Advanced search ?

Object

Shallow Layer Convolutional Features with Correlation Filters for UAV Object Tracking, Journal of Telecommunications and Information Technology, 2022, nr 2
Download

Title: Shallow Layer Convolutional Features with Correlation Filters for UAV Object Tracking, Journal of Telecommunications and Information Technology, 2022, nr 2

Creator:

Saputri, Desti Madya ; Prasetyo, Agus D. ; Wibowo, Suryo Adhi ; Syihabuddin, Budi

Date:

2022, nr 2

Resource Type:

artykuł

Description:

In this paper, convolutional shallow features are proposed for unmanned aerial vehicle (UAV) tracking. These convolutional shallow features are generated by pre-trained convolutional neural networks (CNN) and are used to represent the target objects. Furthermore, to estimate the location of the target objects, an adaptive correlation filter based on the Fourier transform is used. This filter is multiplied with the convolutional shallow features by using pixel-wise multiplication in the Fourier domain. Then, the inverse of Fourier is performed to estimate the location of the target object, where its location is represented by the maximum value of the response map. Unfortunately, the target object always changes its appearance during tracking. Therefore, we proposed an updated model to address this issue. The proposed method is evaluated by using the UAV123 10fps benchmark dataset. Based on the comprehensive experimental results, the proposed method performs favorably against state-of-the-art tracking algorithms

Publisher:

Instytut Łączności - Państwowy Instytut Badawczy

Format:

application/pdf

Resource Identifier:

ISSN 1509-4553, on-line: ISSN 1899-8852 ; oai:bc.itl.waw.pl:2226

Source:

Journal of Telecommunications and Information Technology

Language:

ang

Rights Management:

Biblioteka Naukowa Instytutu Łączności

Subject and keywords:

CNN object tracking shallow layer UAV tracking convolutional features correlation filter

Object collections:

Last modified:

Mar 12, 2024

In our library since:

Jul 21, 2022

Number of object content hits:

34

All available object's versions:

https://bc.itl.waw.pl/publication/2533

Show description in RDF format:

RDF

Show description in OAI-PMH format:

OAI-PMH

Edition name Date
Syihabuddin, Budi; Wibowo, Suryo Adhi; Prasetyo, Agus D.; Saputri, Desti Madya, Shallow Layer Convolutional Features with Correlation Filters for UAV Object Tracking, Journal of Telecommunications and Information Technology, 2022, nr 2 Mar 12, 2024

Objects Similar

2023, nr 4, JTIT-artykuły
2023, nr 4, JTIT-artykuły
A Problem of Detecting Stops While Tracking Moving Objects Under the Stream Processing Regime, Journal of Telecommunications and Information Technology, 2023, nr 4

Białoń, Paweł

2023
artykuł
High-level and Low-level Feature Set for Image Caption Generation with Optimized Convolutional Neural Network, Journal of Telecommunications and Information Technology, 2022, nr 4

Kalla, Mukesh Sharma, Arvind Padate, Roshni Jain, Amit

2022, nr 4
artykuł
2024, nr 3, JTIT-artykuły
2024, nr 3, JTIT-artykuły
A Deep Learning-based Approach for Channel Estimation in Multi-access Multi-antenna Systems, Journal of Telecommunications and Information Technology, 2024, nr 3

Qasaymeh, Mahmoud M. Alqatawneh, Ali Khodeir, Mahmoud A. Aljaafreh, Ahmad F.

2024, nr 3
artykuł
Preliminary Evaluation of Convolutional Neural Network Acoustic Model for Iban Language Using NVIDIA NeMo, Journal of Telecommunications and Information Technology, 20022, nr 1

Michael, Steve Olsen Mit, Edwin Juan, Sarah Samson

2022, nr 1
artykuł
Deep Learning-based SNR Estimation for Multistage Spectrum Sensing in Cognitive Radio Networks, Journal of Telecommunications and Information Technology, 2022, nr 4

Patil, Vilaskumar Jeevangi, Sanjeevkumar Jawaligi, Shivkumar

2022, nr 4
artykuł
More
×

Citation

Citation style:

Contact details

Address

Instytut Łączności – Państwowy Instytut Badawczy ul. Szachowa 1 04-894 Warszawa

Phone

(+48) 5128 696

E-Mail

biblioteka@il-pib.pl

Visit us!

This page uses 'cookies'. More information