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

共 12624 条记录，以下是91-100 订阅

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A Review on the Applications of Machine Learning and Deep Learning algorithms for image Recognition

A Review on the Applications of Machine Learning and Deep Le...

引用

Sentiment Analysis and Deep Learning (ICSADL), International conference on

作者： Ketan Wanjari Prateek Verma Department of Computer Science and Engineering Faculty of Engineering and Technology Datta Meghe Institute of Higher Education and Research (Deemed to be University) Sawangi (Meghe) Wardha Maharashtra India Department of Artificial Intelligence and Data Science Faculty of Engineering and Technology Datta Meghe Institute of Higher Education and Research (Deemed to be University) Sawangi (Meghe) Wardha Maharashtra India

ISBN: (数字)9798331523923

ISBN: (纸本)9798331523930

Modern image recognition has experienced dramatic improvements because of Machine Learning and Deep Learning algorithms together. This study investigates CNNs and SVMs for recognition enhancement while reviewing image recognition technologies extensively through literature. This paper demonstrates how the applications of healthcare and security systems and social media analysis influence society. New developments in technology have not resolved multiple unresolved obstacles such as data bias as well as computational complexity and privacy concerns together with real-time processing restrictions. The latest image processing techniques include ViTs alongside GANs and Few-Shot Learning but developers need to achieve better results in future improvements. The main goal of this research examines present-day advancements in ML and DL with a review of their capabilities as well as constraints before recommending future study paths to overcome problems encountered today. This paper evaluates both the future potential and benefits alongside drawbacks of ML and DL models applied to image recognition.

关键词： Deep learning Ethics Data privacy image recognition Machine learning algorithms Reviews Social networking (online) Vectors Security Stakeholders

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A Comparative Review on Design and Development of Automation System for Grading of Onion

A Comparative Review on Design and Development of Automation...

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AIML-Applications for Engineering & Technology (ICAET), International conference on

作者： Rahul Suryawanshi Jayesh Jagtap Dnyaneshwari Shegokar Siddhesh Jaju Chandan M. N Avinash M. Badadhe Department of Automation and Robotics JSPM's Rajarshi Shahu College of Engineering Pune India

ISBN: (数字)9798350355611

ISBN: (纸本)9798350355628

Grading of onion is important for the purpose of quality as well as market value, and it has, in the past, used traditional methods. Onion grading has thus been automated, which has been a focus of numerous researchers because of the rising need for quality produce. Thus, the findings highlighted in this work show the progress and current approaches and methodologies designed for the design and implementation of automation systems for grading onions. This work outlines various methods such as image processing, gas sensor technology, Near Infra-Red (NIR) spectroscopy, X-ray imaging, Laser Doppler Vibrometry (LDV), and some artificial intelligence approaches that have been used in improving onion sorting systems. In addition, it reveals the drawbacks of these technologies, such as the realization of high image processing, the availability of small data sets, and the stability of the sortation systems. Based on the findings of this review, some recommendations for future research are suggested, such as the integration of multi-sensor systems and the enhancement of the efficiency of the automated onion grading systems using different types of algorithms.

关键词： Automation Reviews image processing X-ray lasers Laser stability Doppler effect Gas lasers Artificial intelligence X-ray imaging Sorting

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Wavelet Analysis of Cardiograms in EDF Format

Wavelet Analysis of Cardiograms in EDF Format

引用

Digital Signal processing and its Applications (DSPA), International conference on

作者： Sinan V. Kurbanov Denis A. Andrikov Department of Mechanics and Control Processes Peoples' Friendship University of Russia (PFUR) Moscow Russian Federation

ISBN: (数字)9798331518752

ISBN: (纸本)9798331518769

The correlation of the wavelet shape and the characteristic ECG section has been confirmed, and wavelets for the identification of P-, R-, and T waves have been experimentally established. An algorithm for identifying R waves in an ECG has been developed and its operability has been verified. Using the algorithm developed, a graph of the dynamics of the heartbeat period is plotted as a function of time (period number). To identify the P and T waves, the wavelet image of the real ECG is constructed, and the presence of distortion of the shape of this image due to the influence of QRS complex and neighboring waves is established. Computer removal (filtering) of QRS complexes from the ECG is carried out, wavelet image of the remaining part is calculated. The possibility of determining the positions of the maximum P- and T-waves has been established from the wavelet image of the filtered ECG. The theoretical and practical value of this study consists in a new direction of wavelet analysis of cardiac signals, by successively applying several wavelets of a special form, to identify characteristic sections of the ECG in order to improve diagnostics. The proposed method also assumes intermediate filtering of the identified sections when moving from wavelet to wavelet. The development was carried out within the framework of computer generation of arrays of digital functions of the state of the heart, suitable for training artificial intelligence systems, and diagnostics using such systems. The practical results obtained can be applied in the development of a digital expert diagnostic system or a specific technical device.

关键词： Training Correlation Shape Heart beat Filtering Heuristic algorithms Signal processing algorithms Electrocardiography Wavelet analysis Distortion

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Robust Calibration for Enhanced Imaging in Near-Field D-Band MIMO Radar systems

Robust Calibration for Enhanced Imaging in Near-Field D-Band...

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European conference on Antennas and Propagation, EuCAP

作者： Lorena Perez-Eijo Marcos Arias Borja Gonzalez-Valdes José Vázquez-Cabo Ignacio Sardinero–Meirás Jesus Grajal AtlanTTic Research Center Universidade de Vigo Vigo Spain Information Processing and Telecommunications Center Universidad Politécnica de Madrid Madrid Spain

ISBN: (数字)9788831299107

ISBN: (纸本)9798350366327

This work introduces a calibration algorithm designed to improve high-precision imaging in real-time MIMO radar systems. The algorithm applies the Inverse Fourier Transform (IFFT) and advanced signal processing techniques to efficiently extract and process key data from raw measurements, focusing on critical Regions Of Interest (ROI) while filtering out unnecessary information. A robust phase correction mechanism ensures precise calibration and alignment, preventing phase errors that could otherwise lower image quality. The algorithm provides an effective balance between computational efficiency and the high accuracy required by modern MIMO radars, paving the way for further improvements in real-time imaging.

关键词： MIMO radar Signal processing algorithms Coherence Radar imaging Signal processing Real-time systems Hardware Calibration Spatial resolution image reconstruction

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Automatic Identification of the American Sign Language Using Machine Learning

Automatic Identification of the American Sign Language Using...

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Machine Learning and Autonomous systems (ICMLAS), International conference on

作者： Ravi Kishore Kodali Arindam Pattanayak Department of Electronics and Communication Engineering National Institute of Technology Warangal Warangal India

ISBN: (数字)9798331505745

ISBN: (纸本)9798331505752

Communication is essential, providing a means to express thoughts, emotions, and ideas. Sign language is a fundamental form of communication for those who are deaf, have hearing impairments, or are non-verbal. This research uses machine learning to develop an effective algorithm for identifying the alphabet in American Sign Language (ASL) through natural hand movements. The system combines image processing, machine learning, and artificial intelligence, especially a convolutional neural network (CNN), to translate ASL gestures into accurate and understandable output. After training the model on a dataset that includes sign language images, the results demonstrate the system's ability to identify hand gestures related to the English alphabet accurately.

关键词： Hands Training Deep learning Sign language Translation Accuracy Machine learning algorithms image processing Predictive models Convolutional neural networks

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4th International conference on Computer Science and Informatics, JCIS'98, Ist International Workshop on High Performance, Ist International Workshop on Computer Vision, Pattern Recognition and image processing, Volume 4

4th International Conference on Computer Science and Informa...

引用

4th International conference on Computer Science and Informatics, JCIS 1998, 1st International Workshop on High Performance, 1st International Workshop on Computer Vision, Pattern Recognition and image processing Volume 4

The proceedings contains 115 papers from the 4th international conference on computer science and informatics, JCIS '98 and the 1st international workshop on high performance computer vision, pattern recognition, and image processing, Volume 4. Topics discussed include: maintenance of controller software components using adaptation algorithms;construction methods of fuzzy decision trees;a comparison of wormhole routing algorithms in Cayley graphs;performance issues in multilevel secure database systems;visualizing distributed object systems;twisted cubes with fast optimal routing algorithms;multicommodity flow in networks;and a distributed connectivity algorithm for ad hoc networks.

关键词： Software engineering

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A Fast Saturation Based Dehazing Framework with Accelerated Convolution and Attention Block

A Fast Saturation Based Dehazing Framework with Accelerated ...

引用

International conference on Acoustics, Speech, and Signal processing (ICASSP)

作者： Shuocheng Wang Jiaming Liu Yilian Zhong Ruoxi Zhu Jiazheng Lian Hao Zhang Yibo Fan State Key Laboratory of Integrated Chips and Systems Fudan University

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Real-time image dehazmg is crucial for applications such as autonomous driving, surveillance, and remote sensing, where haze can significantly reduce visibility. However, many deep learning algorithms are hindered by large model sizes, making real-time processing difficult to achieve. Several fast and lightweight dehazing networks rely on estimating K(x), but they often fail to deliver satisfying performance. In this paper, we present a novel fast dehazing framework built upon the saturation-based algorithm. We design a new convolution module called Feature Extraction Partial Convolution (FEPC), which is faster and achieves better performance than the vanilla 3×3 convolution. Additionally, we fully leverage the information redundancy between feature map channels by dividing it into two parts along the channel dimension and designing a Self-Cross Attention Block (SCAB). The reduction in channel count significantly reduces computational load and improves the framework’s speed. Through extensive experiments, our method demonstrates not only a fast inference speed but also superior dehazing performance, providing a promising solution for real-time practical deployment. Our code will be available at https://***/superwscZFSB-Dehazing-Framework.

关键词： Deep learning image quality Convolution Surveillance Redundancy Signal processing algorithms Feature extraction Real-time systems Speech processing Remote sensing

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Boolean matrix compressed sensing

Boolean matrix compressed sensing

引用

International conference on Acoustics, Speech, and Signal processing (ICASSP)

作者： Qiang Liu Mahdi Soleymani Hessam Mahdavifar National Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou China Halıcıoğlu Data Science Institute University of California San Diego La Jolla CA USA Department of Electrical and Computer Engineering Northeastern University Boston MA USA

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

In real-world datasets, leveraging the low-rank and sparsity properties enables developing efficient algorithms across a diverse array of data-related tasks, including compression, compressed sensing, matrix completion, etc. Notably, these two properties often coexist in certain real-world datasets, especially in Boolean datasets and quantized real-valued datasets. To harness the advantages of low-rank and sparsity simultaneously, we adopt a technique inspired by compressed sensing and Boolean matrix completion. Our approach entails compressing a low-rank sparse Boolean matrix by performing inner product operations with a randomly generated Boolean matrix. We then propose a decoding algorithms based on message-passing techniques to recover the original matrix. Our experiments demonstrate superior recovery performance of our proposed algorithms compared to Boolean matrix completion, with equal measurement requirements.

关键词： image coding Signal processing algorithms Signal processing Acoustics Sensors Decoding Sparse matrices Speech processing Compressed sensing

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Design of AXI Bus-Based IP Core for image processing 12th

Design of AXI Bus-Based IP Core for Image Processing

引用

12th CCF conference on BigData, BigData 2024

作者： Chen, Yutong Yi, Zhongchao Li, Xuqiang Chen, Xingyan Chen, Yanjiang School of Software Engineering University of Science and Technology Hefei China School of Computer Science and Technology University of Science and Technology Hefei China

ISBN: (纸本)9789819610235

This study addresses the significant issue of image blur through image restoration techniques that reduce or remove blur and detect blurry regions, improving image quality and analysis potential. Utilizing FPGA-based digital hardware systems, the research leverages FPGA-supported systems like ZYNQ and ARM, using the Advanced eXtensible Interface (AXI) and Advanced Microcontroller Bus Architecture (AMBA) for streamlined device communication. The design incorporates specialized Intellectual Property (IP) cores such as Square Root (Sqrt) and Shift RAM, tailored to overcome the limitations of development cycles and processing algorithms, focusing on portability across various platforms including domestic FPGAs. The practical implementation features modules for axis-stream transmission, RGB to YUV conversion, image smoothing using Gaussian, mean, and median filters, advanced image processing with Sobel edge detection, and erosion-dilation modules. A ZYNQ verification system with an OV5640 camera and HDMI output substantiates the functionality and efficiency of the designed IP core, which is further analyzed for resource and power consumption using a High-Level Synthesis (HLS) tool. The study successfully demonstrates a robust IP core for blurry image processing, significantly enhancing the field of image processing and embedded systems, laying a strong groundwork for future advancements and porting endeavors, and highlighting the efficacy of FPGA-based image processing solutions. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Median filters

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A Cloud-Edge Integrated Water Extraction Using Superpixel Segmentation 18th

A Cloud-Edge Integrated Water Extraction Using Superpixel Se...

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18th International conference on Wireless Artificial Intelligent Computing systems and Applications, WASA 2024

作者： Zhang, Qingmin Chen, Chen Zhou, Yang Wang, Zhiyi Jin, Fan Lu, Haitao Wan, Shaohua School of Communication Engineering Xidian University Xi’an China Xidian Hangzhou Institute of Technology Hangzhou311231 China The State Grid Jilin Province Electric Power Company Limited Information Communication Company Changchun130000 China National Key Laboratory of Science and Technology on Space Microwave CAST Xi’an710100 China Ningbo Joynext Technology Corporation Ningbo361000 China The Shenzhen Institute for Advanced Study University of Electronic Science and Technology of China Shenzhen518110 China

ISBN: (纸本)9783031714665

With the development of the Industrial Internet of Things (IIoT) and the proposal of smart water conservancy, the integration of the Internet of Things (IoT), edge computing, and computer vision for hydrological information monitoring has become a trend in water conservancy. Difficult to provide comprehensive hydrological data from hydrological observation stations, hydrological forecasting in uninformative basins has become one of the research hotspots. water extraction can provide support for many hydrological monitoring. However, The water is difficult to extract when the water in the near-water image has reflection and water surface ripples. We propose a multi-condition water extraction method based on superpixel segmentation under cloud-edge integration architecture. Firstly, based on the color characteristics of the water and the surrounding vegetation, we propose a reflection processing mechanism. Secondly, we propose a mechanism based on superpixel segmentation for the effect of reflection on water extraction. Then, we propose a contour correction mechanism. Finally, the flood-filling algorithm is used to extract the water. We compare the traditional image segmentation algorithm with our proposed segmentation method. The results show that the proposed method outperforms other algorithms in all evaluation metrics. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： image segmentation

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