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

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VLW-Net: A Very Light-Weight Convolutional Neural Network (CNN) for Single image Dehazing 20th

VLW-Net: A Very Light-Weight Convolutional Neural Network (C...

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20th International conference on Advanced Concepts for Intelligent Vision systems, ACIVS 2020

作者： Liu, Chenguang Tao, Li Kim, Yeong-Taeg Digital Media Solutions Lab Samsung Research America 18500 Von Karman Ave. Suite 700 IrvineCA92612 United States

ISBN: (纸本)9783030406042

Camera imaging is one of the most important application areas of computer image and video processing. However, computational cost is usually the main reason preventing many state of the art image processing algorithms from being applied to practical applications including camera imaging. This paper proposes a very light-weight end-to-end CNN network (VLW-Net) for single image haze removal. We proposed a new Inception structure. By combining it with a reformulated atmospheric scattering model, our proposed network is at least 6 times more light-weight than the state-of-the-arts. We conduct the experiments on both synthesized and realistic hazy image dataset, and the results demonstrate our superior performance in terms of network size, PSNR, SSIM and the subjective image quality. Moreover, the proposed network can be seamlessly applied to underwater image enhancement, and we witness obvious improvement by comparing with the state-of-the-arts. © 2020, Springer Nature Switzerland AG.

关键词： Cameras

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Machine Learning for Medical image Analysis: A Survey 1

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International conference on Advanced Intelligent systems for Sustainable Development, AI2SD 2022

作者： Fettah, Amina Menassel, Rafik Gattal, Abdeljalil Department of Mathematics and Computer Science Echahid Cheikh Larbi Tebessi University Tebessa Algeria

ISBN: (数字)9783031352485

ISBN: (纸本)9783031352478

Machine learning techniques have made significant progress in recent years in the field of healthcare by assisting clinicians in treatment interventions, identification, detection along with the classification of a variety of diseases, including Brain Tumors, Breast Cancer, diagnosis of diabetic retinopathy, as well as, more recently in dealing with the COVID-19 pandemic and its associated medical challenges. To that end, medical image processing employs certain strategies and techniques for manipulating images, which include image acquisition, storage, presentation, and transmission. In this paper, we have overviewed several machine learning and deep learning approaches that are commonly utilized for various image processing tasks, such as image segmentation, image detection, image classification, and image compression on different medical imaging modalities, among which are computed tomography (CT), magnetic resonance imaging (MRI), and x-ray radiography. Focusing on supervised learning and deep learning techniques when applied to medical imaging analysis to enhance the performance in different medical applications using a number of algorithms such as CNNs that lead to efficient outcomes in automatic feature extraction and acceleration of the training process in the detection and classification of different diseases. The methods collected in this survey paper and the results are discussed, and the main conclusions are highlighted. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Medical imaging

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8th International conference on Advanced Computing and Communication systems, ICACCS 2022

8th International Conference on Advanced Computing and Commu...

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8th International conference on Advanced Computing and Communication systems, ICACCS 2022

ISBN: (纸本)9781665408165

The proceedings contain 399 papers. The topics discussed include: wavelet based speech enhancement algorithm for hearing aid application;a review of image processing applications based on Raspberry-Pi;pest detection in crops using deep neural networks;kitchen safety and security system for children;intrusion detection system for databases: a hybrid metaheuristic clustering and closed sequential pattern mining approach;diabetes prediction using machine learning algorithms;integration of optimization techniques to improve performance of machine learning system;role of cloud security in big data processing for healthcare system;behavioral analysis of students by integrated radial curvature and facial action coding system using DCNN;an efficient mouse tracking system using facial gestures;automatic detection of white blood cancer from blood cells using novel machine learning techniques;portable smart storage units for agricultural products;and smart access control system for covid safety smart access control system during covid.

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1st International conference on Computer Vision systems, ICVS 1999

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1st International conference on Computer Vision systems, ICVS 1999

ISBN: (纸本)3540654593

The proceedings contain 32 papers. The special focus in this conference is on Vision for Navigation and Computer Vision systems. The topics include: Integrating vision based behaviours with an autonomous robot;topological maps for visual navigation;vision-aided outdoor navigation of an autonomous horticultural vehicle;an interactive computer vision system DyPERS;using computer vision to control a reactive computer graphics character in a theater play;a language and optimizing compiler for image processing on reconfigurable computing systems;simulation and scheduling of real-time computer vision algorithms;real-time maintenance of figure-ground segmentation;an integrated framework for robust real-time 3D object tracking;face-tracking and coding for video compression;tracking people in a railway station during rush-hour;active knowledge-based scene analysis;experience in integrating image processing programs;integration of vision and decision-making in an autonomous airborne vehicle for traffic surveillance;multilevel integration of vision and speech understanding using bayesian networks;a bayesian computer vision system for modeling human interaction;automatic visual analysis and synthesis of interactive behaviour;a hierarchical vision architecture for robotic manipulation tasks;optimal image processing architecture for active vision;reactive computer vision system with reconfigurable architecture;a modular and extensible path planning system using observation;an active vision system for detection, tracking and recognition;improving 3D active visual tracking and surveillance system based on detection and tracking of moving objects using CMOS imagers.

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A High-performance Energy-efficient Hybrid Redundant MAC for Error-resilient Applications 28

A High-performance Energy-efficient Hybrid Redundant MAC for...

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28th International conference on VLSI Design (VLSID) / 14th International conference on Embedded systems

作者： Dutt, Sunil Chauhan, Anshu Bhadoriya, Rahul Nandi, Sukumar Trivedi, Gaurav Indian Inst Technol Guwahati Dept Elect & Elect Engn Gauhati India Indian Inst Technol Guwahati Dept Comp Sci & Engn Gauhati India INP ENSEEIHT Dept Elect & Signal Proc Toulouse France

ISBN: (纸本)9781479966585

In the majority of Digital Signal processing (DSP) applications, such as image, audio and video processing, the final result is interpreted by human senses;and, the fact of confined perception of human senses declines the strict restriction on accuracy. Thus, by adopting the emerging concept of approximate computing, we propose an approximate radix-2 hybrid redundant Multiply-and-Accumulate (ApproxMAC) unit which stems a novel Speed-Power-Accuracy-Area (SPAA) metrics. The Approx-MAC unit attains tremendous improvements in computational performance, energy efficiency and silicon area with a trivial degradation in the output quality. To inspect the effectiveness of the proposed approach in real-time DSP applications, we demonstrate an ApproxMAC unit embedded JPEG-E-X IP core architecture. The ApproxMAC unit with 40 approximate LSBs ensures 7.177x and 1.526x speedup, 1.594x and 4.163x energy efficiency, and 1.131x and 1.277x silicon area improvements over binary and hybrid redundant MAC units, respectively. Moreover, the ApproxMAC unit with 40 approximate LSBs decorates power-precision and delay-precision metrics by 14.71% and 32.95%, respectively.

关键词： approximation theory digital arithmetic digital signal processing chips Approx MAC unit DSP SPAA metrics approximate computing approximate radix-2 hybrid redundant multiply-and-accumulate unit digital signal processing embedded JPEG-E-X IP core architecture error-resilient applications high-performance energy-efficient hybrid redundant MAC multiply-and-accumulate operation speed-power-accuracy-area metrics Adders Approximation algorithms Approximation methods Computer architecture Digital signal processing Measurement Silicon Approximate Computing Error Resilient Application Hybrid Redundant Number System Multiply-and-Accumulate Unit Digital signal processing digital signal processing chips Digital arithmetic Approximate computing adders Desmoplakin Gene Computer Architecture Approximation method Approximation Theory MAXIMUM ACCEPTABLE CONTAMINATION Media Access Protocol Approximation algorithms Silicon Approx Energy efficiency

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Automated Anemia Detection Through Fingernail image Analysis 4

Automated Anemia Detection Through Fingernail Image Analysis

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4th International conference on Power, Energy, Control and Transmission systems, ICPECTS 2024

作者： Geetha, A. Stanley, Mini Anuradha, S. Maya, P.R. Nalini, M. Sriharipriyan, P. Sri Sairam Engineering College Department of English Chennai India Sri Sairam Engineering College Electronics and Instrumentation Engineering Chennai India

ISBN: (纸本)9798331508845

Millions of people worldwide, especially in low- and middle-income nations, suffer from anemia, a common health problem. The disease is characterized by a lack of hemoglobin or red blood cells, which can result in symptoms including weakness and exhaustion as well as serious consequences if ignored. Conventional techniques for identifying anemia usually entail intrusive blood tests, which can be expensive, time-consuming, and sometimes unavailable to a large number of people. In order to overcome these obstacles, this study uses MATLAB to provide an automated, non-invasive method for detecting anemia via fingernail image analysis. This project's main goal is to develop an effective and precise anemia screening tool by utilizing machine learning and image processing methods. The fingernail photos are taken by the system and pre-processed to improve quality and guarantee consistency. The technology uses sophisticated image processing techniques to extract pertinent elements from the fingernail photos, including texture and color characteristics that indicate hemoglobin levels. Machine learning algorithms use these traits to categorize the photos as either anemic or non-anemic. MATLAB is used because of its strong skills in machine learning and image processing. From picture capture and pre-processing to feature extraction and classification, the program streamlines the whole procedure. MATLAB's extensive toolkit makes it possible to manipulate photos effectively and has strong machine learning capabilities, which makes it the perfect platform for creating an automatic detection system. The system is guaranteed to be scalable, simple to install, and accurate through the use of MATLAB. Clinical data is used to thoroughly validate the system's functionality. The machine learning models are trained and tested using images from both non-anemic individuals and patients with clinically confirmed anemia. The system's sensitivity, specificity, and accuracy are assessed to guar

关键词： Noninvasive medical procedures

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"One-step" short-length DCT algorithms with data representation in the direct sum of the associative algebras 7th

"One-step" short-length DCT algorithms with data representat...

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7th International conference on Computer Analysis of images and Patterns, CAIP 1997

作者： Chernov, Vladimir M. Chicheva, Marina A. Image Processing Systems Institute of RAS IPSI RAS 151 Molodogvardejskaja st Samara Russia

ISBN: (纸本)3540634606

A method of synthesizing DCT fast algorithms for short lengths is proposed. The main ideas are data inclusion into a direct sum of real algebras and the transform interpretation in terms of multiplication rules in these algebras. The synthesized algorithms require less arithmetic operations than the known ones. Results of numerical experiments are given for images being coded with FAs of the DCT described in the present work. © Springer-Verlag Berlin Heidelberg 1997.

关键词： Algebra

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Mapping performance comparison of 2D SLAM algorithms based on different sensor combinations 2

Mapping performance comparison of 2D SLAM algorithms based o...

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2nd International conference on Computer Vision and Data Mining, ICVDM 2021

作者： Qu, Pengtao Su, Chen Wu, Hang Xu, Xinxi Gao, Sheng Zhao, Xiuguo Institute of Medical Support Institute of Systems Engineering Academy of Military Sciences Tianjin300161 China

Currently, some existing SLAM algorithms were widely applied in the field of mobile robots. However, most SLAM algorithms were tested either by simulation or using offline bags storing messages, which ignored other contributing factors influencing mapping including the changes of position and speed of the robot during it autonomous movement. The aim of this study is to investigate the solution of constructing more accurate map with high quality sensors based on freely available SLAM algorithms. Comparisons and analyses of three 2D SLAM algorithms (i.e. Gmapping, Hector SLAM and Cartographer) available in ROS were conducted to map different environments in our work using different sensor combinations of a LIDAR, a Stereo camera and an IMU, respectively. The research showed that the Cartographer algorithm has advantage over two other algorithms on constructing well-defined and informative environmental maps with minimal errors. Also, the LIDAR scan is more suitable than the ZED scan as the input of mapping algorithms, and the Cartographer combining the LIDAR scan, ZED odometry and IMU is the best solution to map in all combinations. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Stereo image processing

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Efficient Stereo Segment Scheduling in Peer-to-Peer 3D/Multi-view Video Streaming

Efficient Stereo Segment Scheduling in Peer-to-Peer 3D/Multi...

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11th IEEE International conference on Peer-to-Peer Computing (P2P)

作者： Ding, Yan Liu, Jiangchuan Simon Fraser Univ Sch Comp Sci Burnaby BC V5A 1S6 Canada

ISBN: (纸本)9781457701498

3D (or stereo) video has been a visually appealing and costly affordable technology. More sophisticated multi-view videos have also been demonstrated. Yet their remarkably increased data volume poses greater challenges to the conventional client/server streaming systems, which has already suffered from supporting 2D videos. The stringent multi-stream synchronization further complicate the system design. In this paper, we present an initial attempt toward efficient streaming of stereo/multi-view videos over a peer-to-peer network. We show that the inherent multi-stream nature of stereo video makes segment scheduling more difficult, which is particularly acute with the existence of multiple senders in a peer-to-peer overlay. We formulate the stereo segment scheduling problem as a Binary Quadratic Programming problem and optimally solve it using an MIQP solver. However, given the high peer dynamics and the stringent playback deadline in real-time streaming, the optimal solution is too costly to be obtained. Thus, we develop two efficient algorithms to allow peers frequently compute the scheduling. We show that one of the proposed algorithms can achieve an analytical guarantee in the worst case performance, in particular, the approximation factor is at most 3 comparing with the optimal solution. We implement the proposed algorithms and the optimal in a peer-to-peer simulating system, and show that the proposed algorithms can achieve near-optimal performance efficiently. We further implement two other scheduling algorithms that are used in popular peer-to-peer streaming systems for comparison, and extend our design to support multi-view video with view diversity and dynamics. Under different end-system and network configurations with both stereo and multi-view streaming, the simulation results demonstrate that our algorithms outperform others in terms of streaming quality, stream synchronization/smoothness and scalability.

关键词： 3D video Algorithm design and analysis Bandwidth Heuristic algorithms MIQP solver Peer to peer computing Streaming media Synchronization Three dimensional displays binary quadratic programming data volume multistream synchronization multiview video streaming network configuration peer dynamics peer-to-peer 3D peer-to-peer computing peer-to-peer network peer-to-peer overlay peer-to-peer simulating system peer-to-peer streaming system playback deadline quadratic programming real-time streaming scheduling algorithm stereo image processing stereo segment scheduling stereo streaming stereo video stream scalability stream smoothness streaming quality synchronisation video streaming

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A Novel image Captioning Approach Using CNN and MLP 1

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5th International conference on Data and Information Sciences, ICDIS 2023

作者： Sharma, Swati Tomar, Vivek Yadav, Neha Aggarwal, Mukul KIET Group of Institutions Ghaziabad India Dehradun India

ISBN: (数字)9789819969067

ISBN: (纸本)9789819969050

Computer vision and natural language processing researchers have dedicated significant time and energy to the problem of automatically creating image descriptions. In this work, we propose an artificially intelligent picture captioner built on a hybrid architecture of convolutional neural networks (CNNs) and multilayer perceptron (MLPs). This system will take photographs as input and generate captions based on those images using algorithms from convolutional neural networks (CNN), multilayer perception (MLP), recurrent neural networks (RNN). To generate a natural language caption, CNN first extracts feature from the input image, and then the MLP analyses these features. The proposed model is trained on a dataset of photos with captions by optimizing the parameters of a convolutional neural network (CNN) and a multilayer perceptron (MLP) via a hybrid of supervised learning and reinforcement learning. Our results demonstrate that the suggested model may produce captions that are on par with the best methods currently available in terms of accuracy and variety. The artificially intelligent picture captioner has potential uses in many areas, such as social networking, e-commerce, and image retrieval systems. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2024.

关键词： Recurrent neural networks

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