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Zhanlin Ji - IEEE Xplore Author Profile

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Author details

Zhanlin Ji

Publications

71

Citations

358

Publications by Year

20092024

Co-Authors:

Yongli AnChenxu DaiTiefan DingChengyuan DuZhu Fan

Show All Co-Authors (55)

Zhanlin Ji

Affiliation

College of Mathematics and Computer Science

Zhejiang A&F University

Hangzhou, P. R. China

Telecommunications Research Centre (TRC)

University of Limerick

Limerick, Ireland

Publication Topics

Convolutional Neural Network,
Feature Maps,
Neural Network,
Attention Mechanism,
Convolutional Layers,
Deep Learning,
F1 Score,
Contextual Information,
Intersection Over Union,
Segmentation Performance,
Deep Neural Network,
Dice Similarity Coefficient

Biography

Zhanlin Ji (Member, IEEE) received the Ph.D. degree from the University of Limerick, Ireland, in 2010. Currently, he is a Professor with Zhejiang Agriculture and Forestry University, China; and an Associate Researcher with the Telecommunications Research Centre (TRC), University of Limerick, Ireland. He was recipient of the Irish Research Council for Science, Engineering and Technology (IRCSET) Post-Graduate Research Scholarship, in 2008; and an IRC Postdoctoral Fellowship, in 2013. He has authored/co-authored more than 100 research papers in refereed journals and conferences. His research interests include the ubiquitous consumer wireless world (UCWW), Internet of Things (IoT), cloud computing, big data management, and artificial intellige...

Publications

71

Citations

358

Publications by Year

20092024

Co-Authors:

Yongli An
Chenxu Dai
Tiefan Ding
Chengyuan Du
Zhu Fan

Show All Co-Authors (55)

Author's Published Works

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Showing 1-25 of 71 results

Conferences (46)

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Zhanlin Ji(71)
Ivan Ganchev(69)
Máirtín O'Droma(16)
Máirtín O’Droma(11)
Mairtin O'Droma(11)
Telecommunications Research Centre (TRC), University of Limerick, Limerick, Ireland(25)
Telecommunications Research Centre, University of Limerick, Ireland(14)
Telecommunications Research Centre, University of Limerick, Limerick, Ireland(13)
Institute of Mathematics and Informatics—Bulgarian Academy of Sciences, Sofia, Bulgaria(12)
Department of Computer Systems, University of Plovdiv “Paisii Hilendarski”, Plovdiv, Bulgaria(11)
IEEE Access(22)
2021 International Conference Automatics and Informatics (ICAI)(3)
2021 International Conference on Computational Science and Computational Intelligence (CSCI)(3)
IEEE Transactions on Consumer Electronics(3)
2009 IEEE 70th Vehicular Technology Conference Fall(2)
IEEE(71)
Las Vegas, NV, USA(6)
Varna, Bulgaria(5)
Beijing, China(3)
Gran Canaria, Spain(3)
Anchorage, AK, USA(2)
Convolutional Neural Network(19)
Internet Of Things(17)
Big Data(14)
Wireless(14)
Feature Maps(13)

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IoT system for AQI monitoring and control

Ivan Ganchev;Zhanlin Ji

2024 International Conference Automatics and Informatics (ICAI)

Year: 2024 | Conference Paper |

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A horizontal-type IoT platform, named EMULSION, is presented*, which was developed for fast IoT system prototyping and speedy roll-out of respective IoT services. The successful use of the platform as a basis of various pilot systems, operating in different IoT areas, is show-cased on the example of ‘smart environment’ monitoring and control.Show More

IoT system for AQI monitoring and control

Ivan Ganchev;Zhanlin Ji

2024 International Conference Automatics and Informatics (ICAI)

Year: 2024 | Conference Paper |

Personalized Recommendations of Drugs to Patients

Jing Zhang;Chengyuan Du;Jiawen Jiang;Zhanlin Ji;Ivan Ganchev

2024 9th International Conference on Mathematics and Computers in Sciences and Industry (MCSI)

Year: 2024 | Conference Paper |

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The elaboration of efficient models for personalized drug recommendation, based on Electronic Health Records (EHRs), has important research significance and application value for assisting doctors in prescribing of drugs to patients. To this end, a novel recommendation model, called GAGRU, is proposed in this paper1, based on the classical Gated Recurrent Unit (GRU) model, combining a graph attent...Show More

Personalized Recommendations of Drugs to Patients

Jing Zhang;Chengyuan Du;Jiawen Jiang;Zhanlin Ji;Ivan Ganchev

2024 9th International Conference on Mathematics and Computers in Sciences and Industry (MCSI)

Year: 2024 | Conference Paper |

Impact of Channel Numbers and Training Epochs on U-Net’s Polyp Segmentation Performance

Zhanlin Ji;Ivan Ganchev

2024 7th International Conference on Signal Processing and Information Security (ICSPIS)

Year: 2024 | Conference Paper |

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Medical image segmentation plays an extremely crucial role in the modern field of medicine. It is a process that involves the precise delineation and labeling of medical images through computer technology. However, during the training of segmentation models, insufficient computational power is often a challenge. Despite having superior models, the lack of hardware resources may hinder the widespre...Show More

Impact of Channel Numbers and Training Epochs on U-Net’s Polyp Segmentation Performance

Zhanlin Ji;Ivan Ganchev

2024 7th International Conference on Signal Processing and Information Security (ICSPIS)

Year: 2024 | Conference Paper |

Novel SSD-Based Models for Detection of Multidimensional Pulmonary Nodules in CT Images

Zhanlin Ji;Shengnan Hao;Jianhua Pang;Ivan Ganchev

2024 7th International Conference on Signal Processing and Information Security (ICSPIS)

Year: 2024 | Conference Paper |

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Lung cancer, as one of the diseases with the highest incidence and mortality rates in the world, has always been a big challenge that humans are constantly striving to address. Pulmonary nodules, as one of the early manifestations of lung cancer, constitute a breakthrough in early detection of this disease and its prompt treatment. Currently, significant progress has been made in object detection ...Show More

Novel SSD-Based Models for Detection of Multidimensional Pulmonary Nodules in CT Images

Zhanlin Ji;Shengnan Hao;Jianhua Pang;Ivan Ganchev

2024 7th International Conference on Signal Processing and Information Security (ICSPIS)

Year: 2024 | Conference Paper |

4$ LuatOS-Based 4G IoT Gateway

Zhanlin Ji;Ivan Ganchev

2024 32nd National Conference with International Participation (TELECOM)

Year: 2024 | Conference Paper |

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This paper***This paper has emanated from joint research conducted with the financial support of the National Key Research and Development Program of China under Grant No. 2017YFE0135700 and the Bulgarian National Science Fund (BNSF) under Grant No. (KP-06-IP-CHINA/I). presents a low-cost 4G Internet of Things (IoT) gateway, developed with the LuatOS script running framework for integration into t...Show More

4$ LuatOS-Based 4G IoT Gateway

Zhanlin Ji;Ivan Ganchev

2024 32nd National Conference with International Participation (TELECOM)

Year: 2024 | Conference Paper |

YOLO-CXR: A Novel Detection Network for Locating Multiple Small Lesions in Chest X-Ray Images

Shengnan Hao;Xinlei Li;Wei Peng;Zhu Fan;Zhanlin Ji;Ivan Ganchev

Year: 2024 | Volume: 12 | Journal Article |

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Chest X-ray is one of the most widely used methods for clinical diagnosis of chest diseases. In recent years, the development of deep learning technologies has driven progress in chest disease detection, but existing methods still face numerous challenges. Current research primarily focuses on detecting specific chest diseases. However, when chest X-ray images indicate multiple diseases, the diver...Show More

YOLO-CXR: A Novel Detection Network for Locating Multiple Small Lesions in Chest X-Ray Images

Shengnan Hao;Xinlei Li;Wei Peng;Zhu Fan;Zhanlin Ji;Ivan Ganchev

Year: 2024 | Volume: 12 | Journal Article |

EFAM-Net: A Multi-Class Skin Lesion Classification Model Utilizing Enhanced Feature Fusion and Attention Mechanisms

Zhanlin Ji;Xuan Wang;Chunling Liu;Zhiwu Wang;Na Yuan;Ivan Ganchev

Year: 2024 | Volume: 12 | Journal Article |

Cited by: Papers (3)

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Skin cancer caused by common malignant tumors is a major threat to the health of patients. Automated classification of skin lesions using computer algorithms is crucial for enhancing diagnostic efficiency and reducing mortality rates associated with skin cancer. Enhancing the capabilities of image classification models for skin lesions is essential to assist in accurately classifying skin diseases...Show More

EFAM-Net: A Multi-Class Skin Lesion Classification Model Utilizing Enhanced Feature Fusion and Attention Mechanisms

Zhanlin Ji;Xuan Wang;Chunling Liu;Zhiwu Wang;Na Yuan;Ivan Ganchev

Year: 2024 | Volume: 12 | Journal Article |

MEFP-Net: A Dual-Encoding Multi-Scale Edge Feature Perception Network for Skin Lesion Segmentation

Shengnan Hao;Zidong Yu;Bao Zhang;Chenxu Dai;Zhu Fan;Zhanlin Ji;Ivan Ganchev

Year: 2024 | Volume: 12 | Journal Article |

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Skin lesion segmentation is an indispensable step in the diagnostic process of skin diseases. Using deep learning networks for skin lesion segmentation can enhance the work efficiency of medical personnel. However, skin lesions in dermoscopy images possess characteristics such as uneven region sizes and inconspicuous region edges, making it difficult for existing neural networks to accurately segm...Show More

MEFP-Net: A Dual-Encoding Multi-Scale Edge Feature Perception Network for Skin Lesion Segmentation

Shengnan Hao;Zidong Yu;Bao Zhang;Chenxu Dai;Zhu Fan;Zhanlin Ji;Ivan Ganchev

Year: 2024 | Volume: 12 | Journal Article |

ST-Double-Net: A Two-Stage Breast Tumor Classification Model Based on Swin Transformer and Weakly Supervised Target Localization

Shengnan Hao;Yihan Jia;Jianuo Liu;Zhiwu Wang;Chunling Liu;Zhanlin Ji;Ivan Ganchev

Year: 2024 | Volume: 12 | Journal Article |

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Breast cancer is the second deadliest cancer (after lung cancer) globally among women, with high incidence and mortality rates. Its early diagnosis is pivotal for improving the cure rate. With the continuous development and maturity of deep learning technologies, traditional classification models have been widely applied for automated classification of pathological images. However, several challen...Show More

ST-Double-Net: A Two-Stage Breast Tumor Classification Model Based on Swin Transformer and Weakly Supervised Target Localization

Shengnan Hao;Yihan Jia;Jianuo Liu;Zhiwu Wang;Chunling Liu;Zhanlin Ji;Ivan Ganchev

Year: 2024 | Volume: 12 | Journal Article |

DCM-CNER: A Dual-Channel Model for Clinical Named Entity Recognition Based on Embedded ConvNet and Gated Dilated CNN

Lin Shi;Wenyan Zhou;Yafeng Wu;Na Yuan;Xiangzhen Zang;Zhanlin Ji;Ivan Ganchev

Year: 2024 | Volume: 12 | Journal Article |

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As the volume of Chinese electronic medical records (EMRs) experiences an explosive growth, the application of clinical named entity recognition (CNER) technology becomes crucial for the effective utilization of EMR data and practical implementation of evidence-based medicine. While mainstream models excel in capturing global contextual information, their feature extraction mechanisms tend to be u...Show More

DCM-CNER: A Dual-Channel Model for Clinical Named Entity Recognition Based on Embedded ConvNet and Gated Dilated CNN

Lin Shi;Wenyan Zhou;Yafeng Wu;Na Yuan;Xiangzhen Zang;Zhanlin Ji;Ivan Ganchev

Year: 2024 | Volume: 12 | Journal Article |

BFG&MSF-Net: Boundary Feature Guidance and Multi-Scale Fusion Network for Thyroid Nodule Segmentation

Jianuo Liu;Juncheng Mu;Haoran Sun;Chenxu Dai;Zhanlin Ji;Ivan Ganchev

Year: 2024 | Volume: 12 | Journal Article |

Cited by: Papers (2)

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Accurately segmenting thyroid nodules in ultrasound images is crucial for computer-aided diagnosis. Despite the success of Convolutional Neural Networks (CNNs) and Transformers in natural images processing, they struggle with precise boundaries and small-object segmentation in ultrasound images. To address this, a novel BFG&MSF-Net model is proposed in this paper, utilizing four newly designed mod...Show More

BFG&MSF-Net: Boundary Feature Guidance and Multi-Scale Fusion Network for Thyroid Nodule Segmentation

Jianuo Liu;Juncheng Mu;Haoran Sun;Chenxu Dai;Zhanlin Ji;Ivan Ganchev

Year: 2024 | Volume: 12 | Journal Article |

DIRBW-Net: An Improved Inverted Residual Network Model for Underwater Image Enhancement

Yongli An;Yan Feng;Na Yuan;Zhanlin Ji;Ivan Ganchev

Year: 2024 | Volume: 12 | Journal Article |

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Underwater photography is challenged by optical distortions caused by water absorption and scattering phenomena. These distortions manifest as color aberrations, image blurring, and reduced contrast in underwater scenes. To address these issues, this paper proposes a novel underwater image enhancement model, called DIRBW-Net, leveraging an improved inverted residual network. In order to minimize t...Show More

DIRBW-Net: An Improved Inverted Residual Network Model for Underwater Image Enhancement

Yongli An;Yan Feng;Na Yuan;Zhanlin Ji;Ivan Ganchev

Year: 2024 | Volume: 12 | Journal Article |

BGRD-TransUNet: A Novel TransUNet-Based Model for Ultrasound Breast Lesion Segmentation

Zhanlin Ji;Haoran Sun;Na Yuan;Haiyang Zhang;Jiaxi Sheng;Xueji Zhang;Ivan Ganchev

Year: 2024 | Volume: 12 | Journal Article |

Cited by: Papers (2)

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Breast UltraSound (BUS) imaging is a commonly used diagnostic tool in the field of counter fighting breast diseases, especially for early detection and diagnosis of breast cancer. Due to the inherent characteristics of ultrasound images such as blurry boundaries and diverse tumor morphologies, it is challenging for doctors to manually segment breast tumors. In recent years, the Convolutional Neura...Show More

BGRD-TransUNet: A Novel TransUNet-Based Model for Ultrasound Breast Lesion Segmentation

Zhanlin Ji;Haoran Sun;Na Yuan;Haiyang Zhang;Jiaxi Sheng;Xueji Zhang;Ivan Ganchev

Year: 2024 | Volume: 12 | Journal Article |

A Novel Human Activity Recognition Model

Xinyi Zeng;Menghua Huang;Haiyang Zhang;Zhanlin Ji;Ivan Ganchev

2023 8th International Conference on Mathematics and Computers in Sciences and Industry (MCSI)

Year: 2023 | Conference Paper |

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With the continuous improvement of the living standard, people have changed their concept of disease treatment to health management. However, most of the current health management software makes recommendations based on users’ static information, with a low frequency of updates. The effect of targeted suggestions becomes weak with the passage of time, and it is hard for their recommendation effect...Show More

A Novel Human Activity Recognition Model

Xinyi Zeng;Menghua Huang;Haiyang Zhang;Zhanlin Ji;Ivan Ganchev

2023 8th International Conference on Mathematics and Computers in Sciences and Industry (MCSI)

Year: 2023 | Conference Paper |

ConvNeXt-ST-AFF: A Novel Skin Disease Classification Model Based on Fusion of ConvNeXt and Swin Transformer

Shengnan Hao;Liguo Zhang;Yanyan Jiang;Jingkun Wang;Zhanlin Ji;Li Zhao;Ivan Ganchev

Year: 2023 | Volume: 11 | Journal Article |

Cited by: Papers (8)

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Automatic classification of dermatological images is an important technology that assists doctors in performing faster and more accurate classification of skin diseases. Recently, convolutional neural networks (CNNs) and Transformer networks have been employed in learning respectively the local and global features of lesion images. However, existing works mainly focus on utilizing a single neural ...Show More

ConvNeXt-ST-AFF: A Novel Skin Disease Classification Model Based on Fusion of ConvNeXt and Swin Transformer

Shengnan Hao;Liguo Zhang;Yanyan Jiang;Jingkun Wang;Zhanlin Ji;Li Zhao;Ivan Ganchev

Year: 2023 | Volume: 11 | Journal Article |

ResDSda_U-Net: A Novel U-Net-Based Residual Network for Segmentation of Pulmonary Nodules in Lung CT Images

Zhanlin Ji;Ziheng Zhao;Xinyi Zeng;Jingkun Wang;Li Zhao;Xueji Zhang;Ivan Ganchev

Year: 2023 | Volume: 11 | Journal Article |

Cited by: Papers (5)

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The timely detection and segmentation of pulmonary nodules in lung computed tomography (CT) images can aid in the early diagnosis and treatment of lung cancer. However, manual segmentation of pulmonary nodules by doctors is highly demanding in terms of operational requirements and efficiency. To effectively improve the pulmonary nodule segmentation, this paper proposes a novel neural network, call...Show More

ResDSda_U-Net: A Novel U-Net-Based Residual Network for Segmentation of Pulmonary Nodules in Lung CT Images

Zhanlin Ji;Ziheng Zhao;Xinyi Zeng;Jingkun Wang;Li Zhao;Xueji Zhang;Ivan Ganchev

Year: 2023 | Volume: 11 | Journal Article |

CACDU-Net: A Novel DoubleU-Net Based Semantic Segmentation Model for Skin Lesions Detection in Images

Shengnan Hao;Haotian Wu;Chengyuan Du;Xinyi Zeng;Zhanlin Ji;Xueji Zhang;Ivan Ganchev

Year: 2023 | Volume: 11 | Journal Article |

Cited by: Papers (6)

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Skin lesion segmentation is a critical task in the field of dermatology as it can aid in the early detection and diagnosis of skin diseases. Deep learning techniques have shown great potential in achieving accurate lesion segmentation. With the help of these techniques, the lesion segmentation process can be automated, thus reducing the impact of manual operations and subjective judgments. This ai...Show More

CACDU-Net: A Novel DoubleU-Net Based Semantic Segmentation Model for Skin Lesions Detection in Images

Shengnan Hao;Haotian Wu;Chengyuan Du;Xinyi Zeng;Zhanlin Ji;Xueji Zhang;Ivan Ganchev

Year: 2023 | Volume: 11 | Journal Article |

Lung Nodule Detection in Medical Images Based on Improved YOLOv5s

Zhanlin Ji;Yun Wu;Xinyi Zeng;Yongli An;Li Zhao;Zhiwu Wang;Ivan Ganchev

Year: 2023 | Volume: 11 | Journal Article |

Cited by: Papers (17)

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Lung cancer has the highest morbidity and mortality rate worldwide. The early detection of pulmonary nodules in lungs can help reduce the incidence of lung cancer. However, due to the great variance in shape, size, and location of pulmonary nodules, the detection of small nodules in medical images is very challenging. This paper proposes a novel YOLOv5-CASP model, based on YOLOv5s with the followi...Show More

Lung Nodule Detection in Medical Images Based on Improved YOLOv5s

Zhanlin Ji;Yun Wu;Xinyi Zeng;Yongli An;Li Zhao;Zhiwu Wang;Ivan Ganchev

Year: 2023 | Volume: 11 | Journal Article |

Improving Non-Negative Positive-Unlabeled Learning for News Headline Classification

Zhanlin Ji;Chengyuan Du;Jiawen Jiang;Li Zhao;Haiyang Zhang;Ivan Ganchev

Year: 2023 | Volume: 11 | Journal Article |

Cited by: Papers (4)

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With the development of Internet technology, network platforms have gradually become a tool for people to obtain hot news. How to filter out the current hot news from a large number of news collections and push them to users has important application value. In supervised learning scenarios, each piece of news needs to be labeled manually, which takes a lot of time and effort. From the perspective ...Show More

Improving Non-Negative Positive-Unlabeled Learning for News Headline Classification

Zhanlin Ji;Chengyuan Du;Jiawen Jiang;Li Zhao;Haiyang Zhang;Ivan Ganchev

Year: 2023 | Volume: 11 | Journal Article |

G2-ResNeXt: A Novel Model for ECG Signal Classification

Shengnan Hao;Hang Xu;Hongyu Ji;Zhiwu Wang;Li Zhao;Zhanlin Ji;Ivan Ganchev

Year: 2023 | Volume: 11 | Journal Article |

Cited by: Papers (3)

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Electrocardiograms (ECG) are the primary basis for the diagnosis of cardiovascular diseases. However, due to the large volume of patients’ ECG data, manual diagnosis is time-consuming and laborious. Therefore, intelligent automatic ECG signal classification is an important technique for overcoming the shortage of medical resources. This paper proposes a novel model for inter-patient heartbeat clas...Show More

G2-ResNeXt: A Novel Model for ECG Signal Classification

Shengnan Hao;Hang Xu;Hongyu Ji;Zhiwu Wang;Li Zhao;Zhanlin Ji;Ivan Ganchev

Year: 2023 | Volume: 11 | Journal Article |

A Learning-Based End-to-End Wireless Communication System Utilizing a Deep Neural Network Channel Module

Yongli An;Shaomeng Wang;Li Zhao;Zhanlin Ji;Ivan Ganchev

Year: 2023 | Volume: 11 | Journal Article |

Cited by: Papers (9)

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The existing end-to-end (E2E) wireless communication systems require fewer communication modules and have a simple processing signal flow, compared to conventional wireless communication systems. However, in the absence of a differentiable channel model, it is impossible to train transmitters, used in such systems, which makes impossible achieving optimal system performance. To solve this problem,...Show More

A Learning-Based End-to-End Wireless Communication System Utilizing a Deep Neural Network Channel Module

Yongli An;Shaomeng Wang;Li Zhao;Zhanlin Ji;Ivan Ganchev

Year: 2023 | Volume: 11 | Journal Article |

Remote Sensing Image Detection Based on YOLOv4 Improvements

Xunkai Yang;Jingyi Zhao;Haiyang Zhang;Chenxu Dai;Li Zhao;Zhanlin Ji;Ivan Ganchev

Year: 2022 | Volume: 10 | Journal Article |

Cited by: Papers (10)

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Remote sensing image target object detection and recognition are widely used both in military and civil fields. There are many models proposed for this purpose, but their effectiveness on target object detection in remote sensing images is not ideal due to the influence of climate conditions, obstacles and confusing objects presented in images, image clarity, and associated problems with small-tar...Show More

Remote Sensing Image Detection Based on YOLOv4 Improvements

Xunkai Yang;Jingyi Zhao;Haiyang Zhang;Chenxu Dai;Li Zhao;Zhanlin Ji;Ivan Ganchev

Year: 2022 | Volume: 10 | Journal Article |

Intelligent System for Recommendation of Mobile Services to Consumers

Ivan Ganchev;Zhanlin Ji;Máirtín O’Droma

2022 3rd URSI Atlantic and Asia Pacific Radio Science Meeting (AT-AP-RASC)

Year: 2022 | Conference Paper |

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This paper presents an intelligent system for recommendation of services to mobile users (consumers) by considering the current context. The system builds up and dynamically manages personal profiles of consumers, aiming to facilitate and optimize the service discovery and recommendation process, in support of consumers’ choices for getting the best ‘cost / quality of experience (QoE)’ ratio when ...Show More

Intelligent System for Recommendation of Mobile Services to Consumers

Ivan Ganchev;Zhanlin Ji;Máirtín O’Droma

2022 3rd URSI Atlantic and Asia Pacific Radio Science Meeting (AT-AP-RASC)

Year: 2022 | Conference Paper |

Designing a Low-cost High-end Android-based Wireless Board for the EMULSION IoT Platform

Ivan Ganchev;Zhanlin Ji;Máirtín O’Droma

2022 3rd URSI Atlantic and Asia Pacific Radio Science Meeting (AT-AP-RASC)

Year: 2022 | Conference Paper |

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This paper proposes an innovative generic wireless low-cost high-end Android-based board for use by the EMULSION IoT platform, which is being elaborated as IoT-service and IoT-system prototyping ready. Based on the AllWinner A33 quad core Cortex-A7 CPU with a Mali400MP2 GPU and 512MB RAM, the board supports a 5MP CMOS sensor camera, 1080p video, MIDP display, and Hi-Fi audio. The paper reveals the...Show More

Designing a Low-cost High-end Android-based Wireless Board for the EMULSION IoT Platform

Ivan Ganchev;Zhanlin Ji;Máirtín O’Droma

2022 3rd URSI Atlantic and Asia Pacific Radio Science Meeting (AT-AP-RASC)

Year: 2022 | Conference Paper |

Improved Vision-Based Vehicle Detection and Classification by Optimized YOLOv4

Jingyi Zhao;Shengnan Hao;Chenxu Dai;Haiyang Zhang;Li Zhao;Zhanlin Ji;Ivan Ganchev

Year: 2022 | Volume: 10 | Journal Article |

Cited by: Papers (41)

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Rapid and precise detection and classification of vehicles are vital for the intelligent transportation systems (ITSs). However, due to small gaps between vehicles on the road and interference features of photos, or video frames containing vehicle images, it is difficult to detect and identify vehicle types quickly and precisely. For solving this problem, a new vehicle detection and classification...Show More

Improved Vision-Based Vehicle Detection and Classification by Optimized YOLOv4

Jingyi Zhao;Shengnan Hao;Chenxu Dai;Haiyang Zhang;Li Zhao;Zhanlin Ji;Ivan Ganchev

Year: 2022 | Volume: 10 | Journal Article |

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