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54 Results Found

  • Article
  • Open Access
3 Citations
2,337 Views
16 Pages

15 August 2024

In order to improve the reading efficiency of pointer meter, this paper proposes a reading method based on LinkNet. Firstly, the meter dial area is detected using YOLOv8. Subsequently, the detected images are fed into the improved LinkNet segmentatio...

  • Article
  • Open Access
47 Citations
6,022 Views
15 Pages

25 February 2022

Skin cancer is common nowadays. Early diagnosis of skin cancer is essential to increase patients’ survival rate. In addition to traditional methods, computer-aided diagnosis is used in diagnosis of skin cancer. One of the benefits of this metho...

  • Article
  • Open Access
7 Citations
3,603 Views
25 Pages

Background: This research goes into in deep learning technologies within the realm of medical imaging, with a specific focus on the detection of anomalies in medical pathology, emphasizing breast cancer. It underscores the critical importance of segm...

  • Article
  • Open Access
2 Citations
2,349 Views
18 Pages

19 September 2023

Measuring water levels in an irrigation channel is an important task in irrigation system decision making and estimating the quantity of irrigation water supplies. This study aimed to measure water levels with image information from an irrigation cha...

  • Article
  • Open Access
2 Citations
1,984 Views
19 Pages

Chestnut Burr Segmentation for Yield Estimation Using UAV-Based Imagery and Deep Learning

  • Gabriel A. Carneiro,
  • Joaquim Santos,
  • Joaquim J. Sousa,
  • António Cunha and
  • Luís Pádua

1 October 2024

Precision agriculture (PA) has advanced agricultural practices, offering new opportunities for crop management and yield optimization. The use of unmanned aerial vehicles (UAVs) in PA enables high-resolution data acquisition, which has been adopted a...

  • Article
  • Open Access
11 Citations
3,559 Views
18 Pages

Computer Vision Method for Automatic Detection of Microstructure Defects of Concrete

  • Alexey N. Beskopylny,
  • Sergey A. Stel’makh,
  • Evgenii M. Shcherban’,
  • Irina Razveeva,
  • Alexey Kozhakin,
  • Besarion Meskhi,
  • Andrei Chernil’nik,
  • Diana Elshaeva,
  • Oksana Ananova and
  • Nikita Beskopylny
  • + 2 authors

5 July 2024

The search for structural and microstructural defects using simple human vision is associated with significant errors in determining voids, large pores, and violations of the integrity and compactness of particle packing in the micro- and macrostruct...

  • Review
  • Open Access
4 Citations
3,028 Views
23 Pages

Enhancing 3D Lung Infection Segmentation with 2D U-Shaped Deep Learning Variants

  • Anindya Apriliyanti Pravitasari,
  • Mohammad Hamid Asnawi,
  • Farid Azhar Lutfi Nugraha,
  • Gumgum Darmawan and
  • Triyani Hendrawati

24 October 2023

Accurate lung segmentation plays a vital role in generating 3D projections of lung infections, which contribute to the diagnosis and treatment planning of various lung diseases, including cases like COVID-19. This study capitalizes on the capabilitie...

  • Article
  • Open Access
16 Citations
3,728 Views
15 Pages

EfficientNetB0 cum FPN Based Semantic Segmentation of Gastrointestinal Tract Organs in MRI Scans

  • Neha Sharma,
  • Sheifali Gupta,
  • Mana Saleh Al Reshan,
  • Adel Sulaiman,
  • Hani Alshahrani and
  • Asadullah Shaikh

The segmentation of gastrointestinal (GI) organs is crucial in radiation therapy for treating GI cancer. It allows for developing a targeted radiation therapy plan while minimizing radiation exposure to healthy tissue, improving treatment success, an...

  • Article
  • Open Access
21 Citations
4,698 Views
19 Pages

A scSE-LinkNet Deep Learning Model for Daytime Sea Fog Detection

  • Xiaofei Guo,
  • Jianhua Wan,
  • Shanwei Liu,
  • Mingming Xu,
  • Hui Sheng and
  • Muhammad Yasir

20 December 2021

Sea fog is a precarious weather disaster affecting transportation on the sea. The accuracy of the threshold method for sea fog detection is limited by time and region. In comparison, the deep learning method learns features of objects through differe...

  • Article
  • Open Access
8 Citations
4,991 Views
25 Pages

LinkNet-Spectral-Spatial-Temporal Transformer Based on Few-Shot Learning for Mangrove Loss Detection with Small Dataset

  • Ilham Adi Panuntun,
  • Ilham Jamaluddin,
  • Ying-Nong Chen,
  • Shiou-Nu Lai and
  • Kuo-Chin Fan

19 March 2024

Mangroves grow in intertidal zones in tropical and subtropical regions, offering numerous advantages to humans and ecosystems. Mangrove monitoring is one of the important tasks to understand the current status of mangrove forests regarding their loss...

  • Article
  • Open Access
1 Citations
1,182 Views
11 Pages

20 December 2024

Numerous methods have been proposed for semantic segmentation and the state-of-the-art part is likely to be incorporated by deep learning-based methods which show a salient performance. This study addresses the challenge of semantic segmentation in l...

  • Article
  • Open Access
18 Citations
4,611 Views
19 Pages

Eigenloss: Combined PCA-Based Loss Function for Polyp Segmentation

  • Luisa F. Sánchez-Peralta,
  • Artzai Picón,
  • Juan Antonio Antequera-Barroso,
  • Juan Francisco Ortega-Morán,
  • Francisco M. Sánchez-Margallo and
  • J. Blas Pagador

7 August 2020

Colorectal cancer is one of the leading cancer death causes worldwide, but its early diagnosis highly improves the survival rates. The success of deep learning has also benefited this clinical field. When training a deep learning model, it is optimiz...

  • Article
  • Open Access
7 Citations
3,484 Views
17 Pages

Plant Disease Segmentation Networks for Fast Automatic Severity Estimation Under Natural Field Scenarios

  • Chenyi Zhao,
  • Changchun Li,
  • Xin Wang,
  • Xifang Wu,
  • Yongquan Du,
  • Huabin Chai,
  • Taiyi Cai,
  • Hengmao Xiang and
  • Yinghua Jiao

The segmentation of plant disease images enables researchers to quantify the proportion of disease spots on leaves, known as disease severity. Current deep learning methods predominantly focus on single diseases, simple lesions, or laboratory-control...

  • Article
  • Open Access
31 Citations
4,200 Views
19 Pages

23 September 2019

Roads are vital components of infrastructure, the extraction of which has become a topic of significant interest in the field of remote sensing. Because deep learning has been a popular method in image processing and information extraction, researche...

  • Article
  • Open Access
10 Citations
3,986 Views
28 Pages

Combining Images and Trajectories Data to Automatically Generate Road Networks

  • Xiangdong Bai,
  • Xuyu Feng,
  • Yuanyuan Yin,
  • Mingchun Yang,
  • Xingyao Wang and
  • Xue Yang

30 June 2023

Road network data are an important part of many applications, e.g., intelligent transportation and urban planning. At present, most of the approaches to road network generation are dominated by single data sources including images, point cloud data,...

  • Article
  • Open Access
951 Views
20 Pages

Semantic-to-Instance Segmentation of Time-Invariant Offshore Wind Farms Using Sentinel-1 Time Series and Time-Shift Augmentation

  • Osmar Luiz Ferreira de Carvalho,
  • Osmar Abílio de Carvalho Junior,
  • Anesmar Olino de Albuquerque and
  • Daniel Guerreiro e Silva

25 February 2025

The rapid expansion of offshore wind energy requires effective monitoring to balance renewable energy development with environmental and marine spatial planning. This study proposes a novel offshore wind farm detection methodology integrating Sentine...

  • Article
  • Open Access
17 Citations
3,351 Views
17 Pages

22 October 2022

The basic identification and classification of sedimentary rocks into sandstone and mudstone are important in the study of sedimentology and they are executed by a sedimentologist. However, such manual activity involves countless hours of observation...

  • Article
  • Open Access
3 Citations
3,414 Views
13 Pages

12 September 2023

Accurately identifying the boundaries of agricultural land is critical to the effective management of its resources. This includes the determination of property and land rights, the prevention of non-agricultural activities on agricultural land, and...

  • Article
  • Open Access
16 Citations
2,883 Views
25 Pages

Analysis of Geometric Characteristics of Cracks and Delamination in Aerated Concrete Products Using Convolutional Neural Networks

  • Irina Razveeva,
  • Alexey Kozhakin,
  • Alexey N. Beskopylny,
  • Sergey A. Stel’makh,
  • Evgenii M. Shcherban’,
  • Sergey Artamonov,
  • Anton Pembek and
  • Himanshu Dingrodiya

2 December 2023

Currently, artificial intelligence (AI) technologies are becoming a strategic vector for the development of companies in the construction sector. The introduction of “smart solutions” at all stages of the life cycle of building materials,...

  • Article
  • Open Access
16 Citations
4,775 Views
18 Pages

Efficient Occluded Road Extraction from High-Resolution Remote Sensing Imagery

  • Dejun Feng,
  • Xingyu Shen,
  • Yakun Xie,
  • Yangge Liu and
  • Jian Wang

7 December 2021

Road extraction is important for road network renewal, intelligent transportation systems and smart cities. This paper proposes an effective method to improve road extraction accuracy and reconstruct the broken road lines caused by ground occlusion....

  • Article
  • Open Access
3 Citations
2,341 Views
21 Pages

Railway Tracks Extraction from High Resolution Unmanned Aerial Vehicle Images Using Improved NL-LinkNet Network

  • Jing Wang,
  • Xiwei Fan,
  • Yunlong Zhang,
  • Xuefei Zhang,
  • Zhijie Zhang,
  • Wenyu Nie,
  • Yuanmeng Qi and
  • Nan Zhang

25 October 2024

The accurate detection of railway tracks from unmanned aerial vehicle (UAV) images is essential for intelligent railway inspection and the development of electronic railway maps. Traditional computer vision algorithms struggle with the complexities o...

  • Article
  • Open Access
19 Citations
3,597 Views
23 Pages

26 March 2020

Image mosaicking which is a process of constructing multiple orthoimages into a single seamless composite orthoimage, is one of the key steps for the production of large-scale digital orthophoto maps (DOM). Seamline determination is one of the most d...

  • Article
  • Open Access
1 Citations
2,630 Views
25 Pages

NGLSFusion: Non-Use GPU Lightweight Indoor Semantic SLAM

  • Le Wan,
  • Lin Jiang,
  • Bo Tang,
  • Yunfei Li,
  • Bin Lei and
  • Honghai Liu

23 April 2023

Perception of the indoor environment is the basis of mobile robot localization, navigation, and path planning, and it is particularly important to construct semantic maps in real time using minimal resources. The existing methods are too dependent on...

  • Article
  • Open Access
8 Citations
2,917 Views
20 Pages

20 October 2024

Remote sensing road extraction based on deep learning is an important method for road extraction. However, in complex remote sensing images, different road information often exhibits varying frequency distributions and texture characteristics, and it...

  • Article
  • Open Access
13 Citations
2,640 Views
18 Pages

17 November 2022

Bladder cancer is a common and often fatal disease. Papillary bladder tumors are well detectable using cystoscopic imaging, but small or flat lesions are frequently overlooked by urologists. However, detection accuracy can be improved if the images f...

  • Article
  • Open Access
24 Citations
3,943 Views
22 Pages

22 February 2024

This study focuses on the identification of collapsed buildings in satellite images after earthquakes through deep learning-based image segmentation models. The performance of four different architectures, namely U-Net, LinkNet, FPN, and PSPNet, was...

  • Article
  • Open Access
1 Citations
2,210 Views
25 Pages

16 April 2023

To assess the impact of the relative displacement between machines and subjects, the machine angle and the fine-tuning of the subject posture on the segmentation accuracy of chest X-rays, this paper proposes a Position and Direction Network (PDNet) f...

  • Article
  • Open Access
20 Citations
4,219 Views
16 Pages

Convolutional Blur Attention Network for Cell Nuclei Segmentation

  • Phuong Thi Le,
  • Tuan Pham,
  • Yi-Chiung Hsu and
  • Jia-Ching Wang

18 February 2022

Accurately segmented nuclei are important, not only for cancer classification, but also for predicting treatment effectiveness and other biomedical applications. However, the diversity of cell types, various external factors, and illumination conditi...

  • Article
  • Open Access
17 Citations
4,103 Views
16 Pages

Optimizing the Recognition and Feature Extraction of Wind Turbines through Hybrid Semantic Segmentation Architectures

  • Miguel-Ángel Manso-Callejo,
  • Calimanut-Ionut Cira,
  • Ramón Alcarria and
  • José-Juan Arranz-Justel

13 November 2020

Updating the mapping of wind turbines farms—found in constant expansion—is important to predict energy production or to minimize the risk of these infrastructures during storms. This geoinformation is not usually provided by public mappin...

  • Article
  • Open Access
2 Citations
2,192 Views
13 Pages

29 November 2022

Road scene segmentation is an integral part of the Intelligent Transport System (ITS) for precise interpretation of the environment and safer vehicle navigation. Traditional segmentation methods have faced difficulties in meeting the requirements of...

  • Article
  • Open Access
47 Citations
5,551 Views
24 Pages

B-FGC-Net: A Building Extraction Network from High Resolution Remote Sensing Imagery

  • Yong Wang,
  • Xiangqiang Zeng,
  • Xiaohan Liao and
  • Dafang Zhuang

7 January 2022

Deep learning (DL) shows remarkable performance in extracting buildings from high resolution remote sensing images. However, how to improve the performance of DL based methods, especially the perception of spatial information, is worth further study....

  • Article
  • Open Access
5 Citations
4,470 Views
24 Pages

Soil erosion worldwide is an intense, poorly controlled process. In many respects, this is a consequence of the lack of up-to-date high-resolution erosion maps. All over the world, the problem of insufficient information is solved in different ways,...

  • Article
  • Open Access
11 Citations
4,301 Views
19 Pages

27 January 2023

Aquatic invasive plants (AIPs) are a global threat to local biodiversity due to their rapid adaptation to the new environments. Lythrum salicaria, commonly known as purple loosestrife, is a predominant AIP in the upper Midwestern region of the United...

  • Article
  • Open Access
23 Citations
4,840 Views
27 Pages

MultiResUNet3+: A Full-Scale Connected Multi-Residual UNet Model to Denoise Electrooculogram and Electromyogram Artifacts from Corrupted Electroencephalogram Signals

  • Md Shafayet Hossain,
  • Sakib Mahmud,
  • Amith Khandakar,
  • Nasser Al-Emadi,
  • Farhana Ahmed Chowdhury,
  • Zaid Bin Mahbub,
  • Mamun Bin Ibne Reaz and
  • Muhammad E. H. Chowdhury

Electroencephalogram (EEG) signals immensely suffer from several physiological artifacts, including electrooculogram (EOG), electromyogram (EMG), and electrocardiogram (ECG) artifacts, which must be removed to ensure EEG’s usability. This paper...

  • Article
  • Open Access
124 Citations
8,322 Views
17 Pages

Automatic Faults Detection of Photovoltaic Farms: solAIr, a Deep Learning-Based System for Thermal Images

  • Roberto Pierdicca,
  • Marina Paolanti,
  • Andrea Felicetti,
  • Fabio Piccinini and
  • Primo Zingaretti

9 December 2020

Renewable energy sources will represent the only alternative to limit fossil fuel usage and pollution. For this reason, photovoltaic (PV) power plants represent one of the main systems adopted to produce clean energy. Monitoring the state of health o...

  • Article
  • Open Access
3 Citations
2,150 Views
16 Pages

7 August 2023

The black soil region of Northeast China is one of the most fertile soil areas in the world and serves as a crucial grain-producing region in China. However, excessive development and improper utilization have led to severe land use issues. Conductin...

  • Article
  • Open Access
2,191 Views
26 Pages

31 May 2025

Utilizing remote sensing models to monitor apple orchards facilitates the industrialization of agriculture and the sustainable development of rural land resources. This study enhanced the DeepLabv3+ model to achieve superior performance in apple orch...

  • Feature Paper
  • Article
  • Open Access
3 Citations
3,723 Views
19 Pages

20 November 2024

Electroencephalography (EEG) is a non-invasive technique widely used in neuroscience to diagnose neural disorders and analyse brain activity. However, ocular and myogenic artifacts from eye movements and facial muscle activity often contaminate EEG s...

  • Feature Paper
  • Article
  • Open Access
61 Citations
4,754 Views
19 Pages

Combined Multi-Layer Feature Fusion and Edge Detection Method for Distributed Photovoltaic Power Station Identification

  • Yongshi Jie,
  • Xianhua Ji,
  • Anzhi Yue,
  • Jingbo Chen,
  • Yupeng Deng,
  • Jing Chen and
  • Yi Zhang

21 December 2020

Distributed photovoltaic power stations are an effective way to develop and utilize solar energy resources. Using high-resolution remote sensing images to obtain the locations, distribution, and areas of distributed photovoltaic power stations over a...

  • Article
  • Open Access
7 Citations
4,222 Views
17 Pages

8 September 2021

Multiple Sclerosis (MS) is a neuroinflammatory demyelinating disease that affects over 2,000,000 individuals worldwide. It is characterized by white matter lesions that are identified through the segmentation of magnetic resonance images (MRIs). Manu...

  • Article
  • Open Access
16 Citations
3,944 Views
18 Pages

Dynamic Detection of Forest Change in Hunan Province Based on Sentinel-2 Images and Deep Learning

  • Jun Xiang,
  • Yuanjun Xing,
  • Wei Wei,
  • Enping Yan,
  • Jiawei Jiang and
  • Dengkui Mo

20 January 2023

Dynamic detection of forest change is the fundamental method of monitoring forest resources and an essential means of preserving the accuracy and timeliness of forest land resource data. This study focuses on a deep learning-based method for dynamic...

  • Article
  • Open Access
54 Citations
5,382 Views
14 Pages

Road extraction is a unique and difficult problem in the field of semantic segmentation because roads have attributes such as slenderness, long span, complexity, and topological connectivity, etc. Therefore, we propose a novel road extraction network...

  • Article
  • Open Access
20 Citations
5,125 Views
13 Pages

Segmentation of Aorta 3D CT Images Based on 2D Convolutional Neural Networks

  • Simone Bonechi,
  • Paolo Andreini,
  • Alessandro Mecocci,
  • Nicola Giannelli,
  • Franco Scarselli,
  • Eugenio Neri,
  • Monica Bianchini and
  • Giovanna Maria Dimitri

19 October 2021

The automatic segmentation of the aorta can be extremely useful in clinical practice, allowing the diagnosis of numerous pathologies to be sped up, such as aneurysms and dissections, and allowing rapid reconstructive surgery, essential in saving pati...

  • Article
  • Open Access
12 Citations
3,828 Views
19 Pages

Semantic Segmentation of Gastric Polyps in Endoscopic Images Based on Convolutional Neural Networks and an Integrated Evaluation Approach

  • Tao Yan,
  • Ye Ying Qin,
  • Pak Kin Wong,
  • Hao Ren,
  • Chi Hong Wong,
  • Liang Yao,
  • Ying Hu,
  • Cheok I Chan,
  • Shan Gao and
  • Pui Pun Chan

Convolutional neural networks (CNNs) have received increased attention in endoscopic images due to their outstanding advantages. Clinically, some gastric polyps are related to gastric cancer, and accurate identification and timely removal are critica...

  • Article
  • Open Access
757 Views
21 Pages

24 June 2025

To address the challenges in identifying NAPL contamination within low-permeability clay sites, this study innovatively integrates high-density electrical resistivity tomography (ERT) with a UNet deep learning model to establish an intelligent contam...

  • Article
  • Open Access
28 Citations
6,448 Views
28 Pages

Ensemble Transfer Learning for Fetal Head Analysis: From Segmentation to Gestational Age and Weight Prediction

  • Mahmood Alzubaidi,
  • Marco Agus,
  • Uzair Shah,
  • Michel Makhlouf,
  • Khalid Alyafei and
  • Mowafa Househ

15 September 2022

Ultrasound is one of the most commonly used imaging methodologies in obstetrics to monitor the growth of a fetus during the gestation period. Specifically, ultrasound images are routinely utilized to gather fetal information, including body measureme...

  • Article
  • Open Access
22 Citations
5,790 Views
25 Pages

12 December 2021

Mangroves are grown in intertidal zones along tropical and subtropical climate areas, which have many benefits for humans and ecosystems. The knowledge of mangrove conditions is essential to know the statuses of mangroves. Recently, satellite imagery...

  • Article
  • Open Access
5 Citations
2,601 Views
23 Pages

A Data-Centric Approach for Wind Plant Instance-Level Segmentation Using Semantic Segmentation and GIS

  • Osmar Luiz Ferreira de Carvalho,
  • Osmar Abílio de Carvalho Junior,
  • Anesmar Olino de Albuquerque,
  • Alex Gois Orlandi,
  • Issao Hirata,
  • Díbio Leandro Borges,
  • Roberto Arnaldo Trancoso Gomes and
  • Renato Fontes Guimarães

23 February 2023

Wind energy is one of Brazil’s most promising energy sources, and the rapid growth of wind plants has increased the need for accurate and efficient inspection methods. The current onsite visits, which are laborious and costly, have become unsus...

  • Article
  • Open Access
8 Citations
2,693 Views
21 Pages

19 May 2023

Smart feeding is essential for maximizing resource utilization, enhancing fish growth and welfare, and reducing environmental impact in intensive aquaculture. The image segmentation technique facilitates fish feeding behavior analysis to achieve quan...

  • Article
  • Open Access
5 Citations
2,585 Views
30 Pages

Text-Guided Synthesis in Medical Multimedia Retrieval: A Framework for Enhanced Colonoscopy Image Classification and Segmentation

  • Ojonugwa Oluwafemi Ejiga Peter,
  • Opeyemi Taiwo Adeniran,
  • Adetokunbo MacGregor John-Otumu,
  • Fahmi Khalifa and
  • Md Mahmudur Rahman

9 March 2025

The lack of extensive, varied, and thoroughly annotated datasets impedes the advancement of artificial intelligence (AI) for medical applications, especially colorectal cancer detection. Models trained with limited diversity often display biases, esp...

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