An artificial target detection method combining a polarimetric feature extractor with deep convolutional neural networks
Sign Up to like & getrecommendations! Published in 2020 at "International Journal of Remote Sensing"
DOI: 10.1080/01431161.2020.1727584
Abstract: ABSTRACT To improve the success rate of target detection, a fusion method that comprises a polarimetric feature extractor and a deep convolutional neural network (CNN) with consecutive small (2 × 2) convolutions (or, CSC-CNN for… read more here.
Keywords: detection; polarimetric feature; target detection; method ... See more keywords
Design and test performance of the ATLAS Feature Extractor trigger boards for the Phase-1 Upgrade
Sign Up to like & getrecommendations! Published in 2017 at "Journal of Instrumentation"
DOI: 10.1088/1748-0221/12/01/c01079
Abstract: In Run 3, the ATLAS Level-1 Calorimeter Trigger will be augmented by an Electron Feature Extractor (eFEX), to identify isolated e/γ and τ particles, and a Jet Feature Extractor (jFEX), to identify energetic jets and… read more here.
Keywords: feature extractor; feature; performance; trigger ... See more keywords
Residual-Based Graph Convolutional Network for Emotion Recognition in Conversation for Smart Internet of Things
Sign Up to like & getrecommendations! Published in 2021 at "Big data"
DOI: 10.1089/big.2020.0274
Abstract: Recently, emotion recognition in conversation (ERC) has become more crucial in the development of diverse internet of things devices, especially closely connected with users. The majority of deep learning-based methods for ERC combine the multilayer,… read more here.
Keywords: emotion recognition; network; feature; recognition conversation ... See more keywords
A Diagonally Oriented Novel Feature Extractor for Pedestrian Detection and Its Efficient Hardware Implementation
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Circuits and Systems for Video Technology"
DOI: 10.1109/tcsvt.2021.3079141
Abstract: Pedestrian detection is an important issue in an intelligent transportation system and involves complex hardware architecture. This high complexity and low detection accuracy make it a prompt topic of research. This paper proposes a novel… read more here.
Keywords: pedestrian detection; hardware; novel feature; feature extractor ... See more keywords
GCT: Graph Co-Training for Semi-Supervised Few-Shot Learning
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Circuits and Systems for Video Technology"
DOI: 10.1109/tcsvt.2022.3196550
Abstract: Few-shot learning (FSL), purposing to resolve the problem of data-scarce, has attracted considerable attention in recent years. A popular FSL framework contains two phases: (i) the pre-train phase employs the base data to train a… read more here.
Keywords: semi supervised; training; feature extractor; graph ... See more keywords
Can pre-trained convolutional neural networks be directly used as a feature extractor for video-based neonatal sleep and wake classification?
Sign Up to like & getrecommendations! Published in 2020 at "BMC Research Notes"
DOI: 10.1186/s13104-020-05343-4
Abstract: Objective In this paper, we propose to evaluate the use of pre-trained convolutional neural networks (CNNs) as a features extractor followed by the Principal Component Analysis (PCA) to find the best discriminant features to perform… read more here.
Keywords: sleep wake; video; classification; pre trained ... See more keywords