Results 161 to 170 of about 5,636 (303)
Full-Gradient Representation for Neural Network Visualization
We introduce a new tool for interpreting neural net responses, namely full-gradients, which decomposes the neural net response into input sensitivity and per-neuron sensitivity components. This is the first proposed representation which satisfies two key
Fleuret, Francois, Srinivas, Suraj
core
Video Enhancement Using Convolutional Networks
, 2017 Convolutional neural networks (CNN) represent a state-of-the-art approach to non-trivial image processing tasks, including compression artifacts reduction and image super-resolution.
Skácel, David
core
Advances and Perspectives in Graphene‐Based Quantum Dots Enabled Neuromorphic Devices
Advanced Science, EarlyView.Graphene‐based QDs are zero‐dimensional carbon nanomaterials with pronounced quantum confinement and tunable electronic structures. Herein, we summarize their synthesis strategies and functionalization methods, and highlight their functional roles and operating mechanisms in devices, as well as recent advances in neuromorphic electronics. We anticipate
Yulin Zhen +9 more
wiley +1 more source
Super Sparse Convolutional Neural Networks
, 2019 To construct small mobile networks without performance loss and address the over-fitting issues caused by the less abundant training datasets, this paper proposes a novel super sparse convolutional (SSC) kernel, and its corresponding network is called ...
Lu, Guangming +4 more
core +1 more source
Synaptic κ‐Ga2O3 Photodetectors for Privacy‐Enhancing Neuromorphic Computing
Advanced Science, EarlyView.We report on a single‐element neuromorphic sensor based on the persistent photoconductivity (PPC) of κ‐phase Ga2O3 capable of sensing ultraviolet light and harnessing intrinsic data privacy. The approach establishes a materials‐enabled pathway toward compact, intelligent, and privacy‐enhancing optoelectronic hardware for next‐generation edge systems ...
Yanqing Jia +13 more
wiley +1 more source
A Study on the Use of Convolutional Networks for RF Coverage Evaluations in Urban Environments
U-nets are a type of Fully Convolutional Neural Network that has been widely adopted for image segmentation applications. In the present study, U-nets are applied to wide area prediction of radio propagation parameters in urban environment. Coverage maps
Duka K., Vitucci E. M., Di Cicco N.
core +1 more source
Labeling Transformation and Introspective Learning with Convolutional Nets [PDF]
, 2018 Convolutional neural networks have been widely used in machine learning and computer vision tasks for either discriminative purposes or generative modeling.
Jin, Long
core
Shadow‐Calibrated Stereo Vision for Colorimetric Sweat Analysis
Advanced Science, EarlyView.By establishing a mathematical model that reconstructs 3D structures through geometric features of object shadows under controlled illumination, and combining it with Convolutional Neural Network‐based 2D image analysis for volumetric calibration, this work enables highly accurate 3D morphological reconstruction.
Ting Xiao +7 more
wiley +1 more source
A Correlative SICM‐OPM Platform for Surface and Volumetric Imaging in Live Cells
Advanced Science, EarlyView.A multifunctional correlative imaging platform integrating Scanning Ion Conductance Microscopy (SICM) with Oblique Plane Microscopy (OPM) enables simultaneous surface topography, mechanical mapping, and 3D volumetric fluorescence imaging in live cells.
Wenzhi Hong +13 more
wiley +1 more source
Advanced Science, EarlyView.We present an organic–inorganic heterostructure transistor array for neuromorphic computing, achieving 95.6% MNIST accuracy and 1.2 fJ per operation, with dynamic spatiotemporal encoding and precise vehicle direction detection under combined optical and electrical stimulation.
Wen‐Min Zhong +13 more
wiley +1 more source