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113 Results Found

  • Article
  • Open Access
3 Citations
2,517 Views
25 Pages

A Face Detection and Standardized Mask-Wearing Recognition Algorithm

  • Jimin Yu,
  • Xin Zhang,
  • Tao Wu,
  • Huilan Pan and
  • Wei Zhang

10 May 2023

In the era of coronavirus disease (COVID-19), wearing a mask could effectively protect people from the risk of infection and largely reduce transmission in public places. To prevent the spread of the virus, instruments are needed in public places to...

  • Article
  • Open Access
78 Citations
9,052 Views
16 Pages

15 January 2019

Building damage accounts for a high percentage of post-natural disaster assessment. Extracting buildings from optical remote sensing images is of great significance for natural disaster reduction and assessment. Traditional methods mainly are semi-au...

  • Article
  • Open Access
1 Citations
783 Views
20 Pages

1 October 2025

Manual pixel-level annotation remains a major bottleneck in deploying deep learning models for dense prediction and semantic segmentation tasks across domains. This challenge is especially pronounced in applications involving fine-scale structures, s...

  • Article
  • Open Access
182 Citations
13,366 Views
21 Pages

6 December 2019

Object detection in aerial images is a fundamental yet challenging task in remote sensing field. As most objects in aerial images are in arbitrary orientations, oriented bounding boxes (OBBs) have a great superiority compared with traditional horizon...

  • Article
  • Open Access
12 Citations
2,917 Views
16 Pages

Active Mask-Box Scoring R-CNN for Sonar Image Instance Segmentation

  • Fangjin Xu,
  • Jianxing Huang,
  • Jie Wu and
  • Longyu Jiang

Instance segmentation of sonar images is an effective method for underwater target recognition. However, the mismatch among positioning accuracy found by boxIoU and classification confidence, which is used as NMS score in current instance segmentatio...

  • Article
  • Open Access
2 Citations
2,127 Views
36 Pages

15 May 2025

Camera and LiDAR data fusion has been a popular research area, especially in the field of autonomous vehicles. This study evaluates the efficiency and accuracy of different depth point extraction methods, including Point-by-Point (PbyP), Complete Reg...

  • Article
  • Open Access
30 Citations
5,161 Views
22 Pages

Efficient Instance Segmentation Paradigm for Interpreting SAR and Optical Images

  • Fan Fan,
  • Xiangfeng Zeng,
  • Shunjun Wei,
  • Hao Zhang,
  • Dianhua Tang,
  • Jun Shi and
  • Xiaoling Zhang

23 January 2022

Instance segmentation in remote sensing images is challenging due to the object-level discrimination and pixel-level segmentation for the objects. In remote sensing applications, instance segmentation adopts the instance-aware mask, rather than horiz...

  • Article
  • Open Access
15 Citations
3,688 Views
27 Pages

Ship Instance Segmentation Based on Rotated Bounding Boxes for SAR Images

  • Xinpeng Yang,
  • Qiang Zhang,
  • Qiulei Dong,
  • Zhen Han,
  • Xiliang Luo and
  • Dongdong Wei

27 February 2023

Ship instance segmentation in synthetic aperture radar (SAR) images is a hard and challenging task, which not only locates ships but also obtains their shapes with pixel-level masks. However, in ocean SAR images, because of the consistent reflective...

  • Feature Paper
  • Article
  • Open Access
25 Citations
3,946 Views
17 Pages

Estimation of fruit size on-tree is useful for yield estimation, harvest timing and market planning. Automation of measurement of fruit size on-tree is possible using RGB-depth (RGB-D) cameras, if partly occluded fruit can be removed from considerati...

  • Article
  • Open Access
9 Citations
4,850 Views
16 Pages

Colorectal cancer (CRC) is a leading cause of mortality worldwide, and preventive screening modalities such as colonoscopy have been shown to noticeably decrease CRC incidence and mortality. Improving colonoscopy quality remains a challenging task du...

  • Article
  • Open Access
6 Citations
3,258 Views
19 Pages

12 May 2022

This paper proposes a learnable line encoding technique for bounding boxes commonly used in the object detection task. A bounding box is simply encoded using two main points: the top-left corner and the bottom-right corner of the bounding box; then,...

  • Article
  • Open Access
781 Views
20 Pages

Learning Precise Mask Representation for Siamese Visual Tracking

  • Peng Yang,
  • Fen Hu,
  • Qinghui Wang and
  • Lei Dou

15 September 2025

Siamese network trackers are a prominent paradigm in visual object tracking due to efficient similarity learning. However, most Siamese trackers are restricted to the bounding box tracking format, which often fails to accurately describe the appearan...

  • Article
  • Open Access
4 Citations
1,995 Views
21 Pages

23 January 2025

Airport runways, as the core part of airports, belong to vital national infrastructure, and the target detection and segmentation of airport runways in remote sensing images using deep learning methods have significant research value. Most of the exi...

  • Communication
  • Open Access
52 Citations
5,086 Views
18 Pages

25 November 2021

Since the mature green tomatoes have color similar to branches and leaves, some are shaded by branches and leaves, and overlapped by other tomatoes, the accurate detection and location of these tomatoes is rather difficult. This paper proposes to use...

  • Article
  • Open Access
1 Citations
2,916 Views
27 Pages

We introduce a weakly supervised segmentation approach that leverages class activation maps and the Segment Anything Model to generate high-quality masks using only classification data. A pre-trained classifier produces class activation maps that, on...

  • Article
  • Open Access
6 Citations
2,690 Views
17 Pages

Deep Learning Models Based on Pretreatment MRI and Clinicopathological Data to Predict Responses to Neoadjuvant Systemic Therapy in Triple-Negative Breast Cancer

  • Zhan Xu,
  • Zijian Zhou,
  • Jong Bum Son,
  • Haonan Feng,
  • Beatriz E. Adrada,
  • Tanya W. Moseley,
  • Rosalind P. Candelaria,
  • Mary S. Guirguis,
  • Miral M. Patel and
  • Gary J. Whitman
  • + 18 authors

13 March 2025

Purpose: To develop deep learning models for predicting the pathologic complete response (pCR) to neoadjuvant systemic therapy (NAST) in patients with triple-negative breast cancer (TNBC) based on pretreatment multiparametric breast MRI and clinicopa...

  • Article
  • Open Access
1,049 Views
25 Pages

17 October 2025

Accurate underground utility mapping remains a critical yet complex task in Ground Penetrating Radar (GPR) interpretation, essential to avoiding costly and dangerous excavation errors. This study presents a novel deep learning-based pipeline for 3D r...

  • Article
  • Open Access
141 Citations
8,653 Views
20 Pages

25 January 2020

Object detection has made significant progress in many real-world scenes. Despite this remarkable progress, the common use case of detection in remote sensing images remains challenging even for leading object detectors, due to the complex background...

  • Article
  • Open Access
10 Citations
13,219 Views
20 Pages

Segment-Tube: Spatio-Temporal Action Localization in Untrimmed Videos with Per-Frame Segmentation

  • Le Wang,
  • Xuhuan Duan,
  • Qilin Zhang,
  • Zhenxing Niu,
  • Gang Hua and
  • Nanning Zheng

22 May 2018

Inspired by the recent spatio-temporal action localization efforts with tubelets (sequences of bounding boxes), we present a new spatio-temporal action localization detector Segment-tube, which consists of sequences of per-frame segmentation masks. T...

  • Article
  • Open Access
19 Citations
3,558 Views
24 Pages

CPISNet: Delving into Consistent Proposals of Instance Segmentation Network for High-Resolution Aerial Images

  • Xiangfeng Zeng,
  • Shunjun Wei,
  • Jinshan Wei,
  • Zichen Zhou,
  • Jun Shi,
  • Xiaoling Zhang and
  • Fan Fan

15 July 2021

Instance segmentation of high-resolution aerial images is challenging when compared to object detection and semantic segmentation in remote sensing applications. It adopts boundary-aware mask predictions, instead of traditional bounding boxes, to loc...

  • Article
  • Open Access
4 Citations
1,308 Views
15 Pages

Segmentation Method of Zanthoxylum bungeanum Cluster Based on Improved Mask R-CNN

  • Zhiyong Zhang,
  • Shuo Wang,
  • Chen Wang,
  • Li Wang,
  • Yanqing Zhang and
  • Haiyan Song

12 September 2024

The precise segmentation of Zanthoxylum bungeanum clusters is crucial for developing picking robots. An improved Mask R-CNN model was proposed in this study for the segmentation of Zanthoxylum bungeanum clusters in natural environments. Firstly, the...

  • Article
  • Open Access
9 Citations
2,807 Views
23 Pages

AlgaeMask: An Instance Segmentation Network for Floating Algae Detection

  • Xiaoliang Wang,
  • Lei Wang,
  • Liangyu Chen,
  • Feng Zhang,
  • Kuo Chen,
  • Zhiwei Zhang,
  • Yibo Zou and
  • Linlin Zhao

Video surveillance on the offshore booster station and around the coast is a effective way to monitor floating macroalgae. Previous studies on floating algae detection are mainly based on traditional image segmentation methods. However, these algorit...

  • Article
  • Open Access
147 Citations
14,945 Views
17 Pages

Real-Time Face Mask Detection Method Based on YOLOv3

  • Xinbei Jiang,
  • Tianhan Gao,
  • Zichen Zhu and
  • Yukang Zhao

The rapid outbreak of COVID-19 has caused serious harm and infected tens of millions of people worldwide. Since there is no specific treatment, wearing masks has become an effective method to prevent the transmission of COVID-19 and is required in mo...

  • Article
  • Open Access
2 Citations
2,535 Views
18 Pages

Image Segmentation from Sparse Decomposition with a Pretrained Object-Detection Network

  • Yulin Wu,
  • Chuandong Lv,
  • Baoqing Ding,
  • Lei Chen,
  • Bin Zhou and
  • Hongchao Zhou

18 February 2022

Annotations for image segmentation are expensive and time-consuming. In contrast to image segmentation, the task of object detection is in general easier in terms of the acquisition of labeled training data and the design of training models. In this...

  • Article
  • Open Access
511 Views
15 Pages

Automatic Apparent Nasal Index from Single Facial Photographs Using a Lightweight Deep Learning Pipeline: A Pilot Study

  • Babak Saravi,
  • Lara Schorn,
  • Julian Lommen,
  • Max Wilkat,
  • Andreas Vollmer,
  • Hamza Eren Güzel,
  • Michael Vollmer,
  • Felix Schrader,
  • Christoph K. Sproll and
  • Norbert R. Kübler
  • + 1 author

27 October 2025

Background and Objectives: Quantifying nasal proportions is central to facial plastic and reconstructive surgery, yet manual measurements are time-consuming and variable. We sought to develop a simple, reproducible deep learning pipeline that localiz...

  • Communication
  • Open Access
647 Views
11 Pages

15 October 2025

Accurate segmentation of surgical instruments in endoscopic videos is crucial for robot-assisted surgery and intraoperative analysis. This paper presents a Segment-then-Classify framework that decouples mask generation from semantic classification to...

  • Article
  • Open Access
12 Citations
5,194 Views
17 Pages

12 January 2023

For the surface defects inspection task, operators need to check the defect in local detail images by specifying the location, which only the global 3D model reconstruction can’t satisfy. We explore how to address multi-type (original image, se...

  • Article
  • Open Access
54 Citations
12,020 Views
15 Pages

An Autonomous Fruit and Vegetable Harvester with a Low-Cost Gripper Using a 3D Sensor

  • Tan Zhang,
  • Zhenhai Huang,
  • Weijie You,
  • Jiatao Lin,
  • Xiaolong Tang and
  • Hui Huang

22 December 2019

Reliable and robust systems to detect and harvest fruits and vegetables in unstructured environments are crucial for harvesting robots. In this paper, we propose an autonomous system that harvests most types of crops with peduncles. A geometric appro...

  • Article
  • Open Access
15 Citations
3,673 Views
14 Pages

28 August 2019

The gradual application of deep learning in the field of computer vision and image processing has made great breakthroughs. Applications such as object detection, recognition and image semantic segmentation have been improved. In this study, to measu...

  • Article
  • Open Access
300 Citations
19,271 Views
17 Pages

Crack Detection and Comparison Study Based on Faster R-CNN and Mask R-CNN

  • Xiangyang Xu,
  • Mian Zhao,
  • Peixin Shi,
  • Ruiqi Ren,
  • Xuhui He,
  • Xiaojun Wei and
  • Hao Yang

5 February 2022

The intelligent crack detection method is an important guarantee for the realization of intelligent operation and maintenance, and it is of great significance to traffic safety. In recent years, the recognition of road pavement cracks based on comput...

  • Article
  • Open Access
14 Citations
2,999 Views
13 Pages

Research on Automatic Pavement Crack Recognition Based on the Mask R-CNN Model

  • Pengcheng Wang,
  • Chao Wang,
  • Hongwu Liu,
  • Ming Liang,
  • Wenhui Zheng,
  • Hao Wang,
  • Shichao Zhu,
  • Guoqiang Zhong and
  • Shang Liu

14 February 2023

Pavement will inevitably be damaged in the process of use; pavement damage detection and assessment are an important part of maintenance management. In order to prevent road diseases, it is necessary to fix the road cracks and implement automatic roa...

  • Article
  • Open Access
2 Citations
1,135 Views
38 Pages

14 February 2025

Green asparagus grows in clusters, which can cause overlaps with weeds and immature stems, making it difficult to identify suitable harvest targets and cutting points. Extracting precise stem details in complex spatial arrangements is a challenge. Th...

  • Article
  • Open Access
1,061 Views
25 Pages

Video instance segmentation (VIS) is plagued by the high cost of pixel-level annotation and defects of weakly supervised segmentation, leading to the urgent need for a trade-off between annotation cost and performance. We propose a novel In-Depth Col...

  • Article
  • Open Access
144 Citations
9,444 Views
18 Pages

A Novel Deep Learning Method for Recognition and Classification of Brain Tumors from MRI Images

  • Momina Masood,
  • Tahira Nazir,
  • Marriam Nawaz,
  • Awais Mehmood,
  • Junaid Rashid,
  • Hyuk-Yoon Kwon,
  • Toqeer Mahmood and
  • Amir Hussain

A brain tumor is an abnormal growth in brain cells that causes damage to various blood vessels and nerves in the human body. An earlier and accurate diagnosis of the brain tumor is of foremost important to avoid future complications. Precise segmenta...

  • Article
  • Open Access
4 Citations
3,310 Views
27 Pages

MOLO-SLAM: A Semantic SLAM for Accurate Removal of Dynamic Objects in Agricultural Environments

  • Jinhong Lv,
  • Beihuo Yao,
  • Haijun Guo,
  • Changlun Gao,
  • Weibin Wu,
  • Junlin Li,
  • Shunli Sun and
  • Qing Luo

Visual simultaneous localization and mapping (VSLAM) is a foundational technology that enables robots to achieve fully autonomous locomotion, exploration, inspection, and more within complex environments. Its applicability also extends significantly...

  • Article
  • Open Access
43 Citations
10,177 Views
23 Pages

Deep Learning-Based Computer-Aided Pneumothorax Detection Using Chest X-ray Images

  • Priyanka Malhotra,
  • Sheifali Gupta,
  • Deepika Koundal,
  • Atef Zaguia,
  • Manjit Kaur and
  • Heung-No Lee

15 March 2022

Pneumothorax is a thoracic disease leading to failure of the respiratory system, cardiac arrest, or in extreme cases, death. Chest X-ray (CXR) imaging is the primary diagnostic imaging technique for the diagnosis of pneumothorax. A computerized diagn...

  • Article
  • Open Access
1 Citations
2,982 Views
31 Pages

Electric power operation is necessary for the development of power grid companies, where the safety monitoring of electric power operation is difficult. Irregular deformable objects commonly used in electrical construction, such as safety belts and s...

  • Article
  • Open Access
11 Citations
3,655 Views
20 Pages

An Instance Segmentation Model Based on Deep Learning for Intelligent Diagnosis of Uterine Myomas in MRI

  • Haixia Pan,
  • Meng Zhang,
  • Wenpei Bai,
  • Bin Li,
  • Hongqiang Wang,
  • Haotian Geng,
  • Xiaoran Zhao,
  • Dongdong Zhang,
  • Yanan Li and
  • Minghuang Chen

Uterine myomas affect 70% of women of reproductive age, potentially impacting their fertility and health. Manual film reading is commonly used to identify uterine myomas, but it is time-consuming, laborious, and subjective. Clinical treatment require...

  • Article
  • Open Access
16 Citations
3,720 Views
20 Pages

23 December 2022

Orchard spraying robots must visually obtain citrus tree crown growth information to meet the variable growth-stage-based spraying requirements. However, the complex environments and growth characteristics of fruit trees affect the accuracy of crown...

  • Article
  • Open Access
41 Citations
5,719 Views
21 Pages

18 March 2020

Accurate and robust detection of multi-class objects in very high resolution (VHR) aerial images has been playing a significant role in many real-world applications. The traditional detection methods have made remarkable progresses with horizontal bo...

  • Article
  • Open Access
4 Citations
2,572 Views
15 Pages

A 2.5D Self-Training Strategy for Carotid Artery Segmentation in T1-Weighted Brain Magnetic Resonance Images

  • Adriel Silva de Araújo,
  • Márcio Sarroglia Pinho,
  • Ana Maria Marques da Silva,
  • Luis Felipe Fiorentini and
  • Jefferson Becker

Precise annotations for large medical image datasets can be time-consuming. Additionally, when dealing with volumetric regions of interest, it is typical to apply segmentation techniques on 2D slices, compromising important information for accurately...

  • Article
  • Open Access
2 Citations
1,467 Views
16 Pages

14 August 2025

Construction sites report the highest rate of industrial accidents, prompting the active development of smart safety management systems based on deep learning-based computer vision technology. To support the digital transformation of construction sit...

  • Article
  • Open Access
68 Citations
6,583 Views
10 Pages

Automated Detection and Segmentation of Early Gastric Cancer from Endoscopic Images Using Mask R-CNN

  • Tomoyuki Shibata,
  • Atsushi Teramoto,
  • Hyuga Yamada,
  • Naoki Ohmiya,
  • Kuniaki Saito and
  • Hiroshi Fujita

31 May 2020

Gastrointestinal endoscopy is widely conducted for the early detection of gastric cancer. However, it is often difficult to detect early gastric cancer lesions and accurately evaluate the invasive regions. Our study aimed to develop a detection and s...

  • Article
  • Open Access
59 Citations
10,728 Views
20 Pages

10 April 2023

Vision-based target detection and segmentation has been an important research content for environment perception in autonomous driving, but the mainstream target detection and segmentation algorithms have the problems of low detection accuracy and po...

  • Article
  • Open Access
1 Citations
1,615 Views
21 Pages

9 July 2025

Image segmentation is an important method in the field of image processing, while infrared (IR) image segmentation is one of the challenges in this field due to the unique characteristics of IR data. Infrared imaging utilizes the infrared radiation e...

  • Article
  • Open Access
14 Citations
7,197 Views
16 Pages

BIoU: An Improved Bounding Box Regression for Object Detection

  • Niranjan Ravi,
  • Sami Naqvi and
  • Mohamed El-Sharkawy

Object detection is a predominant challenge in computer vision and image processing to detect instances of objects of various classes within an image or video. Recently, a new domain of vehicular platforms, e-scooters, has been widely used across dom...

  • Article
  • Open Access
2,126 Views
16 Pages

Prompt Self-Correction for SAM2 Zero-Shot Video Object Segmentation

  • Jin Lee,
  • Ji-Hun Bae,
  • Dang Thanh Vu,
  • Le Hoang Anh,
  • Zahid Ur Rahman,
  • Heonzoo Lee,
  • Gwang-Hyun Yu and
  • Jin-Young Kim

10 September 2025

Foundation models, exemplified by the Segment Anything Model (SAM), have revolutionized object segmentation with their impressive zero-shot capabilities. The recent SAM2 extended these abilities to the video domain, utilizing an object pointer and me...

  • Article
  • Open Access
28 Citations
3,511 Views
15 Pages

8 August 2022

Background: Deep learning (DL) could predict isocitrate dehydrogenase (IDH) mutation status from MRIs. Yet, previous work focused on CNNs with refined tumor segmentation. To bridge the gap, this study aimed to evaluate the feasibility of developing a...

  • Article
  • Open Access
37 Citations
4,295 Views
17 Pages

Detection and Counting of Maize Leaves Based on Two-Stage Deep Learning with UAV-Based RGB Image

  • Xingmei Xu,
  • Lu Wang,
  • Meiyan Shu,
  • Xuewen Liang,
  • Abu Zar Ghafoor,
  • Yunling Liu,
  • Yuntao Ma and
  • Jinyu Zhu

27 October 2022

Leaf age is an important trait in the process of maize (Zea mays L.) growth. It is significant to estimate the seed activity and yield of maize by counting leaves. Detection and counting of the maize leaves in the field are very difficult due to the...

  • Article
  • Open Access
15 Citations
2,945 Views
19 Pages

14 May 2024

With the rapid development of artificial intelligence, computer vision techniques have been successfully applied to concrete defect diagnosis in bridge structural health monitoring. To enhance the accuracy of identifying the location and type of conc...

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