Results 121 to 130 of about 204,781 (309)

Extrusion Bioprinting for Wound Healing: Innovations in Functionalized Bioinks and Bioprinting Technology

Advanced Materials Technologies, EarlyView.
Extrusion‐based bioprinting (EBB) has emerged as a versatile biofabrication platform capable of precisely depositing bioinks composed of biomaterials, cells, and bioactive agents to generate patient‐specific, biomimetic skin constructs. This paper presents a state‐of‐the‐art and forward‐looking overview of EBB for wound healing, encompassing printing ...
Hien‐Phuong Le, Anh Tuan Trong Tran, Ammara Waheed, Tran Thanh Tung, Dusan Losic   +4 more
wiley   +1 more source

Wavelet Convolutional Neural Networks

CoRR, 2018
Spatial and spectral approaches are two major approaches for image processing tasks such as image classification and object recognition. Among many such algorithms, convolutional neural networks (CNNs) have recently achieved significant performance improvement in many challenging tasks. Since CNNs process images directly in the spatial domain, they are
Shin Fujieda, Kohei Takayama, Toshiya Hachisuka   +2 more
openaire   +2 more sources

In Situ Integrated Titanium Oxide Synaptic Phototransistor Enabling Multimodal Plasticity and Noise‐Robust Selective Attention

Advanced Materials Technologies, EarlyView.
An in situ integrated TiO2/SiOx/Al2O3 synaptic phototransistor couples ultraviolet and electrical stimuli within a scalable, CMOS‐compatible oxide stack. Multimodal plasticity, spike‐timing‐dependent learning, and bee‐inspired associative conditioning are achieved through trap‐mediated temporal dynamics.
Youngbin Yoon, Jaehee Lee, Jeongwook Kwon, Yongki Kim, Myunghun Shin, Jung Wook Lim   +5 more
wiley   +1 more source

Directional Latent Hybridization: Beyond Random Noise in Physics‐Informed Generative Inverse Design of Nonlinear Metamaterials

Advanced Materials Technologies, EarlyView.
A physics‐informed generative framework introduces Directional Latent Hybridization (DLH) for the deterministic inverse design of nonlinear metamaterials. By hybridizing dominant traits from parent geometries in the latent space, DLH overcomes the instabilities of stochastic models to ensure high structural precision at high densities.
Semin Ahn, Jun Young Choi, Sung‐Hoon Ahn   +2 more
wiley   +1 more source

A study of combination of autoencoders and boosted Big-Bang crunch theory architectures for Land-Use classification using remotely sensed imagery

Scientific Reports
The research introduced a new method for land-use classification by merging deep convolutional neural networks with a modified variant of a metaheuristic optimization technique.
Qiongbing Xiong, Xuecheng Wu, Cizhen Yu, Hasan Hosseinzadeh   +3 more
doaj   +1 more source

Quaternion Convolutional Neural Networks [PDF]

, 2018
Neural networks in the real domain have been studied for a long time and achieved promising results in many vision tasks for recent years. However, the extensions of the neural network models in other number fields and their potential applications are not fully-investigated yet. Focusing on color images, which can be naturally represented as quaternion
Xuanyu Zhu, Yi Xu 0001, Hongteng Xu, Changjian Chen   +3 more
openaire   +2 more sources

Musical Instrument Recognition in Polyphonic Audio Through Convolutional Neural Networks and Spectrograms [PDF]

This study investigates the task of identifying musical instruments in polyphonic compositions using Convolutional Neural Networks (CNNs) from spectrogram inputs, focusing on binary classification. The model showed promising results, with an accuracy of
Ghobakhlou, Ali, Rujia, Chen, Narayanan, Ajit   +2 more
core  

An AI‐Enabled All‐In‐One Visual, Proximity, and Tactile Perception Multimodal Sensor

Advanced Robotics Research, EarlyView.
Targeting integrated multimodal perception of robots, an AI‐enabled all‐in‐one multimodal sensor is proposed. This sensor is capable of perceiving three types of modalities, including vision, proximity, and tactility. By toggling an ultraviolet light and adjusting the camera focus, it switches smoothly between multiple perceptual modalities, enabling ...
Menghao Pu, Tiyong Zhao, Lingxi Zhang, Chaoqun Han, Zhiping Chai, Yifan Zhou, Han Ding, Zhigang Wu   +7 more
wiley   +1 more source

Hybrid multi-objective evolutionary model compression with convolutional neural networks

Results in Engineering
Deep learning has been utilized in the fields of image processing, natural language processing and speech recognition. For improving the structure of deep learning, how to compress Convolutional Neural Networks has become a major focus topic.
Shuhan Zhang, Yanjie Gao
doaj   +1 more source

Diffusion-Convolutional Neural Networks

, 2015
We present diffusion-convolutional neural networks (DCNNs), a new model for graph-structured data. Through the introduction of a diffusion-convolution operation, we show how diffusion-based representations can be learned from graph-structured data and used as an effective basis for node classification. DCNNs have several attractive qualities, including
James Atwood, Don Towsley
openaire   +3 more sources