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检索条件"任意字段=Conference on Image Processing - Algorithms and Systems XI"

共 16408 条记录，以下是551-560 订阅

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Latest Trends on Satellite image Segmentation 5th

Latest Trends on Satellite Image Segmentation

引用

5th International conference on Communication and Intelligent systems, ICCIS 2023

作者： Borkar, Sahil Chidrawar, Krishna Naik, Sakshi Turuk, Mousami P. Vaijapurkar, Vaibhav B. SCTRs Pune Institute of Computer Technology Pune India

ISBN: (纸本)9789819720781

For the last few decades satellite imaging technology has taken massive strides towards higher spatial resolution, larger swath coverage and almost real-time data delivery. Satellite imaging or remote sensing is extensively used in optical imaging of the globe, military surveillance, deforestation detection, etc. Multispectral imaging by satellite has enabled an exceptional understanding of the earth by imaging beyond the realm of the visible spectrum. Against this backdrop image segmentation using machine learning, deep learning models and image processing has prompted several new approaches and techniques for satellite image segmentation. This survey provides a comprehensive review of the recent literature, covering the novel approaches in image segmentation using satellite imaging as well as others. There is a broad coverage of segmentation algorithms of UNET, TSVM and Random Walker. It investigates the strengths, challenges and novel aspects and compares precisions and deliberate potential research outlooks. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： image segmentation

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AI-Based Feedback Model in Supporting Mobile-Assisted Language Learning Environment 1

AI-Based Feedback Model in Supporting Mobile-Assisted Langua...

引用

1st International conference on Software, systems and Information Technology, SSITCON 2024

作者： Chen, Jingchun Xi'an Fanyi University School of English Language & Culture Shaanxi Xi'an China

ISBN: (纸本)9798350352931

The integration of Artificial Intelligence (AI) in Mobile-Assisted Language Learning (MALL) environments has revealed potential for enhancing learner writing engagement. However, research conducted on the impact of AI-based feedback models within MALL context is meager. This study investigates the effect of an AI-based writing feedback model. We constructed an AI writing feedback model by combining advanced machine learning algorithms with natural language processing techniques. 95 intermediate Chinese learners were divided into control and experimental groups. The experimental group utilized a mobile platform equipped with the AI writing feedback model. Qualitative data like learners' writing samples were collected. The findings revealed a significant increase in learner writing engagement. Learners' participation and assignment completion rates all enhanced. Findings indicate learners make more informed revisions and have a deeper understanding of grammatical structures and vocabulary usage. Furthermore, the model has the ability to analyze and highlight common errors to identify learners' struggled areas. © 2024 IEEE.

关键词： Federated learning

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Efficient feature matching algorithms applied to robust image processing 7

Efficient feature matching algorithms applied to robust imag...

引用

7th International conference on Intelligent Computing and Signal processing, ICSP 2022

作者： Chen, Kaige Ye, Ning xie, Jianhong Taiyuan University of Technology School of Mechanical and Transportation Engineering Taiyuan China Dalian Polytechnic University School of Art and Design Liaoning Dalian China Shenyang University of Technology School of Artificial Intelligence Liaoning Shenyang China

ISBN: (纸本)9781665478571

image feature matching is an essential problem in computer vision. Also, feature matching is an important task in many computer vision applications, such as in VR technology, drones, and autonomous driving. In this paper, four algorithms for matching are presented first. We perform outdoor scene feature matching experiments on four algorithms: Surf, Sift, Orb, Brisk. The original image is rotated, the sharpness is continuously blurred, the scene is transformed, specific regions are scaled, and the resolution is changed. The number of feature points that correctly matched the transformed image to the original image was compared. In this paper, the stability is determined by comparing the operation time of the four algorithms in the case of unified processing. Then, the RANSAC algorithm detects the proportion of internal and external points and compares the robustness. It is concluded that the ORB algorithm is the fastest, and the SURF algorithm is the most robust. © 2022 IEEE.

关键词： Computer vision

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Do We Still Need Non-Maximum Suppression? Accurate Confidence Estimates and Implicit Duplication Modeling with IoU-Aware Calibration

Do We Still Need Non-Maximum Suppression? Accurate Confidenc...

引用

IEEE/CVF Winter conference on Applications of Computer Vision (WACV)

作者： Gilg, Johannes Teepe, Torben Herzog, Fabian Wolters, Philipp Rigoll, Gerhard Tech Univ Munich Munich Germany

ISBN: (纸本)9798350318920;9798350318937

Object detectors are at the heart of many semi- and fully autonomous decision systems and are poised to become even more indispensable. They are, however, still lacking in accessibility and can sometimes produce unreliable predictions. Especially concerning in this regard are the-essentially hand-crafted-non-maximum suppression algorithms that lead to an obfuscated prediction process and biased confidence estimates. We show that we can eliminate classic NMS-style post-processing by using IoU-aware calibration. IoU-aware calibration is a conditional Beta calibration;this makes it parallelizable with no hyperparameters. Instead of arbitrary cutoffs or discounts, it implicitly accounts for the likelihood of each detection being a duplicate and adjusts the confidence score accordingly, resulting in empirically based precision estimates for each detection. Our extensive experiments on diverse detection architectures show that the proposed IoU-aware calibration can successfully model duplicate detections and improve calibration. Compared to the standard sequential NMS and calibration approach, our joint modeling can deliver performance gains over the best NMS-based alternative while producing consistently better-calibrated confidence predictions with less complexity. The code for all our experiments is publicly available(1).

关键词： accountable algorithms algorithms ethical computer vision Explainable fair image recognition and understanding privacy-preserving

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Deep Learning-based Early Lung Cancer Detection using Multi-Model image Fusion Technique 2

Deep Learning-based Early Lung Cancer Detection using Multi-...

引用

2nd International conference on Automation, Computing and Renewable systems, ICACRS 2023

作者： Wahengbam, Monita Sriram, M. Singh, Tonjam Gunendra Department of Computer Science and Engineering Bharath Institute of Higher Education and Research Tamil Nadu Chennai India

ISBN: (纸本)9798350340235

Lung cancer, a significant global health concern, continues to take many lives, especially as a result of late-stage diagnoses. Early detection continues to have the most significant impact on patient outcomes and mortality rates. This research examines how modern image-processing methods might transform the early diagnosis of lung cancer. To investigate the application of deep learning algorithms, computer-aided diagnosis systems, and the synergistic integration of multimodal imaging techniques to increase the accuracy and efficiency of lung cancer diagnosis. The article thoroughly examines current approaches, presents a novel framework designed for early detection, and rigorously assesses the efficacy of the suggested system using actual medical imaging data. The research has the potential to radically alter lung cancer diagnosis, encourage a new era in early intervention, and eventually help to significantly lower lung cancer mortality rates by bridging the gap between cutting-edge image processing and clinical practice. © 2023 IEEE.

关键词： Computer Aided Diagnosis Deep Learning image processing Lung Cancer Multimodal Imaging Fusion

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Dual-modal Fusion Method based on Hierarchical Frequency Domain Neural Network 12

Dual-modal Fusion Method based on Hierarchical Frequency Dom...

引用

12th International conference on Information systems and Computing Technology

作者： Xu, Guoxia He, Yue Deng, Lizhen Zhu, Hu Nanjing Univ Posts & Telecommun Sch Commun & Informat Engn Nanjing Peoples R China

ISBN: (纸本)9798350379860;9798350379877

To address the challenges of image degradation and the limitations of single-domain information, this paper proposes a fusion network that integrates both frequency-domain and spatial-domain information for infrared and visible image fusion. We begin by designing an image fusion network that combines the phase components of the visible image with its amplitude spectrum, effectively processing the high, low and mid-frequency. This method achieves the fusion of salient targets and the preservation of visual quality in the frequency domain. Additionally, an information complementarity network is introduced to address spatial domain differences. This network features an innovative compensation mechanism that addresses the texture disparities between the fused image. Furthermore, the network utilizes implicit degradation estimation during feature fusion. This approach helps the fusion model identify and optimize various potential degradation factors, thereby improving the extraction and aggregation of important content in degraded scenes. The experiment demonstrates our proposed method achieves the superior performance against other comparison methods.

关键词： image fusion Multimodal Learning Self-supervision Neural network

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Sparsity-aware Subband Adaptive Filtering in Impulsive Interferences 7

Sparsity-aware Subband Adaptive Filtering in Impulsive Inter...

引用

7th IEEE International conference on Electronic Information and Communication Technology, ICEICT 2024

作者： Gong, Zhikai Li, Yingsong Pang, Baohe Li, Xueyan xiao, Wudang Li, Liping Zlatanov, Nikola Harbin Engineering University College of Information and Communication Engineering Harbin150001 China Ministry of Education Anhui University Key Laboratory of Intelligent Computing and Signal Processing China Innopolis University Faculty of Computer and Engineering Sciences Russia

ISBN: (纸本)9798350384437

In this paper, we propose two new subband adaptive filtering (SAF) algorithms based on the cost function of the logistic distance metric cost function and use the proportionate proximal gradient algorithm to exploit the sparsity of the system fully. Compared with prior works, the proposed algorithms can handle many different situations better. Through computer simulations, we prove that the algorithm performs excellently in sparse systems disturbed by impulse noises. The algorithm can be used in areas like system identifications. © 2024 IEEE.

关键词： Adaptive filtering

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A Survey on Automated Disease Diagnosis and Classification of Herbal Plants Using Digital image processing 6

A Survey on Automated Disease Diagnosis and Classification o...

引用

6th International conference on Information systems and Computer Networks, ISCON 2023

作者： Khandelwal, Ankit Shukla, Aasheesh Sain, Mangal GLA University Electronics and Communication Dept. Mathura India Dongseo University Information Engineering Dept. Busan Korea Republic of

ISBN: (纸本)9798350346961

This paper presents a review on automated disease detection processing. The primary issue in herbal plants is the diagnosis and stratification of its diseases. The conventional process is unpredictable and inconsistent, therefore techniques for classifying plants diseases using digital method are necessary as they speed up the identification process. This literature discusses various digital methods for classifying plant diseases. The first step is image processing of herbal plants, which make use of traditional image processing techniques and algorithms to categories diseases in herbal plants based on attributes like texture, color, and shape. The second step is plant categorization based on deep learning and machine learning, such as CNN, KNN, logistic regression etc. Deep learning applications mainly lessen the reliance on designs and preprocessing techniques by joining the entire process. This review provides a basic understanding and knowledge of the current state-of-the-art researches, as well as some dynamic trends for future work.. © 2023 IEEE.

关键词： Computer vision

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ACFun: Abstract-Concrete Fusion Facial Stylization 38

ACFun: Abstract-Concrete Fusion Facial Stylization

引用

38th conference on Neural Information processing systems, NeurIPS 2024

作者： Ji, Jiapeng Wei, Kun Zhang, Ziqi Deng, Cheng School of Electronic Engineering Xidian University Xi'an710071 China

Owing to advancements in image synthesis techniques, stylization methodologies for large models have garnered remarkable outcomes. However, when it comes to processing facial images, the outcomes frequently fall short of expectations. Facial stylization is predominantly challenged by two significant hurdles. Firstly, obtaining a large dataset of high-quality stylized images is difficult. The scarcity and diversity of artistic styles make it impractical to compile comprehensive datasets for each style. Secondly, while many methods can transfer colors and strokes from style images, these elements alone cannot fully capture a specific style, which encompasses both concrete and abstract visual elements. Additionally, facial stylization often alters the visual features of the face, making it challenging to balance these changes with the need to retain facial information. To address these issues, we propose a novel method called ACFun, which uses only one style image and one facial image for facial stylization. ACFun comprises an Abstract Fusion Module (AFun) and a Concrete Fusion Module (CFun), which separately learn the abstract and concrete features of the style and face. We also design a Face and Style imagery Alignment Loss to align the style image with the face image in the latent space. Finally, we generate styled facial images from noise directly to complete the facial stylization task. Experiments show that our method outperforms others in facial stylization, producing highly artistic and visually pleasing results. © 2024 Neural information processing systems foundation. All rights reserved.

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Yaw and Pitch Steering Using a Nonlinear Least Square Approach for Spaceborne SAR systems 17

Yaw and Pitch Steering Using a Nonlinear Least Square Approa...

引用

17th IEEE International conference on Signal processing, ICSP 2024

作者： Ding, Yongfei Xu, Dinghai Li, Yu Fang, Zheng Chen, Tao Zhang, Hengyang Key Laboratory on Avionics Integration Shanghai China Airforce Engineering University Institute of Navigation and Information Xi'an China

ISBN: (纸本)9798350387384

In this paper, we investigate the attitude control algorithms for antenna steering of spaceborne Synthetic Aperture Radars (SAR). They are based on the method of Nonlinear Least Squares (NLS), which has the ability to fast calculate the attitude angles (yaw and pitch) of the satellite platform. Doppler centroid and Doppler slope versus range may both be set to zeros by satellite attitude control. Since the Least Mean Squares (LMS) type algorithm needs many iterations to converge, Newton's method may be chosen to accelerate its performance. Computer simulations demonstrate the numerical precision and computational efficiency of the proposed algorithms. As a consequence, we may apply the NLS method to the SAR yaw steering issue with good results. © 2024 IEEE.

关键词： Newton-Raphson method

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