Advanced search ?

Object

Semantic Segmentation of Plant Structures with Deep Learning and Channel-wise Attention Mechanism, Journal of Telecommunications and Information Technology, 2025, nr 1
Download

Title: Semantic Segmentation of Plant Structures with Deep Learning and Channel-wise Attention Mechanism, Journal of Telecommunications and Information Technology, 2025, nr 1

Creator:

Surehli, Mukund Kumar ; Aggarwal, Naveen ; Joshi, Garima ; Harsh Nayyar, Harsh

Date:

2025, nr 1

Resource Type:

artykuł

Group publication title:

2025, nr 1, JTIT-artykuły

Description:

kwartalnik

Abstrakt:

Semantic segmentation of plant images is crucial for various agricultural applications and creates the need to develop more demanding models that are capable of handling images in a diverse range of conditions. This paper introduces an extended DeepLabV3+ model with a channel-wise attention mechanism, designed to provide precise semantic segmentation while emphasizing crucial features. It leverages semantic information with global context and is capable of handling object scale variations within the image. The proposed approach aims to provide a well generalized model that may be adapted to various field conditions by training and tests performed on multiple datasets, including Eschikon wheat segmentation (EWS), humans in the loop (HIL), computer vision problems in plant phenotyping (CVPPP), and a custom "botanic mixed set" dataset. Incorporating an ensemble training paradigm, the proposed architecture achieved an intersection over union (IoU) score of 0.846, 0.665 and 0.975 on EWS, HIL plant segmentation, and CVPPP datasets, respectively. The trained model exhibited robustness to variations in lighting, backgrounds, and subject angles, showcasing its adaptability to real-world applications.

Number:

1

Publisher:

National Institute of Telecommunications

Resource Identifier:

oai:bc.itl.waw.pl:2379

DOI:

10.26636/jtit.2025.1.1853

eISSN:

on-line: ISSN 1899-8852

Source:

Journal of Telecommunications and Information Technology

Language:

ang

Rights Management:

Biblioteka Naukowa Instytutu Łączności

License:

CC BY 4.0

Subject and keywords:

channel-wise attention computer vision DeepLabV3+ deep learning plant segmentation semantic segmentation

Object collections:

Last modified:

Feb 25, 2026

In our library since:

Apr 16, 2025

Number of object content hits:

198

All available object's versions:

https://bc.itl.waw.pl/publication/2694

Show description in RDF format:

RDF

Show description in OAI-PMH format:

OAI-PMH

Edition name Date
Surehli, Mukund Kumar; Aggarwal, Naveen; Joshi, Garima, Semantic Segmentation of Plant Structures with Deep Learning and Channel-wise Attention Mechanism, Journal of Telecommunications and Information Technology, 2025, nr 1 Feb 25, 2026

Objects Similar

2025, nr 1, JTIT-artykuły
2025, nr 1, JTIT-artykuły
FPGA-based Low Latency Square Root CORDIC Algorithm, Journal of Telecommunications and Information Technology, 2025, nr 1

Węgrzyn, Mariusz Voytusik, Stepan Gavkalova, Nataliia

2025, nr 1
artykuł
2025, nr 3, JTIT-artykuły
2025, nr 3, JTIT-artykuły
Enhancing Leaf Area Segmentation by Using Attention Gates and Knowledge Distillation in UNet Architecture, Journal of Telecommunications and Information Technology, 2025, nr 3

Shamim Banu, A. Deivalakshmi, S.

2025, nr 3
artykuł
2024, nr 3, JTIT-artykuły
2024, nr 3, JTIT-artykuły
A Generalized Learning Approach to Deep Neural Networks, Journal of Telecommunications and Information Technology, 2024, nr 3

Ponti, Francesca Frezza, Fabrizio Simeoni, Patrizio Parisi, Raffaele

2024, nr 3
artykuł
2025, nr 3, JTIT-artykuły
2025, nr 3, JTIT-artykuły
A Comprehensive Study on Path Loss Estimation Using Deep Hybrid Learning in 5G Networks, Journal of Telecommunications and Information Technology, 2025, nr 3

Yeaser, Kazi Md Abrar Hassan, Kazi Md Abir

2025, nr 3
artykuł
2026, nr 3, JTIT-artykuły
2026, nr 3, JTIT-artykuły
Explainable Network Traffic Classification Using XGBoost and SHAP: Interpreting Feature Contributions Across Traffic Classes, Journal of Telecommunications and Information Technology, 2026, nr 3

Deghem, Boubakar Seddik Aid, Lahcene Mostefaoui, Kadda

2026, nr 3
artykuł
2025, nr 4, JTIT-artykuły
2025, nr 4, JTIT-artykuły
AI-based Violent Incident Detection in Surveillance Videos to Enhance Public Safety, Journal of Telecommunications and Information Technology, 2025, nr 4

Merit, Khaled Beladgham, Mohammed

2025, nr 4
artykuł
2024, nr 4, JTIT-artykuły
2024, nr 4, JTIT-artykuły
Enhancing Biometric Security with Bimodal Deep Learning and Feature-Level Fusion of Facial and Voice Data, Journal of Telecommunications and Information Technology, 2024, nr 4

Merit, Khaled Beladgham, Mohammed

2024, nr 4
artykuł
2025, nr 1, JTIT-artykuły
2025, nr 1, JTIT-artykuły
Enhancing Cloud-Hosted Phishing Detection Using RNN-LSTM: A Deep Learning Framework, Journal of Telecommunications and Information Technology, 2025

Senouci, Oussama Benaouda, Nadjib

2025, nr 1
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