Results 111 to 120 of about 6,849,681 (296)
A low-cost neural sorting network with O(1) time complexity [PDF]
, 2011 [[abstract]]In this paper, we present an O(1) time neural network with O(n1 + var epsilon) neurons and links to sort n data, var epsilon > 0. For large-size problems, it is desirable to have low-cost hardware solutions.
Lin, Shun-Shii;Hsu, Shen-Hsuan
core
Organic Materials of Tomorrow: Horizons of Artificial Intelligence
Advanced Materials, EarlyView.This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena +3 more
wiley +1 more source
Deep Learning-Based Approaches for Brain Tumour Segmentation and Classification
European Medical JournalBrain tumours are caused by the abnormal growth of cells in the brain. This occurs mainly due to genetic changes or exposure to X-ray radiation. When the tumours are detected early, they can be removed via surgery.
Vidya Baiju +2 more
doaj +1 more source
On the Universal Approximation Property of Deep Fully Convolutional Neural Networks
SIAM Journal on Mathematical AnalysisWe study the approximation of shift-invariant or equivariant functions by deep fully convolutional networks from the dynamical systems perspective. We prove that deep residual fully convolutional networks and their continuous-layer counterpart can achieve universal approximation of these symmetric functions at constant channel width.
Qianxiao Li, Ting Lin, Zuowei Shen
openaire +3 more sources
Application of wavelets and artificial neural network for indoor optical wireless communication systems [PDF]
This study investigates the use of error control code, discrete wavelet transform (DWT) and artificial neural network (ANN) to improve the link performance of an indoor optical wireless communication in a physical channel.
Rajbhandari, Sujan
core
Look-behind fully convolutional neural network for computer-aided endoscopy
, 2019 In this paper, we propose a novel Fully Convolutional Neural Network (FCN) architecture aiming to aid the detection of abnormalities, such as polyps, ulcers and blood, in gastrointestinal (GI) endoscopy images.
Diamantis D.E., Iakovidis D.K., Koulaouzidis A.
core +1 more source
Data‐Driven Materials Science for Energy‐Sustainable Applications
Advanced Materials, EarlyView.Data‐driven approaches powered by artificial intelligence are transforming materials discovery for energy sustainability. This review examines how auto‐generated high‐quality materials databases and domain‐specific language models accelerate research in photovoltaics, thermoelectrics, batteries and magnetic materials. Applications involve extraction of
Jacqueline M. Cole
wiley +1 more source
DermoNet: densely linked convolutional neural network for efficient skin lesion segmentation
EURASIP Journal on Image and Video Processing, 2019 Recent state-of-the-art methods for skin lesion segmentation are based on convolutional neural networks (CNNs). Even though these CNN-based segmentation approaches are accurate, they are computationally expensive.
Saleh Baghersalimi +4 more
doaj +1 more source
Advanced Materials, EarlyView.Memristors offer tunable resistance and intrinsic instability, making them promising tunable noise sources. We propose a spiking‐rate‐programmable probabilistic neuron using a Ru/TaOx/Pt memristor, where resistance‐dependent noise enables frequency‐selective encoding.
Do Hoon Kim +8 more
wiley +1 more source
Dog recognition in public places based on convolutional neural network
International Journal of Distributed Sensor Networks, 2019 With the increase in the number of dogs in the city, the dogs can be seen everywhere in public places. At the same time, more and more stray dogs appear in public places where dogs are prohibited, which has a certain impact on the city environment and ...
Jianquan Ouyang +3 more
doaj +1 more source