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检索条件"任意字段=International Conference on Computer Vision and Image Processing, CVIP 2016"

共 1410 条记录，以下是131-140 订阅

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Quaternion circularly semi-orthogonal moments for invariant image recognition

Quaternion circularly semi-orthogonal moments for invariant ...

引用

international conference on computer vision and image processing, cvip 2016

作者： Ananth Raj, P. Department of ECE College of Engineering Osmania University HyderabadTelangana500 007 India

ISBN: (纸本)9789811021060

We propose a new Quaternion Circularly Semi-Orthogonal Moments for color images that are invariant to rotation, translation and scale changes. In order to derive these moments we employ the recently proposed Circularly Semi-Orthogonal Moment’s expression. Invariant properties are verified with simulation results and found that they are matching with theoretical proof. © Springer Science+Business Media Singapore 2017.

关键词： image recognition

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Automatic Diagnosis of Age-Related Macular Degeneration via Federated Learning 8th

Automatic Diagnosis of Age-Related Macular Degeneration via ...

引用

8th international conference on computer vision and image processing (cvip)

作者： Sonti, Movya Kokil, Priyanka Indian Inst Informat Technol Design & Mfg Dept Elect & Commun Engn Adv Signal & Image Proc ASIP Lab Chennai 600127 Tamil Nadu India

ISBN: (纸本)9783031581731;9783031581748

Artificial intelligence has taken healthcare a step forward by providing quick diagnosis and treatment recommendations. The traditional machine-learning approach requires massive data to train the model for better diagnosis. But, due to policy regulations, medical data is always guarded by the barricades of the law, making data accessibility difficult for researchers. To address this issue, a data-decentralized collaborative framework known as federated learning is adopted that reaps the benefits of huge private data without aggregating it into a single common store. A pre-trained model is employed to diagnose age-related macular degeneration and performance of the proposed framework is compared with other two model architectures, namely, MobileNet and InceptionV3. To investigate the effectiveness of the proposed framework, a comparison is made with a data-centralized learning approach. Using the MobileNet model, the federated and centralized frameworks have achieved an accuracy of 95% and 92%, respectively. These findings encourage clinicians around the globe to utilize wealthy private data without violating privacy laws using federated learning to build a powerful model for classifying any disorders while maintaining data privacy.

关键词： Federated learning Privacy Data-security Data-decentralization Pre-trained models Age-related macular degeneration

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Morphological geodesic active contour based automatic aorta segmentation in thoracic CT images

Morphological geodesic active contour based automatic aorta ...

引用

international conference on computer vision and image processing, cvip 2016

作者： Dasgupta, Avijit Mukhopadhyay, Sudipta Mehre, Shrikant A. Bhattacharyya, Parthasarathi Computer Vision and Image Processing Laboratory Department of Electronics and Electrical Communication Engineering Indian Institute of Technology Kharagpur West Bengal721302 India Institute of Pulmocare & Research KolkataWest Bengal700156 India

ISBN: (纸本)9789811021060

Automatic aorta segmentation and quantification in thoracic computed tomography (CT) images is important for detection and prevention of aortic diseases. This paper proposes an automatic aorta segmentation algorithm in both contrast and non-contrast CT images of thorax. The proposed algorithm first detects the slice containing the carina region. Circular Hough Transform (CHT) is applied on the detected slice to localize ascending and descending aorta (circles with lowest variances) followed by a morphological geodesic active contour to segment the aorta from CT stack. The dice similarity coefficients (DSC) between the ground truth and the segmented output were found to be 0.8845 ± 0.0584 on LIDC-IDRI dataset. © Springer Science+Business Media Singapore 2017.

关键词： image segmentation

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Recent Advancements in image-Based Prediction Models for Diagnosis of Plant Diseases 3rd

Recent Advancements in Image-Based Prediction Models for Dia...

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3rd international conference on computer vision and image processing (cvip)

作者： Verma, Shradha Chug, Anuradha Singh, Amit Prakash GGSIP Univ USICT Delhi India

ISBN: (纸本)9789813290884;9789813290877

India plays a significant role in the world as a major contributor to the overall food industry. Farming being a major occupation, crop protection from plant diseases has become a serious concern. The occurrence of plant diseases is hugely dependent on environmental factors which are uncontrollable. Ongoing agricultural research and the advanced computational technologies can be coalesced to determine an effective solution, which can improve the yield and result in better harvests. The objective is to minimize the economic and production losses. Researchers have developed several modeling techniques, viz. Artificial Neural Networks (ANN), Support Vector Machines (SVM), and Deep Learning for prediction and preferably early detection of diseases in plants. Mostly, images of the diseased plant are given as input to these prediction models. Early detection leads to minimizing the pesticide usage, hence, resulting in lowering the expense along with the ecological impact. Also, it is essential that the prediction techniques are nondestructive in nature. This paper delves into the Machine Learning based plant disease prediction models, along with a brief study of diverse imaging techniques, viz., RGB, multi- and hyperspectral, thermal, fluorescence spectroscopy, etc., catering to different features/parameters of a plant, useful in the prediction of diseases. Around 35 research papers from reputed peer-reviewed journals were studied and analyzed for this systematic review. It highlights the latest trends in plant disease diagnosis as well as identifies the future scope with the application of modern era technologies.

关键词： Imaging Machine Learning Plant diseases Neural Networks Deep Learning Agriculture

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computer vision and image processing 1

引用

丛书名： Communications in computer and Information Science

1000年

作者： Satish Kumar Singh P. Nagabhushan Partha Roy Balasubramanian Raman

ISBN: (数字)9789811610929

ISBN: (纸本)9789811610912

This three-volume set (CCIS 1367-1368) constitutes the refereed proceedings of the 5th international conference on computer vision and image processing, cvip 2020, held in Prayagraj, India, in December 2020. Due to the COVID-19 pandemic the conference was partially held online.;The 134 papers papers were carefully reviewed and selected from 352 submissions. The papers present recent research on such topics as biometrics, forensics, content protection, image enhancement/super-resolution/restoration, motion and tracking, image or video retrieval, image, image/video processing for autonomous vehicles, video scene understanding, human-computer interaction, document image analysis, face, iris, emotion, sign language and gesture recognition, 3D image/video processing, action and event detection/recognition, medical image and video analysis, vision-based human GAIT analysis, remote sensing, and more.

关键词： computer Imaging, vision, Pattern Recognition and Graphics Machine Learning computer Systems Organization and Communication Networks computers and Education computer Applications

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Ramanujan Sums Based image Kernels for computer vision

Ramanujan Sums Based Image Kernels for Computer Vision

引用

international conference on Electrical, Electronics, and Optimization Techniques (ICEEOT)

作者： Krishnaprasad, P. Ramanujan, Ajeesh GEC Palakkad Dept Comp Engn Palakkad Kerala India

ISBN: (纸本)9781467399395

In the recent history, kernel methods had established themselves as powerful tools for computer vision. In this paper we introduce an integer image kernel function based on Ramanujan Sums which finds its place in image vision. The paper proves the validity of kernel function theoretically and also shows the application of the kernel in image vision. Ramanujan Sums are based on number theory and hence the new kernel matrix will contain only the integer values. Since the image processing involves complex matrix manipulations, the processing based on the new kernel will be computationally effective. The paper shows the applicability of the kernel in various context of image processing. By applying the theory of Ramanujan Sums for image kernel, we will show the intervention of numerical mathematics in machine learning which gives new directions for future research.

关键词： image Kernels Ramanujan Sums Edge Detection image Gradient computer vision

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A Review on image processing and image Segmentation.

A Review on Image Processing and Image Segmentation.

引用

international conference on Data Mining and Advanced Computing (SAPIENCE)

作者： Kuruvilla, Jiss Sukumaran, Dhanya Sankar, Anjali Joy, Siji P. Sree Narayana Gurukulam Coll Engn Dept Comp Applicat Kadayiruppu Kerala India Nirmala Coll Muvattupuzha Dept Comp Applicat Muvattupuzha Kerala India

ISBN: (纸本)9781467385947

A methodological study on significance of image processing and its applications in the field of computer vision is carried out here. During an image processing operation the input given is an image and its output is an enhanced high quality image as per the techniques used. image processing usually referred as digital image processing, but optical and analog image processing also are possible. Our study provides a solid introduction to image processing along with segmentation techniques, computer vision fundamentals and its applied applications that will be of worth to the image processing and computer vision research communities.

关键词： image restoration image segmentation Face Detection Character Recognition Signature Verification Biometrics Automatic Target Recognition Fuzzy C-Mean

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Colorization of Thermal Facial images into Visible Facial image Using RGB-GAN 1

引用

8th international conference on computer vision and image processing (cvip)

作者： Bhadane, Dnyaneshwar Chakraborty, Soumendu Indian Inst Informat Technol Lucknow Dept Comp Sci Lucknow 226002 Uttar Pradesh India

ISBN: (数字)9783031585357

ISBN: (纸本)9783031585340;9783031585357

images captured by thermal cameras are independent of lighting conditions. However, it can be challenging for human examiners to identify thermal face photos. Facial recognition technology enables automatic identification or verification of individuals in digital images or video frames extracted from video sequences. There are multiple methods employed by facial recognition systems, but they typically involve comparing the features extracted from a specific image with those stored in a database. This technology finds application in various areas, including access control and identification systems. It is worth noting that facial features can exhibit unique characteristics specific to an individual throughout their lifetime. In this paper, the process of colorizing thermal facial images into the visible spectrum based on Cycle GAN is undertaken. There are many variations of the GAN but to translate or map from the one domain image into another domain image the cycle GAN fits with its application. CycleGAN aims to acquire knowledge of the relationship between two distinct image collections originating from separate domains, each possessing unique styles, textures, or visual attributes. The RGB-GAN which is proposed in this paper refers to the red, green, and blue channel generative adversarial network that individually takes the independent images in the thermal format to colorize in the independent domain channel network-merging three generated channel results combined to make one RGB-colored image. One more generator network involves identifying and comparing the result with the original visible colored image to give feedback to the network. At last after training the final model, the classification task involves generating and classifying the correct person out group of persons when the thermal image is given as input. The output includes face recognition accuracy of generated images, comparative analysis with protocols and state-of-the-art techniques.

关键词： image translation Cycle GAN Colorization Thermal images Facial data

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computer vision and image processing 1

引用

丛书名： Communications in computer and Information Science

1000年

作者： Satish Kumar Singh P. Nagabhushan Partha Roy Balasubramanian Raman

ISBN: (数字)9789811611032

ISBN: (纸本)9789811611025

关键词： computer Imaging, vision, Pattern Recognition and Graphics Artificial Intelligence Information Systems and Communication Service Computing Milieux computer System Implementation computer Appl. in Social and Behavioral Sciences

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computer vision and image processing 1

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丛书名： Communications in computer and Information Science

1000年

作者： Balasubramanian Raman Subrahmanyam Murala Abhinav Dhall Puneet Goyal Ananda Chowdhury

ISBN: (数字)9783031113468

ISBN: (纸本)9783031113451

This two-volume set (CCIS 1567-1568) constitutes the refereed proceedings of the 6h international conference on computer vision and image processing, cvip 2021, held in Rupnagar, India, in December 2021.;The 70 full papers and 20 short papers were carefully reviewed and selected from the 260 submissions. The papers present recent research on such topics as biometrics, forensics, content protection, image enhancement/super-resolution/restoration, motion and tracking, image or video retrieval, image, image/video processing for autonomous vehicles, video scene understanding, human-computer interaction, document image analysis, face, iris, emotion, sign language and gesture recognition, 3D image/video processing, action and event detection/recognition, medical image and video analysis, vision-based human GAIT analysis, remote sensing, and more.

关键词： computer Imaging, vision, Pattern Recognition and Graphics Artificial Intelligence computer Systems Organization and Communication Networks computers and Education computer Applications

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