Showing 1-25 of 6,860 resultsfor "Index Terms":Precise Detection
"Index Terms":Precise Detection
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For the problem that INS/GPS/ADS integrated navigation cannot accurately isolate faults, this paper establishes the chi-square detection models of INS/GPS and INS/ADS and the least squares detection model of GPS/ADS. A new isolation method is designed using the standard residuals component, which solves the position drift problem caused by isolating faulty GPS. By analyzing the diagnostic features...Show More
Multi-model cooperation based self organization multiple cameras system for robust moving object detection
2010 2nd International Conference on Computer Engineering and Technology
Year: 2010 | Conference Paper |
A self-organization multi-model cameras system for robust moving object detection is introduced. The system has three modules: automatic registration, cooperative motion detection and camera parameters change detection. The registration module automatically register visual camera and IR camera based on co-motion statistics. The cooperative motion detection produces precise results bases on coopera...Show More
Multi-Scale Infrared Small Target Detection Method via Precise Feature Matching and Scale Selection Strategy
Infrared small target detection is a crucial and challenging topic for various applications. In recent years, the spectrum scale space (SSS) algorithm has shown considerable potential in the field of target detection. However, the SSS algorithm is prone to high false alarm rates in infrared small target detection scenarios with complex background. This paper proposes an improved SSS (ISSS) algorit...Show More
In this paper, we present a fast object detection algorithm based on color histograms and local binary patterns (LBP). The proposed method consists of two steps: coarse target object detection and precise target object detection. During the coarse target object detection step, a small number of target candidates were generated using integral color histogram matching. To reduce computational comple...Show More
Network intrusion detection method based on Agent and SVM
2010 2nd IEEE International Conference on Information Management and Engineering
Year: 2010 | Conference Paper |
Cited by: Papers (10)
It is necessary to study a kind of network intrusion detection method which realizes faster attack detection and response. In order to improve the network intrusion detection precision further, Network intrusion detection method based on Agent and SVM is proposed to recognize the intrusion types in the paper. The network intrusion detection system based Agent and SVM are created. Then, network Int...Show More
Collision detection algorithm based on slice projection
2009 International Conference on Mechatronics and Automation
Year: 2009 | Conference Paper |
Rapid and accurate collision detection is of critical importance in physical simulations and in interactive use of virtual environments. At the same time, the complexity and the real-time of virtual environment bring a higher requirement to collision detection. In this paper, we present a novel collision detection algorithm based on the slice projection (SP). The process contains coarse detection ...Show More
Recognizing a Sequence of Events from Tennis Video Clips: Addressing Timestep Identification and Subtle Class Differences
Zhaoyu Liu;Jingyu Guo;Mo Wang;Ruicong Wang;Kan Jiang;Jin Song Dong
2023 IEEE 28th Pacific Rim International Symposium on Dependable Computing (PRDC)
Year: 2023 | Conference Paper |
Cited by: Papers (1)
Detecting temporally precise and fine-grained events from tennis videos is important in automatic video annotation. This paper addresses the challenges of recognizing a sequence of events from tennis video clips, focusing on accurate timestep identification and distinguishing subtle class differences. We propose a novel but simple end-to-end event detection network to accurately detect and identif...Show More
A Review of One-Stage Detection Algorithms in Autonomous Driving
2020 4th CAA International Conference on Vehicular Control and Intelligence (CVCI)
Year: 2020 | Conference Paper |
Cited by: Papers (20)
With the deep research on autonomous driving, the target detection algorithms based on 2D images have become a hot topic in recent years. In this paper, we mainly study the six mainstream deep learning detection algorithms, namely YOLO, YOLOv2, YOLOv3, YOLOv4, SSD and RetinaNet, which are used as the representative algorithms of the one-stage object detection methods. This paper is a review of the...Show More
A New Algorithm for Line Detection Based on Relative Maximum Point
2018 IEEE 3rd International Conference on Communication and Information Systems (ICCIS)
Year: 2018 | Conference Paper |
Cited by: Papers (1)
In this paper, a new algorithm for line detection was proposed. It finds out both ends of a possible straight line by searching the relative maximum points on closed envelope of Canny edge, then obtains the fitting variance of the possible straight lines through least squares fitting, and at last detects the straight lines in images through the ratio between fitting variance and line length as the...Show More
Small Target Detection Algorithm of Edge Scene Based on Improved YOLOv8
2024 13th International Conference of Information and Communication Technology (ICTech)
Year: 2024 | Conference Paper |
Presents an enhanced small target detection algorithm for edge scene applications based on the improved YOLOv8 framework, termed YOLOv8-VCS. The primary focus is on the detection and identification of small objects within edge scenarios, characterized by environments with limited computing resources, such as smart cameras and IoT devices. Recognizing the significance of efficient small target dete...Show More
On Object Detection Method of Tank Base on SNMS
2018 IEEE CSAA Guidance, Navigation and Control Conference (CGNCC)
Year: 2018 | Conference Paper |
Cited by: Papers (1)
The detection of overlapping tank targets in visible battlefield reconnaissance image was mainly studied. Analyzed the problem of the target detection of the Faster RCNN based on NMS and proposed the method of SNMS to improve the precision of detection and positioning of tank target detection in overlapping cases. In the process of bounding box regression, the traditional non-maximum suppression[4...Show More
Detection Model of Drainage Pipe Defect Based on Improved YOLOv5
2023 8th International Conference on Intelligent Computing and Signal Processing (ICSP)
Year: 2023 | Conference Paper |
A drainage pipe defect detection model based on improved YOLOv5 is proposed for the problem of leakage and error detection in the manual inspection of drainage pipes. First, the proposed CSSPPF module is added to the YOLOv5 network to enhance multi-scale feature learning, enhance feature map detail information extraction, and improve the detection precision of similar defect objects. Secondly, the...Show More
Multi-scale defect detection of printed circuit board based on feature pyramid network
2021 IEEE International Conference on Artificial Intelligence and Computer Applications (ICAICA)
Year: 2021 | Conference Paper |
Cited by: Papers (22)
Printed circuit board (PCB) is one of the most important components in electronic products, and with the improvement of production technology, the structure PCB is more and more refined, so it is very important for the quality inspection of PCB. The traditional PCB defect detection methods are slow, error prone and the cost of detection is high. With the development of deep learning, there are man...Show More
Fire detection method based on improved DETR
2024 4th International Symposium on AI (ISAI)
Year: 2024 | Conference Paper |
Fire, as a type of disaster, poses a significant threat to both life and property safety. Therefore, timely and accurate detection of fire occurrences is of utmost importance. However, current fire detection methods that rely on traditional sensors suffer from limitations such as a high false alarm rate and extended response time. In this manuscript, we propose a novel fire detection method based ...Show More
Performance Comparison of Overlapping Sound Event Detection Methods
Akshay Tyagi;Kartikeya Singh;P V S Jaswanth Kumar;Prof. Rakesh Garg;Mohammed Edres Yousef Abdullah
2024 14th International Conference on Cloud Computing, Data Science & Engineering (Confluence)
Year: 2024 | Conference Paper |
Sound event detection is pivotal in various applications, including environmental monitoring and surveillance systems, enhancing situational awareness and response strategies. This paper investigates the intricacies of overlapping sound events, where multiple events occur concurrently, creating complexities in accurate detection. Traditional methods falter when confronted with this challenge, nece...Show More
Fitting Landmark Detection on High-Voltage Cables
2024 6th International Conference on Energy Systems and Electrical Power (ICESEP)
Year: 2024 | Conference Paper |
Fittings play an important role in ensuring the safety and stability of transmission lines. Effective detection of these fittings is a prerequisite to upholding their reliability and security. Classic detection techniques only focus on the region and type of fittings, which needs to be improved to find potential problems such as misalignment. We propose a novel method to detect the exact location ...Show More
Rapid and precise object detection based on color histograms and adaptive bandwidth mean shift
2009 IEEE/RSJ International Conference on Intelligent Robots and Systems
Year: 2009 | Conference Paper |
Cited by: Papers (10)
Speed and precision are important for object detection algorithms. In this paper, a novel object detection algorithm based on color histogram and adaptive bandwidth mean shift is proposed. The algorithm is capable of detecting objects rapidly and precisely. It is composed of two stages: a rough detection stage and a precise detection stage. At the rough detection stage, histogram back projection a...Show More
Ellipse detection is one of the important parts of intelligent manufacturing, and the efficient detection of elliptical contours corresponding to hole parts is the prerequisite before performing practical applications. Aiming at enhancing the efficiency in ellipse detection, a fast and high-precision ellipse detection method based on the Candy’s theorem is proposed, in which the constrained simple...Show More
Orientation robust object detection in aerial images using deep convolutional neural network
Haigang Zhu;Xiaogang Chen;Weiqun Dai;Kun Fu;Qixiang Ye;Jianbin Jiao
2015 IEEE International Conference on Image Processing (ICIP)
Year: 2015 | Conference Paper |
Cited by: Papers (283)
Detecting objects in aerial images is challenged by variance of object colors, aspect ratios, cluttered backgrounds, and in particular, undetermined orientations. In this paper, we propose to use Deep Convolutional Neural Network (DCNN) features from combined layers to perform orientation robust aerial object detection. We explore the inherent characteristics of DC-NN as well as relate the extract...Show More
FPSSD7: Real-time Object Detection using 7 Layers of Convolution based on SSD
2019 International Conference of Advanced Informatics: Concepts, Theory and Applications (ICAICTA)
Year: 2019 | Conference Paper |
Cited by: Papers (2)
In recent years, attention has been paid to developing object detection methods from images, based on deep learning. In particular, toward self-driving cars, it is essential to make the detection as accurately as possible, as quickly as possible, as economically as possible. Here, we focus on SSD: Single Shot MultiBox Detector (SSD300) and attempt to improve it with less GPU memory. We propose a n...Show More
Shelf Product Detection Based on Deep Neural Network
2019 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)
Year: 2019 | Conference Paper |
Cited by: Papers (2)
Nowadays, there is a high demand for product detection in the background of shelves. Considering the structure of the shelf and the placement of products, this paper proposes a shelf product detection method based on RFBNet and combined with traditional image processing methods. The method firstly uses the edge detection and other image preprocessing methods to separate the shelves layer by layer ...Show More
Robust Object Detection Based on Decision Trees and a New Cascade Architecture
2008 International Conference on Computational Intelligence for Modelling Control & Automation
Year: 2008 | Conference Paper |
Cited by: Papers (2)
In this paper, we describe a robust object detectionmethod using Decision Trees and a new cascade architecture.On the one hand, we design a weak classifier formulti-valued features on AdaBoost algorithm based on DecisionTrees Method, which directly reduces training timeand increases the object detection’s precision. On the otherhand, the use of new cascade architecture is great helpfulfor the prob...Show More
Development of a Computer Vision Application for Mango (Mangifera Indica L.) Fruit Defect Detection Using YOLOv8 Architecture
Kaycee Kaye Villanueva;Juvy Amor M. Galindo;Apple Joy R. Tamayo;Jamie Eduardo C. Rosal;Daryl Ivan E. Hisola
2024 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET)
Year: 2024 | Conference Paper |
This study investigates the utilization of YOLOv8 architecture to detect and categorize defects in ‘Carabao’ mangoes, using machine learning and object detection methods, the model was trained on a dataset comprising 2,160 annotated images, augmented to enhance performance. Results demonstrated high accuracy rates: 100% for black spot, 80% for brown spot, and 83.33% for mango scab in real time app...Show More
Maritime Object Detection based on YOLOx for Aviation Image
2022 International Conference on Artificial Intelligence and Computer Information Technology (AICIT)
Year: 2022 | Conference Paper |
Accurate detection of ships in maritime scenarios is conducive to improving transport efficiency and reducing the occurrence of maritime traffic accidents. However, ships under the drone perspective are small and have various scale variations, affecting the detection algorithms. Aiming at this problem, this paper proposes a maritime object detection method based on YOLOx. First, the ship data in t...Show More
Research on Vehicle and Pedestrian Detection Algorithm in Foggy Weather Based on Improved YOLOv5s
2023 6th International Conference on Intelligent Robotics and Control Engineering (IRCE)
Year: 2023 | Conference Paper |
Aiming at the problem of the bad performance of current automatic driving perception algorithm in foggy weather, this paper proposes a vehicle and pedestrian detection algorithm in foggy weather based on improved YOLOv5s. Firstly, based on Cityscapes dataset, artificially generate foggy images of three concentrations to form Foggy Cityscapes dataset. Secondly, C3STR structure is introduced into th...Show More
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