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Shanghao Liu, Chunjiang Zhao, Hongming Zhang, Qifeng Li, Shuqin Li, Yini Chen, Ronghua Gao, Rong Wang and Xuwen Li
A clear understanding of the number of pigs plays a crucial role in breeding management. Computer vision technology possesses several advantages, as it is harmless and labour-saving compared to traditional counting methods. Nevertheless, the existing met...
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Xiang Yue, Kai Qi, Xinyi Na, Yang Zhang, Yanhua Liu and Cuihong Liu
The spread of infections and rot are crucial factors in the decrease in tomato production. Accurately segmenting the affected tomatoes in real-time can prevent the spread of illnesses. However, environmental factors and surface features can affect tomato...
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Semen Mukhamadiev, Sergey Nesteruk, Svetlana Illarionova and Andrey Somov
Plant segmentation is a challenging computer vision task due to plant images complexity. For many practical problems, we have to solve even more difficult tasks. We need to distinguish plant parts rather than the whole plant. The major complication of mu...
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Sunguk Jung, Hyeonbeom Heo, Sangheon Park, Sung-Uk Jung and Kyungjae Lee
Instance segmentation has gained attention in various computer vision fields, such as autonomous driving, drone control, and sports analysis. Recently, many successful models have been developed, which can be classified into two categories: accuracy- and...
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Shinjin Kang and Jong-in Choi
On the game screen, the UI interface provides key information for game play. A vision deep learning network exploits pure pixel information in the screen. Apart from this, if we separately extract the information provided by the UI interface and use it a...
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Yanmin Chen, Xiu Li, Mei Jia, Jiuliang Li, Tianyang Hu and Jun Luo
In order to achieve accurate segmentation of each grape image per berry, we construct a dataset composed of red globe grape samples and use a two-stage ?localization?segmentation? framework-based mask region convolutional neural network (Mask R-CNN) and ...
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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 algorithms ...
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Xinyue Fan, Teng Liu, Hong Bao, Weiguo Pan, Tianjiao Liang and Han Li
In the field of computer vision, training a well-performing model on a dataset with a long-tail distribution is a challenging task. To address this challenge, image resampling is usually introduced as a simple and effective solution. However, when perfor...
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Yanwei Sun, Shirin Malihi, Hao Li and Mehdi Maboudi
Windows, as key components of building facades, have received increasing attention in facade parsing. Convolutional neural networks have shown promising results in window extraction. Most existing methods segment a facade into semantic categories and sub...
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Junling Liang, Heng Li, Fei Xu, Jianpin Chen, Meixuan Zhou, Liping Yin, Zhenzhen Zhai and Xinyu Chai
Cereal grains are a vital part of the human diet. The appearance quality and size distribution of cereal grains play major roles as deciders or indicators of market acceptability, storage stability, and breeding. Computer vision is popular in completing ...
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Dapeng Lang, Deyun Chen, Sizhao Li and Yongjun He
The deep model is widely used and has been demonstrated to have more hidden security risks. An adversarial attack can bypass the traditional means of defense. By modifying the input data, the attack on the deep model is realized, and it is imperceptible ...
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Hong Hai Hoang and Bao Long Tran
With the rapid development of cameras and deep learning technologies, computer vision tasks such as object detection, object segmentation and object tracking are being widely applied in many fields of life. For robot grasping tasks, object segmentation a...
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Guo-Shiang Lin, Kuan-Ting Lai, Jian-Ming Syu, Jen-Yung Lin and Sin-Kuo Chai
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Baoxi Yuan, Yang Li, Fan Jiang, Xiaojie Xu, Yingxia Guo, Jianhua Zhao, Deyue Zhang, Jianxin Guo and Xiaoli Shen
In the context of Industry 4.0, the most popular way to identify and track objects is to add tags, and currently most companies still use cheap quick response (QR) tags, which can be positioned by computer vision (CV) technology. In CV, instance segmenta...
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Zahra Ameli, Shabnam Jafarpoor Nesheli and Eric N. Landis
The application of deep learning (DL) algorithms has become of great interest in recent years due to their superior performance in structural damage identification, including the detection of corrosion. There has been growing interest in the application ...
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Fei Huang, Yanming Li, Zixiang Liu, Liang Gong and Chengliang Liu
The leaf area of pak choi is a critical indicator of growth rate, nutrient absorption, and photosynthetic efficiency, and it is required to be precisely measured for an optimal agricultural output. Traditional methods often fail to deliver the necessary ...
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Shuhe Zheng, Yang Liu, Wuxiong Weng, Xuexin Jia, Shilong Yu and Zuoxun Wu
Recognition and localization of fruits are key components to achieve automated fruit picking. However, current neural-network-based fruit recognition algorithms have disadvantages such as high complexity. Traditional stereo matching algorithms also have ...
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Yuanhong Li, Jiapeng Liao, Jing Wang, Yangfan Luo and Yubin Lan
The automated harvesting of clustered fruits relies on fast and accurate visual perception. However, the obscured stem diameters via leaf occlusion lack any discernible texture patterns. Nevertheless, our human visual system can often judge the position ...
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Huiyong Wang, Liang Guo, Ding Yang and Xiaoming Zhang
Road intelligence monitoring is an inevitable trend of urban intelligence, and clothing information is the main factor to identify pedestrians. Therefore, this paper establishes a multi-information clothing recognition model and proposes a data augmentat...
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Yane Li, Ying Wang, Dayu Xu, Jiaojiao Zhang and Jun Wen
The ?Kyoho? (Vitis labruscana) grape is one of the mainly fresh fruits; it is important to accurately segment the grape bunch and to detect its maturity level for the construction of an intelligent grape orchard. Grapes in the natural environment have di...
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