Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (125)
  • Open Access


    A Real-Time Localization Algorithm for Unmanned Aerial Vehicle Based on Continuous Images Processing

    Peng Geng1,*, Annan Yang2, Yan Liu3

    Journal on Artificial Intelligence, Vol.6, pp. 43-52, 2024, DOI:10.32604/jai.2024.047642

    Abstract This article presents a real-time localization method for Unmanned Aerial Vehicles (UAVs) based on continuous image processing. The proposed method employs the Scale Invariant Feature Transform (SIFT) algorithm to identify key points in multi-scale space and generate descriptor vectors to match identical objects across multiple images. These corresponding points in the image provide pixel positions, which can be combined with transformation equations, allow for the calculation of the UAV’s actual ground position. Additionally, the physical coordinates of matching points in the image can be obtained, corresponding to the UAV’s physical coordinates. The method achieves real-time positioning and tracking during UAV… More >

  • Open Access


    Maximum Correntropy Criterion-Based UKF for Loosely Coupling INS and UWB in Indoor Localization

    Yan Wang*, You Lu, Yuqing Zhou, Zhijian Zhao

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2673-2703, 2024, DOI:10.32604/cmes.2023.046743

    Abstract Indoor positioning is a key technology in today’s intelligent environments, and it plays a crucial role in many application areas. This paper proposed an unscented Kalman filter (UKF) based on the maximum correntropy criterion (MCC) instead of the minimum mean square error criterion (MMSE). This innovative approach is applied to the loose coupling of the Inertial Navigation System (INS) and Ultra-Wideband (UWB). By introducing the maximum correntropy criterion, the MCCUKF algorithm dynamically adjusts the covariance matrices of the system noise and the measurement noise, thus enhancing its adaptability to diverse environmental localization requirements. Particularly in the presence of non-Gaussian noise,… More >

  • Open Access


    Adaptive Segmentation for Unconstrained Iris Recognition

    Mustafa AlRifaee1, Sally Almanasra2,*, Adnan Hnaif3, Ahmad Althunibat3, Mohammad Abdallah3, Thamer Alrawashdeh3

    CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 1591-1609, 2024, DOI:10.32604/cmc.2023.043520

    Abstract In standard iris recognition systems, a cooperative imaging framework is employed that includes a light source with a near-infrared wavelength to reveal iris texture, look-and-stare constraints, and a close distance requirement to the capture device. When these conditions are relaxed, the system’s performance significantly deteriorates due to segmentation and feature extraction problems. Herein, a novel segmentation algorithm is proposed to correctly detect the pupil and limbus boundaries of iris images captured in unconstrained environments. First, the algorithm scans the whole iris image in the Hue Saturation Value (HSV) color space for local maxima to detect the sclera region. The image… More >

  • Open Access


    ThyroidNet: A Deep Learning Network for Localization and Classification of Thyroid Nodules

    Lu Chen1,#, Huaqiang Chen2,#, Zhikai Pan7, Sheng Xu2, Guangsheng Lai2, Shuwen Chen2,5,6, Shuihua Wang3,8, Xiaodong Gu2,6,*, Yudong Zhang3,4,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.1, pp. 361-382, 2024, DOI:10.32604/cmes.2023.031229

    Abstract Aim: This study aims to establish an artificial intelligence model, ThyroidNet, to diagnose thyroid nodules using deep learning techniques accurately. Methods: A novel method, ThyroidNet, is introduced and evaluated based on deep learning for the localization and classification of thyroid nodules. First, we propose the multitask TransUnet, which combines the TransUnet encoder and decoder with multitask learning. Second, we propose the DualLoss function, tailored to the thyroid nodule localization and classification tasks. It balances the learning of the localization and classification tasks to help improve the model’s generalization ability. Third, we introduce strategies for augmenting the data. Finally, we submit… More >

  • Open Access


    An Optimal Node Localization in WSN Based on Siege Whale Optimization Algorithm

    Thi-Kien Dao1, Trong-The Nguyen1,2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2201-2237, 2024, DOI:10.32604/cmes.2023.029880

    Abstract Localization or positioning scheme in Wireless sensor networks (WSNs) is one of the most challenging and fundamental operations in various monitoring or tracking applications because the network deploys a large area and allocates the acquired location information to unknown devices. The metaheuristic approach is one of the most advantageous ways to deal with this challenging issue and overcome the disadvantages of the traditional methods that often suffer from computational time problems and small network deployment scale. This study proposes an enhanced whale optimization algorithm that is an advanced metaheuristic algorithm based on the siege mechanism (SWOA) for node localization in… More >

  • Open Access


    Siamese Dense Pixel-Level Fusion Network for Real-Time UAV Tracking

    Zhenyu Huang1,2, Gun Li2, Xudong Sun1, Yong Chen1, Jie Sun1, Zhangsong Ni1,*, Yang Yang1,*

    CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 3219-3238, 2023, DOI:10.32604/cmc.2023.039489

    Abstract Onboard visual object tracking in unmanned aerial vehicles (UAVs) has attracted much interest due to its versatility. Meanwhile, due to high precision, Siamese networks are becoming hot spots in visual object tracking. However, most Siamese trackers fail to balance the tracking accuracy and time within onboard limited computational resources of UAVs. To meet the tracking precision and real-time requirements, this paper proposes a Siamese dense pixel-level network for UAV object tracking named SiamDPL. Specifically, the Siamese network extracts features of the search region and the template region through a parameter-shared backbone network, then performs correlation matching to obtain the candidate… More >

  • Open Access


    Estimating Anthropometric Soft Biometrics: An Empirical Method

    Bilal Hassan1,*, Hafiz Husnain Raza Sherazi2, Mubashir Ali3, Yusra Siddiqi2

    Intelligent Automation & Soft Computing, Vol.37, No.3, pp. 2727-2743, 2023, DOI:10.32604/iasc.2023.039275

    Abstract Following the success of soft biometrics over traditional biometrics, anthropometric soft biometrics are emerging as candidate features for recognition or retrieval using an image/video. Anthropometric soft biometrics uses a quantitative mode of annotation which is a relatively better method for annotation than qualitative annotations adopted by traditional biometrics. However, one of the most challenging tasks is to achieve a higher level of accuracy while estimating anthropometric soft biometrics using an image or video. The level of accuracy is usually affected by several contextual factors such as overlapping body components, an angle from the camera, and ambient conditions. Exploring and developing… More >

  • Open Access


    Underwater Waste Recognition and Localization Based on Improved YOLOv5

    Jinxing Niu1,*, Shaokui Gu1, Junmin Du2, Yongxing Hao1

    CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 2015-2031, 2023, DOI:10.32604/cmc.2023.040489

    Abstract With the continuous development of the economy and society, plastic pollution in rivers, lakes, oceans, and other bodies of water is increasingly severe, posing a serious challenge to underwater ecosystems. Effective cleaning up of underwater litter by robots relies on accurately identifying and locating the plastic waste. However, it often causes significant challenges such as noise interference, low contrast, and blurred textures in underwater optical images. A weighted fusion-based algorithm for enhancing the quality of underwater images is proposed, which combines weighted logarithmic transformations, adaptive gamma correction, improved multi-scale Retinex (MSR) algorithm, and the contrast limited adaptive histogram equalization (CLAHE)… More >

  • Open Access


    Classification of Human Protein in Multiple Cells Microscopy Images Using CNN

    Lina Al-joudi, Muhammad Arif*

    CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 1763-1780, 2023, DOI:10.32604/cmc.2023.039413

    Abstract The subcellular localization of human proteins is vital for understanding the structure of human cells. Proteins play a significant role within human cells, as many different groups of proteins are located in a specific location to perform a particular function. Understanding these functions will help in discovering many diseases and developing their treatments. The importance of imaging analysis techniques, specifically in proteomics research, is becoming more prevalent. Despite recent advances in deep learning techniques for analyzing microscopy images, classification models have faced critical challenges in achieving high performance. Most protein subcellular images have a significant class imbalance. We use oversampling… More >

  • Open Access


    Shear Localization in Polycrystalline Metal at High-Strain Rates with Dynamic Recrystallization: Crystal Plasticity Modeling and Texture Effect

    Qilin Xiong1,2,*, Wen An1,2, Chuanzhi Liu1,2

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.25, No.3, pp. 1-1, 2023, DOI:10.32604/icces.2023.010044

    Abstract Shear localization is an important failure mode, or even the dominant mode in metals at high-strain rates. However, it is a great challenge to accurately predict the occurrence and evolution of shear localization in metals at the high-strain rate deformation. Here, a dislocation-based crystal plasticity constitutive model with a crucial mechanism of shear instability, namely dynamic recrystallization, was developed. The evolution equations of dislocation density and grain size in the process of dynamic recrystallization were proposed and incorporated into the new constitutive model. The threshold of the stored energy in crystals was used as the criterion for the occurrence of… More >

Displaying 1-10 on page 1 of 125. Per Page