmonic Wavelet Bispectrum for Image Analysis

Advanced Science, EarlyView.
The Solid Harmonic Wavelet Bispectrum (SHWB), a rotation‐ and translation‐invariant descriptor that captures higher‐order (phase) correlations in signals, is introduced. Combining wavelet scattering, bispectral analysis, and group theory, SHWB achieves interpretable, data‐efficient representations and demonstrates competitive performance across texture,
Alex Brown, Mathilda Avirett‐Mackenzie, Carolin Villforth, Georgios Exarchakis   +3 more
wiley   +1 more source

Recent Advances in Laser‐Induced Graphene‐Based Gas Sensors: From Sensing Mechanisms to Biomedical Applications

Advanced Science, EarlyView.
Laser‐induced graphene (LIG) provides a scalable, laser‐direct‐written route to porous graphene architecture with tunable chemistry and defect density. Through heterojunction engineering, catalytic functionalization, and intrinsic self‐heating, LIG achieves highly sensitive and selective detection of NOX, NH3, H2, and humidity, supporting next ...
Md Abu Sayeed Biswas, Ankan Dutta, Shuvendu Das, Abu Musa Abdullah, Wanqing Zhang, Fatema Tuz Zohra, Huanyu Cheng   +6 more
wiley   +1 more source

Fine Tuning Hyperparameters of Deep Learning Models Using Metaheuristic Accelerated Particle Swarm Optimization Algorithm

IEEE Access
In recent years, Convolutional Neural Networks (CNNs) have emerged as powerful tools for solving complex real-world problems, particularly in the domain of image processing.
Abdel-Hamid M. Emara, Ghada Atteia, Jawad Hasan Alkhateeb   +2 more
doaj   +1 more source

Sparsity Invariant CNNs

2017 International Conference on 3D Vision (3DV), 2017
In this paper, we consider convolutional neural networks operating on sparse inputs with an application to depth upsampling from sparse laser scan data. First, we show that traditional convolutional networks perform poorly when applied to sparse data even when the location of missing data is provided to the network. To overcome this problem, we propose
Jonas Uhrig, Nick Schneider, Lukas Schneider, Uwe Franke, Thomas Brox, Andreas Geiger 0001   +5 more
openaire   +3 more sources

A Pollen‐Enhanced Bionic Mechanoreceptor Induced by Asymmetric Ionic Convection in Hydrogel for Sensory‐Augmented Prostheses

Advanced Science, EarlyView.
This work proposed a pollen‐enhanced bionic mechanoreceptor based on ionic convection. Leveraging the ion anchoring effect of the pollen particle, the output performance could be ∼12 times higher than the original state. By employing deep learning models as AI brains, the feasibility of a sensory‐augmented prosthesis consisting of a pollen‐enhanced ...
Zi Hao Guo, Jingyu Deng, Yanzhang Xu, Chenchen Zhou, Yangshi Shao, Xiong Pu, Munho Kim, Namjoon Cho   +7 more
wiley   +1 more source

Synthesis and modification strategies of g-C3N4 nanosheets for photocatalytic applications

Advanced Powder Materials
Graphitic carbon nitride nanosheets (CNNs) become the most promising member in the carbon nitride family benefitted from their two-dimensional structural features.
Long Chen, Michael A. Maigbay, Miao Li, Xiaoqing Qiu   +3 more
doaj   +1 more source

Atomic Defects in Layered Transition Metal Dichalcogenides for Sustainable Energy Storage and the Intelligent Trends in Data Analytics

Advanced Science, EarlyView.
This review comprehensively summarizes the atomic defects in TMDs for their applications in sustainable energy storage devices, along with the latest progress in ML methodologies for high‐throughput TEM data analysis, offering insights on how ML‐empowered microscopy facilitates bridging structure–property correlation and inspires knowledge for precise ...
Zheng Luo, Ying Yang, Zizhen Fu, Fengqi Liu, Susu Fang, Kele Xu, Shanshan Wang   +6 more
wiley   +1 more source

Physics‐Embedded Neural Network: A Novel Approach to Design Polymeric Materials

Advanced Science, EarlyView.
Traditional black‐box models for polymer mechanics rely solely on data and lack physical interpretability. This work presents a physics‐embedded neural network (PENN) that integrates constitutive equations into machine learning. The approach ensures reliable stress predictions, provides interpretable parameters, and enables performance‐driven, inverse ...
Siqi Zhan, Hengheng Zhao, Haotian Wang, Zhanjie Liu, Qian Li, Weifeng Zhang, Qingsong Zhao, Liqun Zhang, Jun Liu   +8 more
wiley   +1 more source

An Extensive Study of Convolutional Neural Networks: Applications in Computer Vision for Improved Robotics Perceptions

Sensors
Convolutional neural networks (CNNs), a type of artificial neural network (ANN) in the deep learning (DL) domain, have gained popularity in several computer vision applications and are attracting research in other fields, including robotic perception ...
Ravi Raj, Andrzej Kos
doaj   +1 more source

Location Augmentation for CNN

CoRR, 2018
CNNs have made a tremendous impact on the field of computer vision in the last several years. The main component of any CNN architecture is the convolution operation, which is translation invariant by design. However, location in itself can be an important cue.
Zhenyi Wang 0001, Olga Veksler
openaire   +2 more sources