Article
Medicine, Legal
Punam Sunil Raskar, Sanjeevani Kiran Shah
Summary: The paper presents a new method based on the YOLO (V2) model, successfully detecting Copy-Move attacks with good outcomes in terms of speed and accuracy.
FORENSIC SCIENCE INTERNATIONAL
(2021)
Article
Green & Sustainable Science & Technology
Yu Zhang, Zhongyin Guo, Jianqing Wu, Yuan Tian, Haotian Tang, Xinming Guo
Summary: This paper proposes an improved method for vehicle detection in different traffic scenarios based on an improved YOLO v5 network to reduce the false detection rate caused by occlusion. The proposed method enhances the network's perception of small targets through the Flip-Mosaic algorithm. A multi-type vehicle target dataset collected in different scenarios is used for training the detection model. Experimental results demonstrate that the Flip-Mosaic data enhancement algorithm can improve the accuracy of vehicle detection and reduce the false detection rate.
Article
Agriculture, Multidisciplinary
Yanchao Zhang, Jiya Yu, Yang Chen, Wen Yang, Wenbo Zhang, Yong He
Summary: In this study, a new deep neural network called RTSD-Net is proposed for real-time strawberry detection on harvesting machinery. By simplifying the structure and reducing parameters, the detection speed can be increased without sacrificing accuracy. After evaluation and acceleration, RTSD-Net exhibits good performance in edge computing.
COMPUTERS AND ELECTRONICS IN AGRICULTURE
(2022)
Article
Computer Science, Information Systems
Hamid R. Alsanad, Amin Z. Sadik, Osman N. Ucan, Muhammad Ilyas, Oguz Bayat
Summary: Drones are used for various tasks, but their misuse raises security concerns. This study proposes an improved real-time algorithm for drone detection, enhancing accuracy through the design of a convolutional neural network.
MULTIMEDIA TOOLS AND APPLICATIONS
(2022)
Article
Green & Sustainable Science & Technology
Kedar Nath Singh, Om Prakash Singh, Naman Baranwal, Amit Kumar Singh
Summary: This paper proposes a secure chaos-based image encryption algorithm for protecting the confidentiality and privacy of digital images. The algorithm utilizes the You Only Look Once v3 object detection algorithm and confusion and diffusion operations for key initialization and generation. Experimental results demonstrate that this algorithm outperforms other state-of-the-art schemes in terms of security and speed.
SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS
(2022)
Article
Chemistry, Analytical
Addie Ira Borja Parico, Tofael Ahamed
Summary: This study developed a real-time pear fruit counter using YOLOv4 and Deep SORT algorithm, finding a balance between accuracy, speed, and computational cost, as well as providing a method for choosing the most suitable model for agricultural science applications. YOLOv4-CSP was identified as the most accurate model, while YOLOv4-tiny was deemed more suitable for applications requiring lower speed and computational cost.
Article
Computer Science, Information Systems
Jeonghun Lee, Kwang-il Hwang
Summary: The paper discusses real-time object detection service of YOLO on AI embedded systems with resource constraints, proposing an AFC architecture to address real-time processing issues related to network cameras and efficiently provide real-time object detection service. Experimental results demonstrate that AFC can maintain high precision and convenience while minimizing total service delay.
MULTIMEDIA TOOLS AND APPLICATIONS
(2022)
Article
Entomology
Shuai Yang, Ziyao Xing, Hengbin Wang, Xinrui Dong, Xiang Gao, Zhe Liu, Xiaodong Zhang, Shaoming Li, Yuanyuan Zhao
Summary: Maize is a crucial crop, and pests can cause significant damage. Traditional pest detection methods are complex and inefficient, but recent advancements in deep learning have shown promise. This paper proposes a new real-time pest detection method based on deep convolutional neural networks (CNN), which offers higher accuracy, efficiency, and computational effort. Experimental results demonstrate that the proposed method outperforms others and strikes a good balance between accuracy, efficiency, and computational effort.
Article
Chemistry, Multidisciplinary
Heng Zhang, Yingzhou Wang, Yanli Liu, Naixue Xiong
Summary: This paper proposes an Intelligent Fast Detection (IFD) method for real-time image information in Industrial IoT, which reduces the loss of image information by introducing an improved YOLO-Tiny framework and a VaryBlock module. Experimental results show that the method improves the accuracy and detection speed of image information while meeting the speed requirement.
APPLIED SCIENCES-BASEL
(2022)
Article
Computer Science, Artificial Intelligence
Dan-Sebastian Bacea, Florin Oniga
Summary: In this paper, we propose Mini-YOLOv4-tiny, an improved lightweight one-stage object detector based on YOLOv4-tiny. We achieve model compression by selectively cutting the width of the last convolutional layers while maintaining performance. Additionally, we propose several improvements that enhance the model's receptive field and achieve state-of-the-art results among lightweight object detectors.
IMAGE AND VISION COMPUTING
(2023)
Article
Computer Science, Information Systems
Sudan Jha, Changho Seo, Eunmok Yang, Gyanendra Prasad Joshi
Summary: This paper introduces a system that enables real-time video surveillance in low-end edge computing environments by combining object detection tracking algorithm. The study proposes N-YOLO, a method that divides images into fixed-size sub-images and merges detection results using correlation-based tracking algorithm to significantly reduce computation for object detection and tracking. Additionally, a system is proposed to guarantee real-time performance in various edge computing environments by adaptively controlling the cycle of object detection and tracking.
MULTIMEDIA TOOLS AND APPLICATIONS
(2021)
Article
Computer Science, Artificial Intelligence
Vikram Jain, Ninad Jadhav, Marian Verhelst
Summary: This paper presents a resource and cost efficient hardware accelerator for CNN, implemented on FPGA with optimized architecture achieving the best DSP efficiency at 90% and Cost (efficiency) at 0.146. The exploration of algorithms and hardware was conducted using ZigZag design space exploration tool.
JOURNAL OF REAL-TIME IMAGE PROCESSING
(2022)
Article
Computer Science, Artificial Intelligence
Kai Chen, Zerun Wang, Xueyang Wang, Dahan Gong, Longlong Yu, Yuchen Guo, Guiguang Ding
Summary: This study proposes a novel framework called GigaDet for accurate and real-time object detection in gigapixel videos. The framework adopts a global-to-local strategy and combines patch generation network and decorated detector to improve the efficiency and accuracy of detection.
Article
Engineering, Multidisciplinary
Zongsheng Wu, Ru Xue, Hong Li
Summary: This paper proposes a video fire detection method based on improved YOLOv5. By introducing the dilated convolution module and improving the structure design, it enhances the ability of feature extraction and small-scale target detection. The experimental results show that it has a fast detection speed and high detection accuracy.
Article
Computer Science, Information Systems
Jin Wern Lai, Hafiz Rashidi Ramli, Luthffi Idzhar Ismail, Wan Zuha Wan Hasan
Summary: This paper presents a vision-based ripe FFB detection system as the first step in a robotic FFB harvesting system. The system utilizes a YOLOv4 model and live camera input to detect the presence of ripe FFBs on oil palm trees in real-time, reducing the loss of OER caused by human error.
Article
Computer Science, Hardware & Architecture
Jia Ke, Ying Wang, Mingyue Fan, Xiaojun Chen, Wenlong Zhang, Jianping Gou
Summary: This study integrates the emotional correlation analysis model and Self-organizing Map (SOM) to construct fine-grained user emotion vector based on review text and perform visual cluster analysis, which helps platform merchants quickly mine user clustering and characteristics.
COMPUTERS & ELECTRICAL ENGINEERING
(2024)
Article
Computer Science, Hardware & Architecture
Shi Qiu, Huping Ye, Xiaohan Liao, Benyue Zhang, Miao Zhang, Zimu Zeng
Summary: This paper proposes a multilevel-based algorithm for hyperspectral image interpretation, which achieves semantic segmentation through multidimensional information fusion, and introduces a context interpretation module to improve detection performance.
COMPUTERS & ELECTRICAL ENGINEERING
(2024)
Article
Computer Science, Hardware & Architecture
Jianteng Xu, Qingguo Bai, Zhiwen Li, Lili Zhao
Summary: This study constructs two optimization models for the omnichannel closed-loop supply chain by leveraging the combined power of leader-follower game and mean-variance theories. The focus is on analyzing the performance of manufacturers who distribute products through physical stores. The results show that the risk-averse attitude of the physical store has a positive impact on the overall system profitability, but if the introduced physical store belongs to another firm, total profit experiences a decline.
COMPUTERS & ELECTRICAL ENGINEERING
(2024)
Article
Computer Science, Hardware & Architecture
Jiahao Xiong, Weihua Ou, Zhonghua Liu, Jianping Gou, Wenjun Xiao, Haitao Liu
Summary: This paper proposes a novel remote photoplethysmography framework, named GraphPhys, which utilizes graph neural network to extract physiological signals and introduces Average Relative GraphConv for the task of remote physiological signal measurement. Experimental results show that the methods based on GraphPhys significantly outperform the original methods.
COMPUTERS & ELECTRICAL ENGINEERING
(2024)
Article
Computer Science, Hardware & Architecture
Zhiyao Tong, Yiyi Hu, Chi Jiang, Yin Zhang
Summary: The rise of illicit activities involving blockchain digital currencies has become a growing concern. In order to prevent illegal activities, this study combines financial risk control with machine learning to identify and predict the risks of users with poor credit. Experimental results demonstrate high performance in user financial credit analysis.
COMPUTERS & ELECTRICAL ENGINEERING
(2024)
