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检索条件"任意字段=3rd International Conference on Computer Vision and Image Processing, CVIP 2018"

共 1671 条记录，以下是991-1000 订阅

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An Efficient Approach Towards image Stitching in Aerial images

An Efficient Approach Towards Image Stitching in Aerial Imag...

引用

international conference on Information Technology Research (ICITR)

作者： R.M.N.B. Rathnayake L. Seneviratne Department of Electrical and Computer Engineering Sri Lanka Institute of Information Technology Malabe Sri Lanka

The following topics are dealt with: natural language processing; learning (artificial intelligence); text analysis; social networking (online); mobile robots; support vector machines; feature extraction; word process... 详细信息

ISBN: (纸本)9781728114712

关键词： Feature extraction image registration Classification algorithms Entropy Sorting Principal component analysis Calibration

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An interactive voice controlled humanoid smart home prototype using concepts of natural language processing and machine learning 3

An interactive voice controlled humanoid smart home prototyp...

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3rd IEEE international conference on Recent Trends in Electronics, Information and Communication Technology, RTEICT 2018

作者： Mithil, K.M. Mukesh Kumar, Khatri Bimal Sharma, Lalit Sayeed Pasha, Mohammed Zaki Kallinath, H.D. Siddaganga Institute of Technology Department of Computer Science and Engineering Tumakuru India

ISBN: (纸本)9781538624401

Currently available interactive technologies and infrastructure such as open source hardware, increased processing power, artificial intelligence (AI), machine learning (ML), Natural Language processing (NLP) and connectivity through the internet, have led to a new definition of human living. Smart homes, smart streets, smart cities and eventually a smarter planet, is what humans are progressing towards. The boon in things being smart is that it involves automation and interactive technologies, something that we as humans prefer over introvert and monotonous characteristic of machines. However, most present systems have a physical entity like a remote or a personal device assistant (PDA) which is used to control our homes. When the access to these physical devices is lost, you can no longer control them. This paper addresses this very issue and proposes a solution which eliminates the need for any physical device. It proposes a multi-functional 'Smart Home Automation System' (SHAS) controlled using an interactive and humanoid central processing unit which is powered by features of AI and NLP. Voice-commands to control the devices of the house such as fans, lights, doors, etc. can be given by the residents. The system is also intelligent enough to search things which it doesn't quite understand using the internet. The system has a camera integrated for continuously monitoring the home and also uses image processing techniques to identify the people trying to access the house. The system also has an automated mailing system which e-mails photos captured by the camera based on valid/invalid users. The system is aimed at being easy, cost-effective and non-physical. © 2018 IEEE.

关键词： Automation

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Analysis of segmentation methods on isolated balinese characters from palm leaf manuscripts 3rd

Analysis of segmentation methods on isolated balinese charac...

引用

3rd international conference on Cognitive Computing and Information processing, CCIP 2017

作者： Kumar, Deepak Vatsala, K. Pattanashetty, Sushmitha Sandhya, S. Udayapura Kanakapura Main Road Bengaluru560082 India

ISBN: (纸本)9789811090585

Segmentation of an image is a complex process when image has to be divided into constituent and meaningful parts. In case of a clean image, the segmentation process is an easy task due to distinct foreground and background within the image. Whereas, the images captured or scanned from palm leaf manuscripts, the segmentation process is more complex and complicated. In this paper, we have used the individual characters from the palm leaf manuscript for segmentation. We have chosen multiple segmentation algorithms to perform segmentation of isolated Balinese characters. We evaluate the performance of all the algorithms on AMADI_Lontarset dataset. From our analysis, we observe that a global thresholding approach provides good segmentation on the set of analyzed images over the local thresholding approach. © 2018, Springer Nature Singapore Pte Ltd.

关键词： image segmentation

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computer Communication, Networking and Internet Security: Proceedings of IC3T 2016

引用

2018年

作者： Suresh Chandra Satapathy Vikrant Bhateja K Srujan Raju B Janakiramaiah

ISBN: (纸本)9789811098208

The book is a compilation of high-quality scientific papers presented at the 3rd international conference on computer & Communication Technologies (IC3T 2016). The individual papers address cutting-edge technologies and applications of soft computing, artificial intelligence and communication. In addition, a variety of further topics are discussed, which include data mining, machine intelligence, fuzzy computing, sensor networks, signal and image processing, human-computer interaction, web intelligence, etc. As such, it offers readers a valuable and unique resource.

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Lunar Geomorphology Three-Dimensional Visualization within WorldWide Telescope Based on GPU

Lunar Geomorphology Three-Dimensional Visualization within W...

引用

international conference on image, vision and Computing (ICIVC)

作者： Wanfeng Zhang Shengyang Li Bo Wang Chinese Academy of Sciences Key Laboratory of Lunar and Deep Space Exploration Beijing China

ISBN: (纸本)9781538649923

The three-dimensional visualization of lunar geomorphology was a significant research topic. There exist some problems during the three-dimensional visualization of lunar geomorphology image such as massive dataset rendering, parallelized visualization algorithms on GPU, and lunar geomorphology image projection transformation. So this paper utilized the WorldWide Telescope platform as the image rendering architecture and adopted the OSWorkflow engine and OpenPBS scheduler to enhance parallel efficiency. Beyond above, one map transformation called tessellated octahedral adaptive subdivision transform was also designed and applied into the lunar geomorphology image three-dimensional rendering.

关键词： Moon Graphics processing units Rendering (computer graphics) Decoding computer architecture Three-dimensional displays Task analysis

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A Cost-Effective Audio-Visual Summarizer for Summarization of Presentations and Seminars 3

A Cost-Effective Audio-Visual Summarizer for Summarization o...

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3rd international conference on Computational Systems and Information Technology for Sustainable Solutions, CSITSS 2018

作者： Bhat, Anmol Rao, Aneesh C. Bhaskar, Anirudh Adithya, V. Computer Science and Engineering RVCE Bangalore India RVCE Bangalore India

ISBN: (纸本)9781538660782

Nowadays, more than half the world's population live hand-in-hand with technology. From smart watches to smart phones to smart cities, the embodiment of technology in all of our day-to-day activities no longer looks like a distant dream. Lectures in classrooms have also advanced to the extent of using smart-boards and smart-classrooms;the developments in jotting down notes in such scenarios has, however, not advanced at the same pace. In the problem statement being tackled, based on similar lines, the target audience includes the attendees of any seminar, presentation or lecture, be it students, or the public in general, attending important conferences and talks. More often than not, complete undivided attention proves to be difficult at these seminars as the attendee may be preoccupied with the objective of jotting down pointers and making notes for future reference. It is during this process that several essentials in the speaker's delivery are missed out. Keeping this forethought in mind, this paper delves into the implementation of an audio-visual summarizer that achieves the aforementioned motive. With audio evidence on the speaker's delivery, paired with visual images of PowerPoint slides or handwritten material that is presented in the seminars, this device provides a smart solution of summarizing the entire presentation and logging the summary to a remote database server from where it is accessed through a user-end software application. The prototype comprises a Raspberry Pi coupled with a camera and a microphone. The prototype uses a fast RCNN model for text detection, Open Source computer vision (OpenCV) for text extraction, Google Speech Recognition and Natural Language processing concepts for generating the summarized data. The proposed solution is very effective, in terms of feasibility and cost cutting factors. The novelty aspect of the proposed solution lies in the consolidation of ideas of Internet of Things (IOT) and machine learning, to deliver a p

关键词： Object detection

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Automated computer Aided Detection of Cataract 3rd

Automated Computer Aided Detection of Cataract

引用

3rd international Afro-European conference for Industrial Advancement (AECIA)

作者： Khan, Albab Ahmad Akram, M. Usman Tariq, Ahmad Tahir, Faraz Wazir, Kamran Natl Univ Sci & Technol Coll Elect & Mech Engn Dept Comp Engn Islamabad Pakistan

ISBN: (纸本)9783319608341;9783319608334

A common eye diseases named as cataract can cause blindness. It normally affects the central vision of the person and in some cases causes severe blindness depending upon its stage. Cataract is one of the diseases of eye in which the clouding of the lens occur which leads to the permanent blindness if not detected and treated on time. Now a day's cataract is being diagnosed by initially dilating the pupil and afterwards examining the eye through the slit lamp. computer Aided Diagnostic (CAD) systems with their mobility of usage in low resource settings can be very useful for the detection of cataract. For the detection of cataract through CAD system, the picture of the patient with retina in focus, is accessed and our proposed method localizes the iris and pupil of the eye. Texture analysis of the obtained image is performed enabling us to tell whether the eye is normal or it has cataract. The system is developed and tested using locally gathered dataset of cataract.

关键词： Cataract detection Eye images CAD system Cataract Automated computer Aided Detection of Cataract

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Head Ternary Pattern-Head Shoulder Density Features Pedestrian Detection Algorithm Based on Depth image 1st

Head Ternary Pattern-Head Shoulder Density Features Pedestri...

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1st international conference on Intelligent Manufacturing and Internet of Things (IMIOT) / 5th international conference on Computing for Sustainable Energy and Environment (ICSEE)

作者： Wang, Haikuan Sun, Haoxiang Liu, Kangli Fei, Minrui Shanghai Univ Sch Mechatron Engn & Automat 99 Shangda Rd Shanghai 200444 Peoples R China

ISBN: (纸本)9789811323843;9789811323836

The existing pedestrian detection algorithms are mostly based on 2D image processing, which are susceptible to complex background, the changes of light intensity, and many other factors. For these reasons, the robustness and accuracy of traditional algorithms are not ideal. Moreover, for other few algorithms that use 3D vision, the core process is to extract features by converting 3D images to grayscale images, which cannot make full use of depth information. To solve these problems, a pedestrian detection algorithm based on depth image is proposed in this paper. For depth image preprocessing, a 3D dilation and erosion algorithm based on probability density is proposed. Combined with the Head Ternary Pattern-Head Shoulder Density (HTP-HSD) features proposed in this paper, the implement of pedestrian detection can be ensured using SVM classifier to classify the features. Experimental results show that the HTP-HSD features meet the actual needs of pedestrian detection with higher recognition rate and recognition speed.

关键词： Depth image Pedestrian detection 3D dilation and erosion HTP-HSD

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Brain Cancer Imaging Phenomics Toolkit (brain-CaPTk): An Interactive Platform for Quantitative Analysis of Glioblastoma 3rd

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3rd international Workshop on Brain-Lesion (BrainLes) held jointly at the conference on Medical image Computing for computer Assisted Intervention (MICCAI)

作者： Rathore, Saima Bakas, Spyridon Pati, Sarthak Akbari, Hamed Kalarot, Ratheesh Sridharan, Patmaa Rozycki, Martin Bergman, Mark Tunc, Birkan Verma, Ragini Bilello, Michel Davatzikos, Christos Univ Penn Perelman Sch Med CBICA Dept Radiol Philadelphia PA 19104 USA

ISBN: (纸本)9783319752389;9783319752372

Quantitative research, especially in the field of radio(geno) mics, has helped us understand fundamental mechanisms of neurologic diseases. Such research is integrally based on advanced algorithms to derive extensive radiomic features and integrate them into diagnostic and predictive models. To exploit the benefit of such complex algorithms, their swift translation into clinical practice is required, currently hindered by their complicated nature. brain-CaPTk is a modular platform, with components spanning across image processing, segmentation, feature extraction, and machine learning, that facilitates such translation, enabling quantitative analyses without requiring substantial computational background. Thus, brain-CaPTk can be seamlessly integrated into the typical quantification, analysis and reporting workflow of a radiologist, underscoring its clinical potential. This paper describes currently available components of brain-CaPTk and example results from their application in glioblastoma.

关键词： Glioblastoma Open-source software Radiomics Radiogenomics Computational algorithms image analysis Fiber tracking

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Distributed Deep Reinforcement Learning using TensorFlow 3

Distributed Deep Reinforcement Learning using TensorFlow

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3rd international conference on Current Trends in computer, Electrical, Electronics and Communication, CTCEEC 2017

作者： Ajay Rao, P. Navaneesh Kumar, B. Cadabam, Siddharth Praveena, T. Department of Computer Science Engineering RVCE Bengaluru 59 India

ISBN: (纸本)9781538632420

Deep Reinforcement Learning is the combination of Reinforcement Learning algorithms with Deep neural network, which had recent success in learning complicated unknown environments. The trained model is a Convolutional Neural Network trained using Q-Learning Loss value. The agent takes in observation, i.e. raw pixel image and reward from the environment for each step as input. The deep Q-learning algorithm gives out the optimal action for every observation and reward pair. The hyperparameters of Deep Q-Network remain unchanged for any environment. TensorFIow, an open source machine learning and numerical computation library is used to implement the deep Q-Learning algorithm on GPU. The distributed TensorFIow architecture is used to maximize the hardware resource utilization and reduce the training time. The usage of Graphics processing Unit (GPU) in the distributed environment accelerated the training of deep Q-network. On implementing the deep Q-learning algorithm for many environments from OpenAI Gym, the agent outperforms a decent human reference player with few days of training. © 2017 IEEE.

关键词： Graphics processing unit

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