Results 1 to 10 of about 510,572 (297)

Offline Identification of the Author using Heterogeneous Data based on Deep Learning [PDF]

هوش محاسباتی در مهندسی برق, 2022
Handwriting recognition has always been a challenge; therefore, it has attracted the attention of many researchers. The present study presents an offline system for the automatic detection of human handwriting under different experimental conditions ...
Seyed Nadi Mohamed Khosroshahi, Seyed Naser Razavi, Amin Babazadeh Sangar, Kambiz Majidzadeh   +3 more
doaj   +1 more source

Inverse Feature Learning: Feature Learning Based on Representation Learning of Error [PDF]

IEEE Access, 2020
This paper proposes inverse feature learning as a novel supervised feature learning technique that learns a set of high-level features for classification based on an error representation approach. The key contribution of this method is to learn the representation of error as high-level features, while current representation learning methods interpret ...
Behzad Ghazanfari, Fatemeh Afghah, Mohammadtaghi Hajiaghayi   +2 more
openaire   +4 more sources

Improving Domain Generalization in Appearance-Based Gaze Estimation With Consistency Regularization

IEEE Access, 2023
Gaze estimation, a method for understanding human behavior by analyzing where a person is looking, has significant applications in various fields including advertising, driving assistance, medical diagnostics, and human-computer interaction.
Moon-Ki Back, Cheol-Hwan Yoo, Jang-Hee Yoo   +2 more
doaj   +1 more source

Spatial-Aware Network for Hyperspectral Image Classification

Remote Sensing, 2021
Deep learning is now receiving widespread attention in hyperspectral image (HSI) classification. However, due to the imbalance between a huge number of weights and limited training samples, many problems and difficulties have arisen from the use of deep ...
Yantao Wei, Yicong Zhou
doaj   +1 more source

Discriminative feature learning through feature distance loss

Machine Vision and Applications, 2023
AbstractEnsembles of convolutional neural networks have shown remarkable results in learning discriminative semantic features for image classification tasks. However, the models in the ensemble often concentrate on similar regions in images. This work proposes a novel method that forces a set of base models to learn different features for a ...
Tobias Schlagenhauf, Yiwen Lin, Benjamin Noack   +2 more
openaire   +4 more sources

LT-FS-ID: Log-Transformed Feature Learning and Feature-Scaling-Based Machine Learning Algorithms to Predict the k-Barriers for Intrusion Detection Using Wireless Sensor Network

Sensors, 2022
The dramatic increase in the computational facilities integrated with the explainable machine learning algorithms allows us to do fast intrusion detection and prevention at border areas using Wireless Sensor Networks (WSNs).
Abhilash Singh, J. Amutha, Jaiprakash Nagar, Sandeep Sharma, Cheng-Chi Lee   +4 more
doaj   +1 more source

Feature space learning model [PDF]

Journal of Ambient Intelligence and Humanized Computing, 2018
With the massive volume and rapid increasing of data, feature space study is of great importance. To avoid the complex training processes in deep learning models which project original feature space into low-dimensional ones, we propose a novel feature space learning (FSL) model.
Guan, Renchu, Wang, Xu, Marchese, Maurizio, Yang, Mary Qu, Liang, Yanchun, Yang, Chen   +5 more
openaire   +2 more sources

Linear Discriminant Analysis via Pseudo Labels: A Unified Framework for Visual Domain Adaptation

IEEE Access, 2020
This paper deals with the problem of visual domain adaptation in which source domain labeled data is available for training, but the target domain unlabeled data is available for testing.
Rakesh Kumar Sanodiya, Leehter Yao
doaj   +1 more source

An Efficient Convolutional Neural Network with Supervised Contrastive Learning for Multi-Target DOA Estimation in Low SNR

Axioms, 2023
In this paper, a modified high-efficiency Convolutional Neural Network (CNN) with a novel Supervised Contrastive Learning (SCL) approach is introduced to estimate direction-of-arrival (DOA) of multiple targets in low signal-to-noise ratio (SNR) regimes ...
Yingchun Li, Zhengjie Zhou, Cheng Chen, Peng Wu, Zhiquan Zhou   +4 more
doaj   +1 more source

Learning With Feature Evolvable Streams [PDF]

IEEE Transactions on Knowledge and Data Engineering, 2021
Learning with streaming data has attracted much attention during the past few years. Though most studies consider data stream with fixed features, in real practice the features may be evolvable. For example, features of data gathered by limited-lifespan sensors will change when these sensors are substituted by new ones.
Bo-Jian Hou, Lijun Zhang, Zhi-Hua Zhou
openaire   +2 more sources