Results 31 to 40 of about 204,781 (309)
FocusedDropout for Convolutional Neural Network
CoRR, 2021 In convolutional neural network (CNN), dropout cannot work well because dropped information is not entirely obscured in convolutional layers where features are correlated spatially. Except randomly discarding regions or channels, many approaches try to overcome this defect by dropping influential units.
Tianshu Xie +5 more
openaire +2 more sources
Sensors, 2019 This paper proposes a new method of mixed gas identification based on a convolutional neural network for time series classification. In view of the superiority of convolutional neural networks in the field of computer vision, we applied the concept to ...
Lu Han +3 more
doaj +1 more source
A Hybrid Framework for Visual Positioning: Combining Convolutional Neural Networks with Ontologies
EAI Endorsed Transactions on Energy Web, 2022 Visual positioning is a new generation positioning technique which has been developed rapidly during recent years for many applications such as robotics, self-driving vehicles and positioning for visually impaired people due to advent of powerful image
Abdolreza Mosaddegh +4 more
doaj +1 more source
Interpretable Convolutional Neural Networks [PDF]
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018 This paper proposes a method to modify traditional convolutional neural networks (CNNs) into interpretable CNNs, in order to clarify knowledge representations in high conv-layers of CNNs. In an interpretable CNN, each filter in a high conv-layer represents a certain object part.
Quanshi Zhang +2 more
openaire +2 more sources
An exact mapping from ReLU networks to spiking neural networks [PDF]
, 2023 Deep spiking neural networks (SNNs) offer the promise of low-power artificial intelligence. However, training deep SNNs from scratch or converting deep artificial neural networks to SNNs without loss of performance has been a challenge.
Wulfram Gerstner +11 more
core +1 more source
Forecast Model of TV Show Rating Based on Convolutional Neural Network
Complexity, 2021 The TV show rating analysis and prediction system can collect and transmit information more quickly and quickly upload the information to the database. The convolutional neural network is a multilayer neural network structure that simulates the operating
Lingfeng Wang
doaj +1 more source
Feature Extraction From Images Using Integrated Photonic Convolutional Kernel
IEEE Photonics Journal, 2022 Optical neural networks are expected to solve the problems of computational efficiency and energy consumption in neural networks. Herein, we experimentally implemented a 2 × 2 photonic convolutional kernel (PCK) using four on-chip micro-ring ...
Yulong Huang +6 more
doaj +1 more source
Empowering convolutional networks for malware classification and analysis [PDF]
, 2022 S.3838-3845Performing large-scale malware classification is increasingly becoming a critical step in malware analytics as the number and variety of malware samples is rapidly growing.
Eraisha, G. +4 more
core +1 more source
NeuroImage: Clinical, 2019 We hypothesized that expert epileptologists can detect seizures directly by visually analyzing EEG plot images, unlike automated methods that analyze spectro-temporal features or complex, non-stationary features of EEG signals.
Ali Emami +5 more
doaj +1 more source
Imaging from temporal data via spiking convolutional neural networks [PDF]
, 2020 A new approach for imaging that is solely based on the time of flight of photons coming from the entire imaged scene, combined with a novel machine learning algorithm for image reconstruction: a spiking convolutional neural network (SCNN) named Spike-SPI
Kapitany, Valentin +6 more
core +1 more source