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

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Prediction of Colon Cancer using DenseNet121, CNN, and REsNET50 Machine Learning Models and using image processing Techniques

Prediction of Colon Cancer using DenseNet121, CNN, and REsNE...

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2023 International conference on Artificial Intelligence Robotics, Signal and image processing, AIRoSIP 2023

作者： Hasan, Mahadi Islam, Jahirul Ahmed, Minhaz Hasan, Md Maruf The University of Tennessee at Chattanooga Ms in Data Analytics ChattanoogaTN United States New Mexico Institute of Mining and Technology Ms in Cse SocorroNM United States Ms in Cse *** United States The University of South Dakota Department of Comuter Science VermillionSD United States

ISBN: (纸本)9798350327472

Colon cancer is a matter of great importance in the field of global health, as it stands as one of the primary contributors to mortality rates associated with cancer. The timely identification and precise prognostication of colon cancer have the potential to significantly enhance patient outcomes and diminish mortality rates. The global public health systems face a significant challenge in addressing the impact of colon cancer, which underscores the need for efficient screening and prediction techniques. Machine learning techniques present potential solutions by utilizing extensive datasets to detect intricate patterns that may be imperceptible to human observers. This study investigates the viability of employing machine learning techniques to predict colon cancer by utilizing a dataset consisting of 10,000 colonoscopy images that have been classified into two categories: cancerous and non-cancerous cases. The main aim of this study is to assess the efficacy of various machine learning algorithms, namely DenseNet-121, CNN, and ResNet50, in the prediction of colon cancer. The models' performance was comprehensively assessed in terms of their accuracy in predicting colon cancer. Among the models that were evaluated, DenseNet-121 demonstrated exceptional performance, achieving the highest accuracy of 99.6%. © 2023 IEEE.

关键词： Lung cancer

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Enhanced backscatter analysis for long-range optical tracking in deep turbulent conditions 4

Enhanced backscatter analysis for long-range optical trackin...

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conference on Laser Communication and Propagation through the Atmosphere and Oceans IV

作者： Smith, Christopher A. Belichki, Sara B. Coffaro, Joseph T. Panich, Michael G. Splitter, Landon J. Andrews, Larry C. Phillips, Ronald L. Wayne, David T. Univ Cent Florida CREOL Townes Laser Inst Coll Opt & Photon Orlando FL 32816 USA Space & Naval Warfare Syst Ctr Pacific San Diego CA USA

ISBN: (纸本)9781628417807

The usage of long-range optical systems for tracking applications encounters regions of deep turbulence throughout propagation. Such conditions lead to the inability to remain on target for a tracked object due to scintillation. To mitigate this issue, a double pass optical system is utilized as a means of tracking enhanced backscatter (EBS) and thus keeping alignment while characterizing turbulent conditions. EBS is detected through image processing algorithms that capture the returning constructive interference from the target. This paper evaluates EBS optical systems using a retro-reflector at a 1 kilometer distance in order to validate theoretical models that typify atmospheric turbulence regarding low-ground propagation. Meteorological conditions are also included in the empirical data obtained for the analysis of atmospheric conditions that contribute to non-homogenous turbulent conditions along the path.

关键词： scintillation Cn(2) enhanced backscatter image processing atmospheric turbulence

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SuperTA-Net: A Supervised Transmission-Augmented Network for image Compressive Sensing Reconstruction 6

SuperTA-Net: A Supervised Transmission-Augmented Network for...

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6th International conference on Data-Driven Optimization of Complex systems (DOCS)

作者： Zhang, Zhijie Bai, Huang Stankovic, Ljubisa Sun, Junmei Li, Xiumei Hangzhou Normal Univ Sch Informat Sci & Technol Hangzhou Peoples R China Univ Montenegro Fac Elect Engn Podgorica Montenegro

ISBN: (纸本)9798350377859;9798350377842

Compressive sensing (CS) has seen extensive use in signal processing, particularly in tasks related to image reconstruction. CS simplifies the sampling and compression procedures, but leaves the difficulty to the nolinear reconstruction. Traditional CS reconstruction algorithms are usually iterative, having a complete theoretical foundation. However, these iterative algorithms are constrained by significant computational complexity. While modern deep network-based methods can achieve high-precision reconstruction in compressed sensing (CS) with satisfactory speed, they often lack theoretical analysis and interpretability. To leverage the strengths of both types of CS methods, the deep unfolding networks (DUNs) have been developed. In this paper, a novel DUN named supervised transmission-augmented network (SuperTA-Net) is proposed. Based on the framework of our previous work PIPO-Net, the multi-channel transmission strategy is put forward to reduce the influence of critical information loss between modules and improve the reliability of data. Besides, in order to avoid the issues such as high information redundancy and high computational burden when too many channels are set, the attention based supervision scheme is presented to dynamically adjust the weight of each channel and remove the redundant information. Through experiments focused on reconstructing CS images, the proposed neural network architectures are shown to be highly effective.

关键词： Compressive sensing deep unfolding network multi-channel transmission attention based supervision alternating optimization

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Registration of infrared and visible images based on edge extraction and phase correlation approaches

Registration of infrared and visible images based on edge ex...

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4th International conference on image processing and Communications, IPC 2012

作者： Klimaszewski, Jan Kondej, Marcin Kawecki, Mariusz Putz, Barbara Institute of Automatic Control and Robotics Warsaw University of Technology ul. św. Andrzeja Boboli 8 Warsaw 02-525 Poland

ISBN: (纸本)9783642323836

The paper presents test results of several edge detectors intended to be used for multimodal image registration. It was found that application of edge detectors before running phase correlation algorithms allows achievement of good quality of registration and assure simultaneously high performance of registration necessary particularly in real time applications. Canny edge detector implemented in OpenCV and its simplification, Harris edge detector and two types of morphological edge detectors: basic and extended have been tested. It has been shown that OpenCV implementation of Canny algorithm gives best translation coefficients for IR and TV images registration. The results show that edge extraction with subsequent phase correlation is a very promising for multisensor image registration. © 2013 Springer-Verlag.

关键词： image registration

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Ballistic Examinations based on 3D Data: A Comparative Study of Probabilistic Hough Transform and Geometrical Shape Determination for Circle-Detection on Cartridge Bottoms

Ballistic Examinations based on 3D Data: A Comparative Study...

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conference on Media Watermarking, Security, and Forensics

作者： Fischer, Robert Vielhauer, Claus Hildebrandt, Mario Kiltz, Stefan Dittmann, Jana Brandenburg Univ Appl Sci Dept Informat & Media Magdeburger Str 50 D-14770 Brandenburg Germany Brandenburg Univ Appl Sci Dept Informat & Media Brandenburg Germany

ISBN: (纸本)9780819494382

The application of contact-less optical 3D sensing techniques yielding digital data for the acquisition of toolmarks on forensic ballistic specimens found at crime scenes, as well as the development of computer-aided, semi-automated firearm identification systems that are using 3D information, are currently emerging fields of research with rising importance. Traditionally, the examination of forensic ballistic specimen is done manually by highly skilled forensic experts using comparison microscopes. A partly automation of the comparison task promises examination results that are less dependent on subjective expertise and furthermore a reduction of the manual work needed. While there are some partly automated systems available they are all of proprietary nature to our current knowledge. One necessary requirement for the examination of forensic ballistic specimens is a reliable circle-detection and segmentation of cartridge bottoms. This information is later used for example for alignment and registration tasks, determination of regions of interest, and locally restricted application of complex feature-extraction algorithms. In this work we are using a Keyence VK-X 105 laser-scanning confocal microscope to acquire a very high detail topography image, a laser-intensity image, and a color image of the assessed cartridge bottoms simultaneously. The work is focused on a comparison of Hough Transform (21HT) and Geometric Shape Determination for circle-detection on cartridge bottoms using 3D as well as 2D information. We compare the pre-processing complexity, the required processing time, and the ability for a reliable detection of all desired circles. We assume that the utilization of Geometric Shape Detection can reduce the required processing time due to a less complex processing. For application of shape determination as well as for Hough Transform we expect a more reliable circle-detection when using additional 3D information. Our first experimental evaluation, using 1

关键词： Ballistics forensic science firearm identification circle-detection image processing segmentation shape determination hough transform

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On-line analysis of music conductor's two-dimensional motion

On-line analysis of music conductor's two-dimensional motion

引用

1992 IEEE International conference on Fuzzy systems - FUZZ-IEEE

作者： Bien, Zeungnam Kim, Jong-Sung

ISBN: (纸本)0780302362

The authors propose an online method for understanding a human's conducting action for a chorus or orchestra observed through a vision sensor. The vision system captured images of conducting action and extracted image coordinates of each endpoint of the baton every 1/15 second. A fuzzy-logic-based inference algorithm was then applied for the information involved in the conducting action. Complementary algorithms are also proposed for identifying first beat, static point, and dynamics of playing. Through a sequence of experiments organized around a system including an IBM PC-386, and a special-purpose vision system and sound module, the algorithm was found to faithfully follow the conductor's motion in playing a given song.

关键词： image processing

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Design of Liquid Viscosity Measurement System Using Brownian Motion

Design of Liquid Viscosity Measurement System Using Brownian...

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International conference on Electrical, Electronics and Information Engineering (ICEEIE)

作者： Zulfahmi Isnaeni Prajitno, Prawito Univ Indonesia Dept Phys Depok Indonesia Indonesian Inst Sci Res Ctr Phys Serpong Indonesia

ISBN: (纸本)9781728141602

As the development of science and technology is increasing rapidly, there is one research method that plays an important role in micro-scale measurements, namely Brownian motion. Brownian motion is a phenomenon of the random movement of several particles that can be observed under the objective lens of a microscope due to collisions between particles and surrounding liquid molecules. In this study, the author will observe how the Brownian motion method can be used to determine the liquid viscosity value through the relation between the displacement of polymer particles in various concentration of the solutions and the size of polymer particles that will be used in the observation. The Brownian motion-based system was made with the aim of creating a method of measuring the viscosity of a liquid with equipment that is easier and simpler by utilizing the minimum liquid quantity (in microliters) rather than the conventional methods such as using a viscometer where the quantity of liquid used is large (in milliliters). Measurements were made using the design of optical systems such as camera (Zeiss Axiocam 105 Color) and microscope objective lens (50x magnification). Through the optical system, the movement of particles is then recorded, and the recording image results are processed using image processing algorithms in MATLAB. By using the correlation function, the trajectory of particle movement can be traced until particle displacement data are obtained for each frame (in second). From the experiments that have been conducted using 10-40% glycerin concentrations and 1-micron particle, it shows that the measured glycerin viscosities have good accuracies with the errors no more than 10%. For the measured NaCl viscosities with the concentration variations of 0%, 50%, and 100% using 1- micron particle, it also shows that it has good accuracy with the errors no more than 7%.

关键词： viscosity Brownian motion image processing correlation function glycerin NaCl

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Various algorithms and Techniques for Traffic Density Estimation 1

Various Algorithms and Techniques for Traffic Density Estima...

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1st International conference on Computational Science and Technology, ICCST 2022

作者： Venkat, Sanjay Sarkar, Swagata Shreemadhi, B. Siri, Karanam Poorna Bavanika, M. Sri Sairam Engineering College Artificial Intelligence and Data Science Chennai India

ISBN: (纸本)9781665476553

Traffic has been a major problem in recent times. Traffic management is a must for safer and faster transportation. Automatic smart signal controlling systems respond to day-to-day world traffic densities to provide precedence and reduction in cross-road delays for travelers. According to the traffic density, the time between signals is adjusted so that the waiting time in traffic reduces. The ML model is capable of detecting accidents and immediately sends notifications or alert messages to nearby hospitals. The model tracks the GPS location of the ambulance and ensures no red signal in its pathway. Zebra crossing signals are also included, the signal timings are switched based on the crossing crowd. Automatic Smart Signal Control is a complete Machine Learning based project with some applications of IoT and Video / image processing. Implementation of the model all over the major signals and junctions provides faster and safer transportation. © 2022 IEEE.

关键词： image processing

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Smart Traffic Lights using image processing algorithms 7

Smart Traffic Lights using Image Processing Algorithms

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7th IEEE Palestinian International conference on Electrical and Computer Engineering (PICECE)

作者： Elkhatib, Mohammed M. Adwan, Alarqam I. Alsamna, Ahmed S. Abu-Hudrouss, Ammar M. Islamic Univ Elect Engn Dept Gaza Palestine

ISBN: (纸本)9781538662915

Conventional methods of traffic light systems are unable to deal with the ongoing issues surrounding congestion. The current traffic light models are not suited to tackle problems such as traffic jams, ease of access for emergency vehicles and prevention of accidents. In order to counteract these issues, we propose the 'Smart traffic light control system'. The adopted Traffic Light Controllers (TLC) in Gaza, are based on microcontroller and microprocessor. These TLCs have limitations because they use the pre-defined hardware, which is functioning according to the program that does not have the flexibility of modification on real time basis. Due to the fixed time intervals of green, orange and red signals the waiting time is more and car uses more fuel. The intended project will focus on two aspects of implementation. First and foremost, to make traffic light controlling more efficient, image processing alongside with embedded system, will be used. This system will intelligently decide when to alternate signals based on the total traffic on each road detected by cameras on each lane which will increase road capacity and traffic flow. Secondly, the minor component consists of the ability to control the traffic signals by an android application throughout the Bluetooth and wireless connection. This will be controlled by the traffic warden or police officer. The prototype of the system has been built and tested. The model is better than the current system which is limited to the Fixed Mode Traffic Light Controller. It is observed that the proposed smart Traffic Light Controller is more efficient than the conventional controller in respect of less waiting time, more distance travelled by average vehicles and efficient operation during emergency mode.

关键词： smart traffic lights embedded system Arduino applications image processing

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Automatic Switching of Electric Locomotives in Neutral Sections 5

Automatic Switching of Electric Locomotives in Neutral Secti...

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5th IEEE Annual International conference on Information Communications Technology and Society (ICTAS)

作者： Mcineka, Christopher Thembinkosi Reddy, Serendra Durban Univ Technol Dept Elect & Comp Engn Durban South Africa

ISBN: (纸本)9781728180816

A neutral section is a phase break that is used on the Transnet freight rail system to separate the single-phase supply from the 25kV three-phase overhead traction supply. The 25kV is a stepped-down voltage from an 88kV three-phase supply coming from the national grid. Electric locomotives operate only on a single-phase supply and require a separation of supplies as the trains traverse from one phase to the other;consequently, electric locomotives are required to switch off at the neutral sections. The most common automated schemes that have been implemented in switching electric locomotives are ground, on-board, and pole switching systems;one downside to these types of schemes is their relatively large investment and infrastructure costs. This paper proposes a new automated scheme that employs the use of computer vision and image processing methods. The system uses two unique markers that are externally situated along the railway tracks and used to trigger either the opening or closing of the electric locomotive vacuum circuit breakers as the trains traverse through the neutral sections. The two markers were designed in accordance with Transnet guidelines and the system employs shape detection algorithms, including a circular Hough transform (CHT), to locate the markers, and histogram of oriented gradient (HOG) for feature extraction and training of the classifier. The model has an accuracy of approximately 72%.

关键词： Neutral section Computer Vision image processing ROI Segmentation CHT HOG features classifier

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