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检索条件"任意字段=Conference on Applications of Digital Image Processing XXXIX"

共 10172 条记录，以下是21-30 订阅

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Land cover classification of satellite images using deep learning 47

Land cover classification of satellite images using deep lea...

引用

conference on applications of digital image processing XLVII

作者： Ul Hoque, Md Sami Al Mahmud Silwal, Roshan Ajami, Hanieh Nigjeh, Mandi Kargar Umbaugh, Scott E. SIUE Comp Vis & Image Proc Lab Edwardsville IL 62026 USA

ISBN: (纸本)9781510679344;9781510679351

The advent of high-resolution satellite imagery has revolutionized remote sensing applications, offering unprecedented access and detail worldwide. However, the vast volume and complexity of this data pose significant challenges for traditional classification methods, necessitating advanced computational approaches. This research leverages the OpenEarthMap dataset, an extensive and diverse collection of high-resolution earth observation imagery, to improve landcover classification accuracy using deep learning techniques. We optimize a U-Net convolutional neural network architecture by analyzing different learning rates and variations on the OpenEarthMap dataset and choose this architecture because of its previous success in semantic segmentation tasks. Through a comprehensive methodology encompassing dataset preparation, preprocessing, network parameter experimentation, and model evaluation, this research seeks to push the boundaries of current landcover classification capabilities and contribute valuable insights to the field of remote sensing. Using a Unet on 3500 OpenEarthMap images, Adam optimizer, and image variation preprocessing, we found an f-score of 0.75, consistent with visual image interpretation. Future work involving additional images, a 4x image split implementation, and other models may improve this f-score and the associated semantic segmentation.

关键词： Satellite image Urban Planning Environmental monitoring image processing Computer Vision Deep Learning Mapping Agricultural

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Universal filter array with memristive crossbar 24

Universal filter array with memristive crossbar

引用

IEEE 24th International conference on Nanotechnology (NANO)

作者： Remanan, Akhila Gopi, Anitha Aswani, A. R. James, Alex Digital Univ Kerala Sch Elect Syst & Automat Veiloor India

ISBN: (纸本)9798350386257;9798350386240

This study explores the integration of memristor crossbar as filter arrays for image processing applications exploit the various filtering techniques. Memristor crossbar arrays offer a promising platform for parallel processing and efficient implementation of filtering operations due to their dense and scalable architecture. Configuring each column in the crossbar array to act as a filter, it becomes possible to perform multiple filtering operations simultaneously on input images. This research investigates the feasibility and performance of utilizing memristor crossbar arrays as filter arrays with different filter structures and random dropouts in image processing. This analysis focusing on the potential of memristor based reconfigurable filter arrays in advancing the field of image processing.

关键词： image processing Memristor crossbar array Filters

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Linear operators for filtering digital images based on two-dimensional local spline of the fifth order 3

Linear operators for filtering digital images based on two-d...

引用

3rd International conference on Cyber Hygiene and Conflict Management in Global Information Networks, CH and CMiGIN 2024

作者： Prystavka, Pylyp Cholyshkina, Olha Dyriavko, Oleh National Aviation University Liubomyra Huzara Ave. 1 Kyiv03058 Ukraine Interregional Academy of Personnel Management Frometivska Str. 2 Kyiv03039 Ukraine

The paper explores the development and application of linear operators for filtering digital images, particularly through the use of fifth-order polynomial splines. The authors emphasize the importance of high-quality, high-speed image processing in enhancing cybersecurity systems, which require accurate and real-time data analysis for applications such as military intelligence and UAV navigation. They propose using B-splines, which offer precise approximation capabilities while maintaining computational efficiency. The paper outlines a method for representing these splines in a manner that reduces computational complexity, making them suitable for real-time processing in environments with high data throughput demands. The research highlights the advantages of using wider window filters and linear operators to maintain image accuracy and fidelity. It demonstrates how these techniques can be effectively applied to a range of signal processing tasks beyond image filtering, including audio and telecommunications. The experimental results presented in the paper indicate that the proposed filters significantly improve the detection and accuracy of special points in digital images, which is crucial for UAV navigation and other critical applications. The authors conclude that the use of these advanced filtering techniques can lead to more efficient and sophisticated image processing systems, with potential applications across various fields. In addition to the practical applications, the paper also discusses the theoretical underpinnings of splinebased filters, including the derivation of low- and high-frequency filter masks. The authors propose that these filters can be used to perform both sub-band filtering and multi-scale analysis of digital images, leading to improved data processing and analysis capabilities. The research contributes to the ongoing development of efficient image processing techniques that are essential for modern technology and various real-time appl

关键词： Wiener filtering

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Complex-Domain FIR Filter Design for Signal processing applications 22

Complex-Domain FIR Filter Design for Signal Processing Appli...

引用

IEEE 22nd Mediterranean Electrotechnical conference (MELECON)

作者： Mandavi, Mojtaba Ericsson Dept Device Platform Res Ericsson Res Lund Sweden

ISBN: (数字)9798350387025

ISBN: (纸本)9798350387032;9798350387025

The finite impulse response (FIR) filters play a vital role in a wide range of applications including audio, image, and video processing as well as wireless communication systems. Due to the high computational complexity and memory requirement, designing an efficient and high performance FIR filter is challenging, especially for high-order filters. This paper introduces a new approach for implementation of high-throughput, fully-parallel, and reconfigurable FIR filters through the utilization of processing-in-memory (PIM) technique. Within this framework, the filter coefficients are programmed into memristive devices, which can perform the essential multiply-accumulate operations. This innovative method not only enhances processing efficiency but also underscores the flexibility achieved by leveraging the unique capabilities of PIM in programming filter coefficients within memristors. Moreover, the proposed scheme supports arbitrary filter frequency responses and filter lengths.

关键词： Finite Impulse Response (FIR) Filter digital Signal processing (DSP) Wireless Communication Systems processing In Memory (PIM) image processing Memristive Devices

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Heliumspeech Unscrambling Method Based on Spectrogram Lexicon Learning

Heliumspeech Unscrambling Method Based on Spectrogram Lexico...

引用

9th International conference on Signal and image processing (ICSIP)

作者： Zhu, Heng Zhou, Jinghan Zhang, Shibing Shanghai Sipo Polytech Digital Informat Coll Shanghai Peoples R China Nantong Univ Sch Elect & Informat Nantong Peoples R China

ISBN: (纸本)9798350350920

In order to unscramble heliumspeech effectively, a novel heliumspeech unscrambling method is proposed, which consists of correction network and unscrambling network. First, a common working language lexicon is established and used to generate supervision signals and vector signals of the correction network. The correction network learns the spectrogram features of heliumspeech as well as normal speech from the supervision signals and vector signals to obtain the correction network parameters. Then, the correction network parameter set with the largest spectrogram fitness is used to correct heliumspeech, according to which, the vector signals and supervision signals are generated. Finally, the unscrambling network unscramble the corrected heliumspeech. Therefore, the individual spectrogram features of the heliumspeech signal of divers in different environments are fully used to improve the learning efficiency of the machine learning networks. Simulation results show that the method proposed is effective.

关键词： saturation diving heliumspeech unscrambling machine learning spectrogram

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Wavelet Knowledge Distillation for Efficient Stain Normalization in digital Histopathology 32

Wavelet Knowledge Distillation for Efficient Stain Normaliza...

引用

32nd IEEE Signal processing and Communications applications conference (SIU)

作者： Keklik, Sefa Ekinci, Murat Kablan, Elif Baykal Karadeniz Tech Univ Bilgisayar Muhendisligi Bolumu Trabzon Turkiye Karadeniz Tech Univ Yazilim Muhendisligi Bolumu Trabzon Turkiye

ISBN: (纸本)9798350388978;9798350388961

In digital histopathology, color standardization, known as stain normalization, is widely used in computer-aided diagnosis (CAD) systems. This study details the adaptation and implementation of the Wavelet Knowledge Distillation (WKD) method to CAD systems. The proposed method focuses on knowledge transfer between the teacher and student models within a specially designed Pix2Pix Generative Adversarial Network (GAN) for stain normalization in histopathology images. The student model, guided by the knowledge transferred by the teacher model using wavelet-based feature extraction, significantly improves the accuracy of stain normalization, which is crucial for preserving histological details and image quality. The WKD method has demonstrated high performance on the publicly available paired MITOS-ATYPIA dataset, outperforming state-of-the-art methods. Using the same settings, the Teacher model achieved a PSNR of 25.559, SSIM of 0.934, and RMSE of 7.270. Additionally, the student model used in the method yielded better results in the Frechet Inception *** (FID) metric compared to the teacher and baseline models.

关键词： wavelet knowledge distillation stain normalization digital histopathology generative adversarial network pix2pix

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Comparison of performance of two deep learning models for classification of skin lesions using image resampling technique for data augmentation 47

Comparison of performance of two deep learning models for cl...

引用

conference on applications of digital image processing XLVII

作者： Al Mahmud Ajami, Hanieh Ul Hoque, Md Sami Silwal, Roshan Nigjeh, Mandi Kargar Umbaugh, Scott E. SIUE Comp Vis & Image Proc Lab Edwardsville IL 62026 USA

ISBN: (纸本)9781510679344;9781510679351

This paper introduces an automated system comparing VGG16 and ResNet50 for dermatoscopic image processing and classification. This method utilized transfer learning and fine-tuning VGG16 and ResNet50 using the HAM10000 dataset. Random resampling balanced the dataset, optimizing models for accurate results with limited resources. We preprocessed images, performed data augmentation, modified the pre-existing models, and tuned the hyperparameters to increase the overall accuracy of both the models. Results demonstrate VGG16 and ResNet50 achieving 93.45% and 94.69% accuracy, respectively, showcasing the effectiveness of the proposed system in advancing early skin cancer intervention with deep learning techniques. Time comparison shows that VGG16 is 4 times faster than the other indicating the time-complexity of ResNet50 when skin lesion images are used for training.

关键词： Deep Learning skin lesion VGG16 ResNet50 transfer learning

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Utilizing Various Filtering Methodologies in digital image processing

Utilizing Various Filtering Methodologies in Digital Image P...

引用

2024 International conference on Electrical, Electronics and Computing Technologies, ICEECT 2024

作者： Singh, Harshdeep Kaur, Sarabpreet Sharma, Preeti Chitkara University Institute of Engineering & Technology Punjab Punjab India CGC Chandigarh Engineering College Punjab India

ISBN: (纸本)9798350378092

The development of efficient noise reduction techniques is imperative to maintain the quality and features of digital images, as they are essential in numerous key applications. Specifically, noise from salt and pepper can severely deteriorate the quality of digital images;the impact varies depending on the size and noise ratio of the image. The problem of image smoothing with edge preservation using Gaussian, mean, and median filters is addressed in this suggested work. For applications including computer vision, surveillance, and medical imaging, it seeks to preserve image structure while lowering noise. The results show that the Mean, Median, and Gaussian filters may be effectively compared for different smoothing applications, as indicated by the desirable peak signal to noise ratios (PSNR). © 2024 IEEE.

关键词： Salt and pepper noise

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Wavelet-Based Loss Function for image Denoising by Neural Networks 26

Wavelet-Based Loss Function for Image Denoising by Neural Ne...

引用

26th International conference on digital Signal processing and its applications, DSPA 2024

作者： Alimagadov, Kurban Umnyashkin, Sergei National Research University of Electronic Technology Higher Mathematics № 1 Moscow Russia

ISBN: (纸本)9798350361728

image processing related to noise suppression may entail partial distortion of useful visual information caused by filtering. Preservation of contours and texture details in the process of image denoising is one of the important problems of computer vision. Recent years deep neural networks are widely applied in the tasks of noise suppression and signal recovering. However, neural networks are subjects to spectral bias towards low-frequency components. It results in blurring of contours and local high-frequency details after filtration. We propose loss function based on using high-frequency information of wavelet representation of images during network training to solve the problem. Our experiments demonstrate that this approach improves results of filtration in terms of signal to noise ratio and structural similarity index. © 2024 IEEE.

关键词： image denoising

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Face Recognition Implementation Based on image processing Techniques 2

Face Recognition Implementation Based on Image Processing Te...

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2nd International conference on Signal processing and Intelligent Computing, SPIC 2024

作者： Yang, Bingcan Chen, Xiai Shenyang Ligong University School of Automation and Electrical Engineering Shenyang China Chinese Academy of Sciences Shenyang Institute of Automation Shenyang China

ISBN: (纸本)9798350368888

image processing is a technique that involves the manipulation and enhancement of digital images. It encompasses various aspects such as image acquisition, image preprocessing, image enhancement, image segmentation, feature extraction, and object detection. The purpose of image processing is to process and enhance images using computer technology, aiming to achieve higher image quality for subsequent processing and applications. In practical applications, image processing techniques employ different algorithms and methods to achieve various processing and enhancement effects. Additionally, image processing techniques can be applied in fields such as medicine, security, autonomous driving, VR/AR, etc. For instance, in the medical field, image processing techniques can be utilized for image segmentation and diagnosis of medical images, thereby improving the accuracy and analytical capabilities of medical imaging. In the security field, image processing techniques can be employed for tasks such as video surveillance and facial recognition, enhancing the efficiency and accuracy of security monitoring. In the domain of autonomous driving, image processing techniques can be used for detecting and recognizing the surrounding environment of vehicles, thereby enhancing the safety and performance of autonomous driving systems. In conclusion, image processing technology is a very important technology. By continuously improving the accuracy and reliability of the algorithm, it is expected to be applied in a wider range of applications. © 2024 IEEE.

关键词： MATLAB

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