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检索条件"任意字段=18th Image Processing: Algorithms and Systems Conference, IPAS 2020"

共 258 条记录，以下是41-50 订阅

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Optimizing 3D object detection for embedded systems in automated vehicles using sensor data fusion and CUDA computing 18

Optimizing 3D object detection for embedded systems in autom...

引用

IEEE 18th International conference on Intelligent Computer Communication and processing (ICCP)

作者： Miekkala, Topi Kutila, Matti Schneider, Mathias Hoess, Alfred VTT Techincal Res Ctr Finland Ltd Tampere Finland Tech Univ Appl Sci Amberg Weiden Germany

ISBN: (纸本)9781665464376

this article explores the utilization of the processing power of GPUs using CUDA computation for real-time aggregation of multi-sensor data and detection of 3D objects using parallel clustering algorithms. the purpose is to implement an algorithm that fuses raw lidar point cloud data and 2D camera image object detections to produce 3D object clusters in a lidar point cloud. Most of the computation has been implemented using CUDA parallelism to investigate the capability of GPU devices in this task, which is a common challenge in automated driving. the results indicate that processing times can be optimized within the algorithm, which is crucial when considering the large amounts of data provided by lidar and camera-based systems. the algorithm can perform inference on the Jetson Xavier AGX at rates of similar to 20 to similar to 220 ms depending on the number of objects and their corresponding point amounts in the KITTI dataset.

关键词： 3D object detection CUDA sensor data fusion automated driving

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Pathology image-based lung cancer subtyping using deep-learning features and cell-density maps 18

Pathology image-based lung cancer subtyping using deep-learn...

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18th image processing: algorithms and systems conference, ipas 2020

作者： Jaber, Mustafa I. Szeto, Christopher W. Song, Bing Beziaeva, Liudmila Benz, Stephen C. Soon-Shiong, Patrick Rabizadeh, Shahrooz NantOmics LLC. Culver CityCA United States ImmunityBio Santa CruzCA United States ImmunityBio Culver CityCA United States NantHealth Culver CityCA United States

In this paper, we propose a patch-based system to classify non-small cell lung cancer (NSCLC) diagnostic whole slide images (WSIs) into two major histopathological subtypes: adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC). Classifying patients accurately is important for prognosis and therapy decisions. the proposed system was trained and tested on 876 subtyped NSCLC gigapixel-resolution diagnostic WSIs from 805 patients – 664 in the training set and 141 in the test set. the algorithm has modules for: 1) auto-generated tumor/non-tumor masking using a trained residual neural network (ResNet34), 2) cell-density map generation (based on color deconvolution, local drain segmentation, and watershed transformation), 3) patch-level feature extraction using a pre-trained ResNet34, 4) a tower of linear SVMs for different cell ranges, and 5) a majority voting module for aggregating subtype predictions in unseen testing WSIs. the proposed system was trained and tested on several WSI magnifications ranging from x4 to x40 with a best ROC AUC of 0.95 and an accuracy of 0.86 in test samples. this fully-automated histopathology subtyping method outperforms similar published state-of-the-art methods for diagnostic WSIs. © 2020, Society for Imaging Science and Technology

关键词： Cytology

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Number Recognition of Parts Book Schematics using Convolutional Recurrent Neural Network 18

Number Recognition of Parts Book Schematics using Convolutio...

引用

18th International conference on Control, Automation and systems (ICCAS)

作者： Genc, Erdal Shin, Hee Ran Park, Jang Sik Kyunsung Univ Dept Elect & Elect Engn 48434 309 Suyeong Ro Busan South Korea

ISBN: (纸本)9788993215151

OCR (Optical Character Recognition) has been becoming a vital method to recognize digits, letters, symbols and so on. the main idea is basically the conversion of data files which consists of handwritten or machine-written digits or characters into a type to let the machine make edits and read. this way, it lets computers read articles or books. they can also read images and make the conversion to a text file by using OCR. there are two important benefits of OCR. First, is the enhancement of the device to operate more productively even if the number of employees is decreased. Secondly, is the increase in the efficiency of the storage. this paper compares two state-of-the-art OCR algorithms in a simulated environment by using modified dataset. Simulation results are shown in part 4.

关键词： OCR MLP Deep Learning Computer Vision RNN LSTM image processing

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An active contour model for medical image segmentation using a quaternion framework 18

An active contour model for medical image segmentation using...

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18th image processing: algorithms and systems conference, ipas 2020

作者： Voronin, V. Zhdanova, M. Semenishchev, E. Zelensky, A. Agaian, S. Moscow State University of Technology "STANKIN" Moscow Russia Don State Technical University Lab. «Mathematical methods of image processing and computer vision Intelligent Systems» Gagarina 1 Rostov on Don Russia CUNY/ College of Staten Island Dept. of Computer Science New York United States

this paper presents a new method for segmenting medical images is based on Hamiltonian quaternions and the associative algebra, method of the active contour model and LPA-ICI (local polynomial approximation - the intersection of confidence intervals) anisotropic gradient. Since for segmentation tasks, the image is usually converted to grayscale, this leads to the loss of important information about color, saturation, and other important information associated color. To solve this problem, we use the quaternion framework to represent a color image to consider all three channels simultaneously when segmenting the RGB image. As a method of noise reduction, adaptive filtering based on local polynomial estimates using the ICI rule is used. the presented new approach allows obtaining clearer and more detailed boundaries of objects of interest. the experiments performed on real medical images (Z-line detection) show that our segmentation method of more efficient compared with the current state-of-art methods. © 2020, Society for Imaging Science and Technology

关键词： Adaptive filtering

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2024 18th International conference on Open Source systems and Technologies, ICOSST 2024 - Proceedings

2024 18th International Conference on Open Source Systems an...

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18th International conference on Open Source systems and Technologies, ICOSST 2024

ISBN: (纸本)9798331508692

the proceedings contain 23 papers. the topics discussed include: solar powered auto irrigation monitoring system with plant health indication using image processing;large language model and artificial intelligence based human conversation agent;to enhance graph-based retrieval-augmented generation (RAG) with robust retrieval techniques;automatic timetable generation using neural networks trained by genetic algorithms;assessment of efficient and cost-effective vehicle detection in foggy weather;enhanced detection and prevention of SQL injection and cross-site scripting attacks in web applications: analyzing algorithms and threat modeling approaches;efficient duplicate question detection;and a comprehensive survey on computing services to detect stress and anxiety using smart devices.

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A Feature-Based Approach For Group-Wise Grid Map Registration 18

A Feature-Based Approach For Group-Wise Grid Map Registratio...

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18th IEEE International conference on Intelligent Transportation systems

作者： Rapp, Matthias Giese, Tilmann Hahn, Markus Dickmann, Juergen Dietmayer, Klaus Univ Ulm Inst Measurement Control & Microtechnol D-89069 Ulm Germany Daimler AG Ulm Germany

ISBN: (纸本)9781467365963

For autonomous vehicles and advanced driver assistance systems, information on the actual state of the environment is fundamental for localization and mapping tasks. Localization benefits from multiple observations of the same location at different times as these may provide important information on static and mobile objects. For efficient mapping, the environment may be explored in parallel. For these purposes, multiple observations represented by grid maps have to be aligned into one mutual frame. this paper addresses the problem of group-wise grid map registration using an image processing approach. For registration, a rotational-invariant descriptor is proposed in order to provide the correspondences of points of interest in radar-based occupancy grid maps. As pairwise registration of multiple grid maps suffers from bias, this paper proposes a graph-based approach for robust registration of multiple grid maps. this will facilitate highly accurate range sensor maps for the aforementioned purposes. Large-scale experiments show the benefit of the proposed methods and compare it to state-ofthe- art algorithms on radar measurements.

关键词： driver information systems feature extraction graph theory image registration intelligent transportation systems radar imaging road vehicles advanced driver assistance systems autonomous vehicles feature-based approach graph-based approach group-wise grid map registration image processing approach localization tasks mapping tasks mobile objects radar measurements radar-based occupancy grid maps range sensor maps rotational-invariant descriptor static objects Detectors Estimation Feature extraction Optimization Radar Robustness

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Real-Time Implementation of Background Modelling algorithms in FPGA Devices 18th

Real-Time Implementation of Background Modelling Algorithms ...

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18th International conference on image Analysis and processing (ICIAP)

作者： Kryjak, Tomasz Gorgon, Marek AGH Univ Sci & Technol Al Mickiewicza 30 PL-30059 Krakow Poland

ISBN: (纸本)9783319232225;9783319232218

the article discusses the possibilities of hardware implementation of foreground object segmentation and background modelling algorithms in FPGA. the potential benefits, as well as challenges and problems associated with porting algorithms from general-purpose processors (CPU) to reconfigurable logic (FPGA) are presented. Also several hardware implementation of well known method are reviewed: GMM, Codebook, Clustering, ViBE and PBAS. the last algorithm was also evaluated on the SBI dataset.

关键词： Real-time image processing Embedded systems Smart cameras Background modelling Foreground object segmentation

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Hand geometry and palmprint-based authentication using image processing 18

Hand geometry and palmprint-based authentication using image...

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18th IEEE International Symposium on Intelligent systems and Informatics, SISY 2020

作者： Oldal, Laura Gulyas Kovacs, Andras Óbuda University John von Neumann Faculty of Informatics Budapest Hungary

ISBN: (纸本)9781728173528

Nowadays, the importance of biometric authentication has increased, since biometric identifiers are unique to every individual, and are more reliable than knowledge or ownership factors. Palmprint and hand geometry features are suitable for high-confidence personal authentication. Contactless authentication is another topic which has been researched for capturing a palm image in more sanitary conditions. the combined use of multiple biometric identifiers results in a more reliable authentication system. this paper proposes a method for contactless hand geometry and palmprint-based authentication. the proposed method uses simple image processing algorithms and geometric relations for keypoint detection and palm image extraction. Morphological operations, averaging filters and different methods for noise filtering are used for palmprint principal line extraction. the corresponding points of palmprint images are detected by template-based matching which is followed by further filtering of matching points. With the use of hand geometry features and palmprint matching mechanism, the collected information of the hand and palm is suitable for authentication. © 2020 IEEE.

关键词： Authentication

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Implementation of An Ultrasound platform for Proposed Photoacoustic image Reconstruction Algorithm 18

Implementation of An Ultrasound platform for Proposed Photoa...

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18th IEEE International conference on Bioinformatics and Bioengineering

作者： Batbayar, Enkhbat Tumenjargal, Enkhbaatar Song, Chulgyu Ham, Woonchul Chonbuk Natl Univ Elect Div Jeonju South Korea

ISBN: (纸本)9781538662175

Photoacoustic tomography is a quickly growing imaging method that can provide images of high spatial resolution and high contrast at a limited depths. Medical photoacoustic processing characteristics two main components: A transducer is required to transmit laser pulses and acquire the reflected ultrasound signals and a back-end processing system that will generate the final reconstructed image. In this paper, we introduce an implementation of the receive part of proposed embedded system and briefly discuss reconstruction algorithms which are used in medical imaging systems. Furthermore, an intellectual property core (IP-core), which can be controlled and configured by a user application on Zynq-7000 System-On-Chip (SoC) via AXI-Lite Interface, that can receive multichannel digitized raw signals from Analog-Front-End (AFE) device via Low Voltage Differential Signal (LVDS), is proposed for photoacoustic imaging systems. Besides, block diagram of the system, the hardware design flow and the proposed IP-core are fully described in this paper. In order to effortlessly test and evaluate a wide variety of ultrasonic signal processing applications, 16 channel system is implemented and demonstrated by using TI AFE5816 Evaluation module (EVM) based on AFE5816 device and Xilinx ZC702 Evaluation Kit based on Zynq-7000 SoC. Apart from working on hardware, we review and commented on the proposed 3-Dimensional photoacoustic image reconstruction algorithm.

关键词： Photo-acoustic image portable ultrasound system multichannel AFE reconstruction algorithm

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Auto-vectorization for image processing DSLs 2017

Auto-vectorization for Image Processing DSLs

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18th ACM SIGPLAN/SIGBED conference on Languages, Compilers, Tools and theory for Embedded systems (LCTES)

作者： Reiche, Oliver Kobylko, Christof Hannig, Frank Teich, Juergen Friedrich Alexander Univ Erlangen Nurnberg FAU Dept Comp Sci Hardware Software Codesign Erlangen Germany

ISBN: (纸本)9781450350303

the parallelization of programs and distributing their workloads to multiple threads can be a challenging task. In addition to multithreading, harnessing vector units in CPUs proves highly desirable. However, employing vector units to speed up programs can be quite tedious. Either a program developer solely relies on the auto-vectorization capabilities of the compiler or he manually applies vector intrinsics, which is extremely error-prone, difficult to maintain, and not portable at all. Based on whole-function vectorization, a method to replace control flow with data flow, we propose auto-vectorization techniques for image processing DSLs in the context of source-to-source compilation. the approach does not require the input to be available in SSA form. Moreover, we formulate constraints under which the vectorization analysis and code transformations may be greatly simplified in the context of image processing DSLs. As part of our methodology, we present control flow to data flow transformation as a source-to-source translation. Moreover, we propose a method to efficiently analyze algorithms with mixed bit-width data types to determine the optimal SIMD width, independently of the target instruction set. the techniques are integrated into an open source DSL framework. Subsequently, the vectorization capabilities are compared to a variety of existing state-of-the-art C/C++ compilers. A geometric mean speedup of up to 3.14 is observed for benchmarks taken from ISPC and image processing, compared to non-vectorized executions.

关键词： Domain-Specific Languages Vectorization image processing

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