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检索条件"任意字段=17th Image Processing: Algorithms and Systems Conference, IPAS 2019"

共 249 条记录，以下是11-20 订阅

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Automatic regions detection in CT images based on Haralick textures 17

Automatic regions detection in CT images based on Haralick t...

引用

17th Iberian conference on Information systems and Technologies (CISTI)

作者： Caridade, Cristina M. R. Almeida, Duarte Rodrigues, Simao ISEC Polytech Coimbra Coimbra Portugal ISEC Appl Biomech Lab CICGE Res Ctr Geospatial Sci Coimbra Portugal

ISBN: (纸本)9789893334362

the identification of anomalies (such as bone fractures or tendonitis in muscles and soft tissues) through image processing and analysis techniques in Computed Tomography (CT) images is today of great importance to assist doctors and health professionals in making accurate diagnoses. the extraction of relevant information from the CT image is characterized by the calculation of gray level input image attributes. Statistical moments (SM) are calculated using the gray level distribution of an image and are therefore generally calculated from that image's histogram. these characteristics provide a statistical description of the relationship between different gray levels in the CT image. Haralick proposed a methodology for describing textures based on second order statistics, where characteristics are derived from co-occurrence matrices, which are constructed by counting different combinations of gray levels in an image according to certain directions. In this work, it is intended to automatically identify and extract regions in CT images based on textures as an aid for a quick and accurate diagnosis. CT images are first pre-processed for noise reduction and image enhancement, followed by the application of Haralick textures to segment and detect zones of interest. Classifiers trained on the Haralick invariant features showed good accuracy and performance. Despite the presence of low contrast and noise in some images, the proposed algorithms present promising results in the segmentation and automatic identification of regions of tomographic images, being an important contribution to support health professionals in the characterization of anomalies and their extension. Good results are expected for the next step of this work in the detection and segmentation of anomalies in CT images.

关键词： Digital image processing image segmentation Haralick textures

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Heterogeneous FPGA-based System for Real-Time Drowsiness Detection 17

Heterogeneous FPGA-based System for Real-Time Drowsiness Det...

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17th conference on Ph.D Research in Microelectronics and Electronics (PRIME)

作者： Migali, Andrea Spagnolo, Fanny Corsonello, Pasquale Univ Calabria Dept Informat Modeling Elect & Syst Engn I-87036 Arcavacata Di Rende Italy

ISBN: (纸本)9781665467001

Drowsiness detection is a key feature in modern Advanced Driver Assistance systems (ADAS). State-of-the-art approaches rely on machine learning techniques and neural networks to monitor unusual movements of the head and eyes activities. Unfortunately, due to their computationally intensive operations, integrating such algorithms in real-time and low-power operating scenarios, like automotive applications, is still quite challenging. this paper proposes an efficient hardware architecture for real-time drowsiness detection based on monitoring the driver's eye blinking behaviour through the PERcentage of eye CLOSure (PERCLOS) metric. Experimental results obtained on the Xilinx Zynq XC7Z020 FPGA SoC show that the proposed system is up to 33.3 times faster and 2.6 times less area consuming than state-of-the-art competitors.

关键词： Drowsiness detection ADAS real-time image processing FPGA

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Development of a Procedure for Improving the Effectiveness of Personal Identification systems Based on the Analysis of Facial images 17

Development of a Procedure for Improving the Effectiveness o...

引用

17th International Scientific and Technical conference on Dynamics of systems, Mechanisms and Machines, Dynamics 2023

作者： Tatarkanov, A.A. Umyskov, A.A. Kuklin, V. Zh. Institute of Design and Technology Informatics of RAS Moscow Russia

ISBN: (纸本)9798350358315

this research aims to develop a new procedure to improve the performance of the personal identification system. this process will be based on the analysis of digital facial images using special artificial intelligence technologies. Additionally, it is emphasized that the successful development of a completely new neural network algorithm for personality identification and its special robust modification are required to achieve this goal. Furthermore, it is essential that this algorithm demonstrates increased effectiveness in identifying faces. As part of this algorithm, two key components are distinguished, namely, an algorithm aimed at determining the area where a face is located in an image, which involves the use of a standard version of a convolutional neural network. And the presented neural network algorithm is the second component, which is designed for personal identification with a specific robust modification. the studies presented have shown that an algorithm with a proposed architecture, will have around 25 times less weight parameters than the algorithms utilized at present. Also, unlike other algorithms, it was possible to improve the level of accuracy. © 2023 IEEE.

关键词： image enhancement

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An Adaptive BSCO Algorithm of Solid Color Optimization for 3D Reconstruction System with PIFuHD 17th

An Adaptive BSCO Algorithm of Solid Color Optimization for 3...

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17th International conference on Wireless algorithms, systems, and Applications (WASA)

作者： Hsieh, Chao-Hsien Song, Yubo Wang, Zhen Li, Changfeng Qufu Normal Univ Jining 273165 Shandong Peoples R China

ISBN: (纸本)9783031192135;9783031192142

PIFuHD can generate high-resolution model in the process of human 3D reconstruction. However, PIFuHD will produce debris outside the human body when the image background is more complex. In order to solve this problem, this paper develops an adaptive BSCO algorithm for the background of human body and image of human body in 3D reconstruction system. the BSCO algorithm is divided into four steps in processing. First, BSCO algorithm uses Go-selfies to separate the background. Second, BSCO algorithm converges the RGB of all pixels of the character into a set. third, BSCO algorithm finds the greatest difference from the set through HSV conversion. Fourth, BSCO algorithm weighs the set and then calculates the RGB score. the highest score of RGB is used as the RGB of the background after solid color optimization. the experimental results show that the proposed method improves the reconstruction effect of PIFuHD.

关键词： PIFuHD 3D reconstruction image processing Background adaptive

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ResRnnNet: Learning to Reconstruct the 3D Room Layout from a Single RGB Panorama 17th

ResRnnNet: Learning to Reconstruct the 3D Room Layout from a...

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17th International conference on Intelligent Information Hiding and Multimedia Signal processing (IIH-MSP) / 14th International conference on Frontiers of Information Technology, Applications and Tools (FITAT)

作者： Zhao, Shaonan Li, Wei Univ New South Wales Sch Civil Engn & Environm Sydney NSW 2052 Australia Harbin Engn Univ Coll Comp Sci & Technol Harbin 150001 Peoples R China

ISBN: (纸本)9789811910579;9789811910562

3D room layout reconstruction from a single RGB panoramic image has been an emerging research topic in recent years. To achieve better prediction accuracy, in this paper, we propose a new approach to predict 3D room layout from a single panoramic image. Our reconstruction flow follows a common framework which is same as LayoutNet [9] and HorizonNet [4];however, we redesign a new deep learning architecture with recurrent neural networks (RNNs) encoder-decoder as an extension for keypoints refinement and use a gradient ascent optimization algorithm to minimize the similar loss. Experiments on both cuboid-shaped and general Manhattan layouts show that the proposed work outperforms recent algorithms in prediction accuracy.

关键词： 3D room layout Deep learning Manhattan world Panorama image

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Simple Linear Iterative Clustering with Efficiency 1

引用

作者： Liao, Nannan Liu, Hui Li, Cheng Ren, Xia Guo, Baolong Xidian Univ Inst Intelligent Control & Image Engn Xian Peoples R China

ISBN: (数字)9789811910579

ISBN: (纸本)9789811910579;9789811910562

As an instructive work to generate satisfactory superpixels, simple linear iterative clustering (SLIC), has become fundamental and popular in various computer vision tasks. In this work, the algorithm is reconsidered, and an integrated framework is proposed to further improve the running speed and segmentation performance. In the first stage, a fast convergence strategy for clustering is presented on SLIC to redistribute the seeds efficiently. this is done to initialize a set of clustering centers that is fairly representative of local information on the image plane. then, a followup work of SLIC termed simple non-iterative clustering (SNIC) is utilized to process more accurate segmentation without any post-processing to enforce connectivity. Experimental results show that the framework could generate a synergetic effect and performs better than previous superpixel algorithms in a limited computational time.

关键词： Clustering Initialization Redistribution Superpixels

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RGB image Guided Depth Hole-Filling Using Bidirectional Attention Mechanism 1

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作者： Chen, Anran Zhao, Yao Lin, Chunyu Beijing Jiaotong Univ Inst Informat Sci Beijing Key Lab Adv Informat Sci & Network Beijing 100044 Peoples R China

ISBN: (数字)9789811910531

ISBN: (纸本)9789811910531;9789811910524

Depth maps obtained by commercial depth sensors are more likely to have missing values due to the occlusion effect, low-reflection objects, etc. Filling holes of depth maps is an important way to meet the demands of depth related computer vision tasks. In this paper, we propose an efficient end-to-end network that takes RGB image and mask of the hole to jointly guide the depth hole-filling. Previous algorithms indistinguishably treat valid pixels and holes, resulting in inaccurate depth values prediction and blurred boundaries. Nevertheless, the proposed algorithm uses the bidirectional attention mechanism which takes the surrounding valid values as the auxiliary information to focus on the process of depth hole-filling from edge to center. the proposed method achieves competitive performance on existing public datasets.

关键词： Bidirectional attention mechanism Depth map Hole-filling RGB guided

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Analysis of Decision Tree and Random Forest algorithms for Nutrient Deficiency Classification in Citrus Leaves through image processing

Analysis of Decision Tree and Random Forest Algorithms for N...

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International conference on Telecommunication systems, Services, and Applications (TSSA)

作者： Lia Kamelia Rin Rin Nurmalasari Electrical Engineering Department UIN Sunan Gunung Djati Bandung Bandung Indonesia

the research presents a hybrid approach to identify and categorise nutritional deficiency syndrome in citrus leaves using image processing and machine learning. the method includes processing images, segmenting images and extracting color-texture information. the Decision Tree and the Random Forest algorithms use various statistical measures for classification, including mean, skewness, variance, entropy, maximum probability, angular second moment, contrast, correlation, dissimilarity, energy, and homogeneity. the test results show a range of performance levels, with an accuracy of 80.28% being attained by utilising an 80:20 data ratio in the Decision Tree approach. the Random Forest method’s highest accuracy, 91.25%, was reached using an 80:20 ratio. In conclusion, the accuracy of the Random Forest approach regularly beats that of the Decision Tree method.

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17th Asian conference on Intelligent Information and Database systems, ACIIDS 2025

17th Asian Conference on Intelligent Information and Databas...

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17th Asian conference on Intelligent Information and Database systems, ACIIDS 2025

ISBN: (纸本)9789819660049

the proceedings contain 29 papers. the special focus in this conference is on Intelligent Information and Database systems. the topics include: GAMER-Pong: Game Adjustment by Monitoring Emotional Response;Machine Learning algorithms Comparison for Hand sEMG-Recorded Movements Classification;boosting Face Super-Resolution and Identification with Knowledge Distillation and Frequency Domain Loss;improving Efficiency image Captioning by Using Attention Mechanism Combined with Knowledge Graph;integrating Topological Data Analysis and Deep Learning: A Case Study in Cardiovascular Disease Prediction at thu Duc Hospital;boosting Lightweight Multi-branch Network by Integrating Segment, Skeleton, and Attribute Information;continuous Recognition of Mouth Patterns in Japanese Sign Language for Visual Communication;Towards an UAV Visual Navigation System Based on Map processing and Spatial Matching Techniques: A Literature Review;image Enhancement with Boosted Schrödinger Bridge;kernel-Level Energy-Efficient Neural Architecture Search for Tabular Dataset;estimation of Distribution algorithms with Overlapped Subpopulations;energy-Efficient Edge Query processing for Smart City Using Query Prediction;influence Maximization with Fairness Cost on Groups in Online Social Networks;TMMP: Efficient Continual Learning via Mixture of LoRA Experts and Top Maximum Magnitude Parameter Fusion;ADMEdge: Accelerating Edge Computing through Co-design for Enhanced Data Mobility;the Recursive Scheme of Clustering;TOPSIS-Inspired Socio-cognitive Mutation Operator for Metaheuristics;feature-Based Drift Detection in Non-stationary Data Streams Using Multiple Classifiers: A Comprehensive Analysis;a Feature Transformation Technique for Improving Ensemble Learning systems;explainable Artificial Intelligence to Improve Interpretability in Predictive Mutation Testing;an Analysis of Class Imbalance Challenges in Predictive Mutation Testing;efficient Vietnamese Name Detection Using Highly Discriminative N-Gra

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17th Asian conference on Intelligent Information and Database systems, ACIIDS 2025

17th Asian Conference on Intelligent Information and Databas...

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17th Asian conference on Intelligent Information and Database systems, ACIIDS 2025

ISBN: (纸本)9789819660070

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