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检索条件"任意字段=5th International Conference on Image and Graphics"

共 12985 条记录，以下是91-100 订阅

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Investigating Time Series Clustering Algorithms for Hyper Spectral image Analysis 5th

Investigating Time Series Clustering Algorithms for Hyper Sp...

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5th international conference on Data Science, Machine Learning and Applications, ICDSMLA 2023

作者： Mahalakshmi, R. Agarwal, Trapty Kudari, Jayashree M. Mehra, Ritika School of Computer Science and Engineering Presidency University Karnataka Bengaluru India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India Karnataka Bangalore India Department of Computer Science & Engineering School of Engineering and Computing Dev Bhoomi Uttarakhand University Navgaon Manduwala Dehradun India

ISBN: (纸本)9789819780426

Time collection clustering algorithms (TSCAs) are of increasing significance within the evaluation and interpretation of hyper spectral image (HSI) facts. TSCAs are being used to become aware of spatiotemporal styles of spectral characteristics in HSI records by identifying areas of interest (ROIs) which can be associated with physical techniques and mapping the ones ROIs to clusters. One-of-a-kind clustering algorithms may be used to analyze HSI statistics and tease out diffused spatiotemporal modifications. this paper investigates the software of two exceptional TSCAs, particularly okay-method clustering and Self-Organizing Maps (SOMs) to HSI *** SOM set of rules changed into additionally capable of phase the hyperspectral facts into meaningful clusters primarily based on their spectral traits. the accuracy of the SOM results was also assessed. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Self organizing maps

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Unraveling Disease-Specific Diffusion Patterns in Human Brain Using Diffusion Tensor image Analysis 5th

Unraveling Disease-Specific Diffusion Patterns in Human Brai...

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5th international conference on Data Science, Machine Learning and Applications, ICDSMLA 2023

作者： Prajapati, Sandhya Bhagawati, Rupam Alam, Intekhab Jebakumari, S. Adlin Department of Electrical Engineering School of Engineering and Computing Dev Bhoomi Uttarakhand University Navgaon Manduwala Dehradun India School of Computer Science and Engineering Presidency University Karnataka Bengaluru India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India Karnataka Bangalore India

ISBN: (纸本)9789819780426

Diffusion tensor imaging (DTI) is a feasible approach to have a look at the structural connectivity of neuronal networks in vivo, as it presents insights into the microstructural and molecular properties of white depend fiber bundles. On this study, we used superior DTI and diffusion tensor image evaluation to analyze the unique diffusion patterns of several distinct diseases in human mind. We obtained statistics from healthful controls and cohorts of sufferers with a range of sicknesses, along with stroke, annoying mind injury, Alzheimer’s ailment, and Parkinson’s ailment, in addition to from postmortem brains of each wholesome and diseased people. Our findings emphasize the capability of the use of this technique to increase ailment-precise structural networks biomarkers for diagnosis and control of neurological illnesses. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Diffusion tensor imaging

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Twelfth international conference on graphics and image Processing, ICGIP 2020

Twelfth International Conference on Graphics and Image Proce...

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12th international conference on graphics and image Processing, ICGIP 2020

ISBN: (纸本)9781510642775

the proceedings contain 97 papers. the topics discussed include: infrared small target detection in image sequences based on temporal low-rank and sparse decomposition;detection of multicomponent distribution by electrical impedance spectroscopic tomography;using spatio-temporal hybrid features for detecting bleeding point in laparoscopic surgery;application of region disparity in passenger flow statistics;ship detection in optical sensing images based on Yolov5;simple online and real-time underwater multiple object tracking;multiple vehicles tracking in the aerial video based on fast incremental discriminative appearance learning;and robust kernel correlation filter tracker based on adaptive scale and occlusion detection.

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HySeg-Net: A Robust Interactive Hybrid Technique for image Segmentation and Classification in Hand Gesture Recognition 5th

HySeg-Net: A Robust Interactive Hybrid Technique for Image S...

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5th international conference on Advances in Information Communication Technology and Computing, AICTC 2024

作者： Narayan, Satya Gajrani, Jyoti Jain, Vinesh Kumar Jat, Dharm Singh Engineering College Ajmer Ajmer India NUST Namibia South Africa

ISBN: (纸本)9789819761050

image segmentation is helpful for a variety of tasks in many fields, including image analysis, object recognition and characterization, content-based image recovery, and foreground detection. Several models have been developed by considering spatial analysis and adjustment of skin models to continuously enhance the segmentation process. However, the field of hand image segmentation using skin identification is still controversial due to high pixel variation and particularly low human skin shading and thus, limits the performance of models. this research designs a HySeg-Net framework, by proposing marker-based Automated Maximal Similarity-Based Region Merging (AMSRM) that enhances the segmentation for recognition of foreground objects. the approach also leverages stoppage limit, region merging, and convolutional neural networks (CNN) techniques to make the framework robust for skin data belonging to different geographical regions. the proposed technique is validated on two standard datasets, namely American Sign Language and Polish Sign Language with varying backgrounds. the framework achieves significant improvements in various parameters including Probability Random Index (PRI), Global Consistent Error (GCE), Variation of Information (VOI), Mean Square Error (MSE), and subsequently peak signal-to-noise ratio (PSNR). Ablation study demonstrates that the results of HySeg-Net are better as compared to the state-of-the-art techniques. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Convolutional neural networks

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2025 5th international conference on Advanced Research in Computing: Converging Horizons: Uniting Disciplines in Computing Research through AI Innovation, ICARC 2025 - Proceedings

2025 5th International Conference on Advanced Research in Co...

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5th international conference on Advanced Research in Computing, ICARC 2025

ISBN: (纸本)9798331530983

the proceedings contain 155 papers. the topics discussed include: enhancing systematic literature reviews: evaluating the performance of LLM-based tools across key systematic literature review stages;optical observation for body angles of cricket players’ motion to identify the batting shots;enhanced approaches to kingfisher species identification using machine learning and deep learning;BAHAGAP: design and development of an image processing-based detection and monitoring system for early flood warnings in high-risk zones;model optimization for personalized health metrics analysis;a secure protocol for computer-based assessments in disrupted environments;machine learning based enhanced remote power analysis attacks;and Indian sign language alphanumeric hand gestures recognition using deep learning techniques.

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Multi-statistical Features-Based 4D Spatiotemporal Level Set Model for CTP image Segmentation 5th

Multi-statistical Features-Based 4D Spatiotemporal Level Set...

引用

5th international conference on Medical Imaging and Computer Aided Diagnosis, MICAD 2024

作者： Wang, Shuai Lin, Jixian Yu, Jinhua Wu, Guoqing School of Information Science and Technology Fudan University Shanghai China Department of Neurology Minhang Central Hospital Fudan University Shanghai China

ISBN: (纸本)9789819638628

Computed tomography perfusion (CTP) imaging is a commonly used tool for stroke diagnosis, and accurate segmentation of cerebral vessels based on CTP images is of great significance for the diagnosis and treatment of stroke patients. However, the complex tree-like structure of cerebral vessels and inhomogeneous diffusion of contrast agents during dynamic imaging pose significant challenges to manual segmentation or the establishment of supervised automatic segmentation models. this research presents a multi-statistical features-based 4D level set model (MSF-4DLSM), which requires no labeled training samples while achieving segmentation accuracy comparable to fully supervised models. First, the temporal dimension information of the CTP image is introduced into the level set through the variance map to construct a 4D level set combining temporal and spatial features. then, in the evolution term of the model, a mixed image of the fixed-point enhanced temporal variance map and the spatiotemporal mean map is used to replace the basic variance map, which improves the model’s adaptability to the uneven diffusion of contrast agents. Finally, to improve the continuity of the vessel segmentation results, we added optical flow information to the model evolution term. the proposed method was validated on 50 CTP images, and achieved an encouraging performance, with Dice, Sensitivity, Specificity, Accuracy and Jaccard of 0.90, 0.92, 0.94, 0.99 and 0.85, respectively. the results are close to those of the supervised model U-Net (Dice: 0.91, Sensitivity: 0.93;Specificity: 0.95;Accuracy: 0.99;Jaccard: 0.87). © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： image segmentation

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mL-mB LBP Fused Net: Multi-layer-Multi-block LBP image Fusion Facial Expression Recognition 5th

mL-mB LBP Fused Net: Multi-layer-Multi-block LBP Image Fusio...

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5th international conference on Electrical and Electronics Engineering, ICEEE 2024

作者： Mukhopadhyay, Moutan Ghosh, Ankush Shaw, Rabindra Nath Dey, Aniruddha Department of Computer Science & Engineering MAKAUT West Bengal Kolkata India Chandigarh University Punjab Mohali India Department of Computer Science & Engineering MSIT West Bengal Kolkata India

ISBN: (纸本)9789819791118

Facial emotion recognition (FER) systems have gained popularity due to their applications in various fields, including healthcare, cognitive science, video conferencing, and driver safety. However, recognizing facial expressions automatically from images presents challenges due to inter-person variability and the difficulty in accurately distinguishing between different emotions. the research investigates the application of a modified Local Binary Pattern (LBP) in facial emotion detection, focusing on the multilayer multi-block local binary pattern (mL-mB LBP). the process involves converting facial expression images into 3×3 identical blocks, which are then used to generate center pixels using the LBP descriptor block-wise. the final layer is partitioned into 3×3 blocks to generate central pixels. the study introduces a customized convolutional neural network (CNN)-based framework for emotion recognition, which uses the mL-mB LBP image data to accurately predict emotions. the CNN model is trained using multi-level multi-block images. the experimental study findings show that the accuracy of the CNN model is significantly improved when trained using multi-block multi-level images with all layers fused. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： image fusion

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Accurate image Registration Using Evolutionary Algorithms 5th

Accurate Image Registration Using Evolutionary Algorithms

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5th international conference on Data Science, Machine Learning and Applications, ICDSMLA 2023

作者： Gobi, N. Kumar, Ritesh Kumar, Deepak Singh, Ashutosh Kr. Karnataka Bangalore India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India Department of Mathematics Vivekananda Global University Jaipur India Department of Electronics and Communication Engineering Noida Institute of Engineering and Technology Uttar Pradesh Noida India

ISBN: (纸本)9789819780426

Photograph registration is aligning or more excellent snapshots of the same bodily object or scene;it's widely used in many regions of image processing and pc imaginative and prescient. Evolutionary algorithms are optimization algorithms stimulated with herbal choice aid and used efficiently for image registration. the principal advantage of evolutionary algorithms is their potential to remedy complex optimization tasks without relying on a given set of heuristics. Additionally, they require fewer parameters for the convergence than conventional optimization algorithms with gradient descent and might reap better accuracy with reduced computational time. Evolutionary algorithms can also deal with multiple goals simultaneously, making them suitable for photo registration packages. Genetic algorithms can deal with both simple and complex problems and can be efficiently deployed for registration responsibilities in a disbursed computing place. Evolutionary algorithms have been used efficaciously for many picture registration programs, which include medical imaging, satellite picture registration, and face reputation. their combination of high accuracy and low computational time makes them a famous desire for registration troubles inside the subject of pc vision. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Genetic algorithms

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Exploring Multi-Task Learning for Transfer Learning Based Active Learning in Medical image Segmentation 5th

Exploring Multi-Task Learning for Transfer Learning Based Ac...

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5th international conference on Data Science, Machine Learning and Applications, ICDSMLA 2023

作者： Yadav, Surjeet Kumar, Arvind Kannagi, A. Sahoo, Girija Shankar Department of Mechanical Engineering Vivekananda Global University Jaipur India Department of Biotechnology Noida Institute of Engineering and Technology Uttar Pradesh Greater Noida India Karnataka Bangalore India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India

ISBN: (纸本)9789819780426

Present methods for medical photograph segmentation have enabled clinical practitioners and researchers to apprehend and create unique interpretations ultra-modern clinical snap shots. But, there is nonetheless tons that may be stepped forward upon. Switch brand new-based energetic modern-day has been proposed to improve the accuracy cutting-edge deep today’s-based scientific photograph segmentation but the consequences are limited. Multi-project modern day, a contemporary transfer modern day, can further enhance the accuracy and robustness modern day segmentation. this research makes a specialty of exploring the efficacy contemporary multi-challenge learning, combined with switch present day based lively contemporary, in scientific image segmentation. In the long run, these research pursuits to take cutting-edge expertise associated with transfer cutting-edge based energetic latest and scientific photo segmentation and make bigger upon it to discover novel methods to improve average accuracy and robustness modern day clinical image segmentation. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Active learning

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Design of Performance Enhanced Approximate Multiplier for image Processing Applications 5th

Design of Performance Enhanced Approximate Multiplier for Im...

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5th international conference on Computing Science, Communication and Security

作者： Sivanandam, K. Sathana, R. M Kumarasamy Coll Engn Dept Elect & Commun Engn Karur Tamil Nadu India

ISBN: (纸本)9783031751691;9783031751707

Precise is most appropriate in scenarios where errors are hard to make, such processing mixed material and signs. Loose registering produces noticeable and quicker results with less power usage, especially for arithmetic circuits. this study proposes an alternative approach to utilize the packages of halfway items, based on recursive growth using blower-based rough multipliers. there are three proposed multiplier methods using four: 2 approximated blowers. Broad reproduction studies show that the proposed technique offers significant improvements in exactness, power reduction, and region reducing when compared to earlier imprecise multiplier designs. the first two multiplier setups make use of the first rough blower. Replicated and coordinated in Xilinx programming, the recommended multiplier design (1) has different area, less power, and less accuracy than the current multipliers. the recommended multiplier design (2) is reenacted and incorporated in Xilinx programming with high exactness, similar to the suggested plan (1), but at the expense of additional region and power. the recommended multiplier design (3) makes advantage of the second estimated blower. It is combined and replicated using Xilinx programming. Compared to plan (1) and design (2), it consumes less space and energy.

关键词： Approximate computing compressor multiplier Low power Computation

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