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Semantic Map Injected GAN Training for image-to-image Translation 12th

Semantic Map Injected GAN Training for Image-to-Image Transl...

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12th indian conference on computer vision, graphics, and image processing, ICVGIP 2021

作者： Kshatriya, Balaram Singh Dubey, Shiv Ram Sarma, Himangshu Chaudhary, Kunal Gurjar, Meva Ram Rai, Rahul Manchanda, Sunny Computer Vision Group Indian Institute of Information Technology Sri City Chittoor India Computer Vision and Biometrics Lab Indian Institute of Information Technology Allahabad India Bangalore India

ISBN: (纸本)9789811941351

image-to-image translation is the recent trend to transform images from one domain to another domain using a generative adversarial network (GAN). the existing GAN models perform the training by only utilizing the input and output modalities of transformation. In this paper, we perform the semantic injected training of GAN models. Specifically, we train with original input and output modalities and inject a few epochs of training for translation from input to semantic map. Let us refer to the original training as the training for the translation of the input image into the target domain. the injection of semantic training in the original training improves the generalization capability of the trained GAN model. Moreover, it also preserves the categorical information in a better way in the generated image. the semantic map is only utilized at the training time and is not required at the test time. the experiments are performed using state-of-the-art GAN models over CityScapes and RGB-NIR stereo datasets. We observe the improved performance in terms of the SSIM, FID, and KID scores after injecting semantic training as compared to the original training. © 2022, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Generative adversarial networks

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A new SIFT matching criteria in a genetic algorithm framework for registering multisensory satellite imagery 14

A new SIFT matching criteria in a genetic algorithm framewor...

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9th indian conference on computer vision, graphics and image processing, ICVGIP 2014

作者： Senthilnath, J. Prasad, Ram Department of Aerospace Engineering Indian Institute of Science Bangalore India Department of Electronics and Communication Engineering NITK-Surathakal Mangalore India

ISBN: (纸本)1595930361

Synthetic Aperture Radar (SAR) images are efficient and reliable source of information in extraction of damaged regions in case of floods. In assessment of damage accurately due to floods, image registration of optical (before-flood) and SAR images (after-flood) has to be carried out efficiently. In this paper, we discuss a robust multi-sensor image registration algorithm using scale invariant feature points for keypoint extraction. For matching the keypoints, a multi-objective genetic algorithm is developed with angle, distance and vicinity criterion as the fitness functions. this optimization process helps in matching the scale invariant feature points. From the obtained results, the performance of the image registration is evaluated and it is concluded that the proposed approach is efficient. Copyright 2014 ACM.

关键词： Genetic algorithms

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Scale-invariant image inpainting using gradient-based image composition 10

Scale-invariant image inpainting using gradient-based image ...

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10th indian conference on computer vision, graphics and image processing, ICVGIP 2016

作者： Ghorai, Mrinmoy Samanta, Soumitra Chanda, Bhabatosh Indian Statistical Institute Kolkata India

In this paper, we propose a novel scale-invariant image inpainting algorithm that combines several inpainted images obtained from multiple pyramids of different coarsest scales. To achieve this, first we build the pyramids and then we run an image inpainting algorithm individually on each of the pyramids to obtain different inpainted images. Finally, we combine those inpainted images by a gradient based approach to obtain the final inpainted image. the motivation of this approach is to solve the problem of appearing artifacts in traditional single pyramid-based approach since the results depend on the starting scale of the pyramid. Here we assume that most of the inpainted images produced by the pyramids are quite good. However, some of them may have artifacts and these artifacts are eliminated by gradient based image composition. We test the proposed algorithm on a large number of natural images and compare the results with some of the existing methods to demonstrate the efficacy and superiority of the proposed method. © Springer International Publishing AG 2017.

关键词： image processing

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Autism Spectrum Disorder Classification of Facial images Using Xception Model and Transfer Learning with image Augmentation 29th

Autism Spectrum Disorder Classification of Facial Images Usi...

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29th International conference on Neural Information processing

作者： Shrivastava, Trapti Singh, Vrijendra Agrawal, Anupam Indian Inst Informat Technol Dept Informat Technol Allahabad 211015 Uttar Pradesh India

ISBN: (纸本)9783031301100;9783031301117

Autism spectrum disorder (ASD) is a neurodevelopmental disorder in which the neurology of an autistic person is severely hampered. A child with autism has difficulty answering his name, avoids eye contact, and cannot express his emotions. Early diagnosis can assist children with ASD enhance their intellectual abilities while reducing autistic symptoms. In computer vision, determining developmental disorder problems from facial image data is a significant but largely unexplored challenge. this paper proposed a method to classify autistic and non-autistic facial images using model 1 (Xception) and model 2 (Augmentation + Xception). Among Model 1 and Model 2, Model 2 achieved higher accuracy of 98% and a minimum loss of 0.08.

关键词： Autism Spectrum Disorder Facial image image Augmentation Transfer learning Xception Model

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Methods and system for segmentation of isolated nuclei in microscopic breast fine needle aspiration cytology images 10

Methods and system for segmentation of isolated nuclei in mi...

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10th indian conference on computer vision, graphics and image processing, ICVGIP 2016

作者： Garud, Hrushikesh Karri, Sri Phani Krishna Sheet, Debdoot Maity, Ashok Kumar Chatterjee, Jyotirmoy Mahadevappa, Manjunatha Ray, Ajoy Kumar Indian Institute of Technology Kharagpur Kharagpur721301 India Midnapur Medical College and Hospital Midnapur721101 India

computer vision systems for automated breast cancer diagnosis using Fine Needle Aspiration Cytology (FNAC) images are under development for a while now. Accurate segmentation of the nuclei in microscopic images is crucial for functioning of these systems, as most quantify and analyze nuclear features for diagnosis. this paper presents a nucleus segmentation system (NSS) involving pre-processing, pre-segmentation and refined segmentation stages. the NSS includes a novel pixel transformation step to create a high contrast grayscale representation of the input color image. the grayscale image gives NSS the capability-to disregard elements that mimic nuclear morphological and luminescence characteristics, and to minimize effects of non-specific staining of cytoplasm by Hematoxylin. Experimental results illustrate generalizability of the NSS to use multiple refined segmentation techniques and particularly achieve accurate nucleus segmentation using active contours without edges(F-score > 0.92). the paper also presents the results of experiments conducted to study the impact of image pre-processing steps on the NSS performance. the pre-processing steps are observed to improve accuracy and consistency across tested refined segmentation techniques. © Springer International Publishing AG 2017.

关键词： Cytology

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Variational Augmentation for Enhancing Historical Document image Binarizationg± 13

Variational Augmentation for Enhancing Historical Document I...

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13th indian conference on computer vision, graphics, and image processing, ICVGIP 2022

作者： Dey, Avirup Nasipuri, Prof. Mita Das, Nibaran Jadavpur University West Bengal Kolkata India

ISBN: (纸本)9781450398237

Historical Document image Binarization is a well-known seg-mentation problem in image processing. Despite ubiquity, traditional thresholding algorithms achieved limited success on severely degraded document images. With the advent of deep learning, several segmentation models were proposed that made significant progress in the field but were limited by the unavailability of large training datasets. To mitigate this problem, we have proposed a novel two-stage framework-the first of which comprises a generator that generates degraded samples using variational inference and the second being a CNN-based binarization network that trains on the generated data. We evaluated our framework on a range of DIBCO datasets, where it achieved competitive results against previous state-of-the-Art methods. © 2022 ACM.

关键词： image enhancement

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Symbol Spotting in Offline Handwritten Mathematical Expressions 4th

Symbol Spotting in Offline Handwritten Mathematical Expressi...

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4th Workshop on Document Analysis and Recognition, DAR 2018, held in Conjunction with the 11th indian conference on vision, graphics, and image processing, ICVGIP 2018

作者： Aggarwal, Ridhi Harit, Gaurav Tiwari, Anil Kumar Department of Computer Science and Engineering Indian Institute of Technology Jodhpur Jodhpur India Department of Electrical Engineering Indian Institute of Technology Jodhpur Jodhpur India

ISBN: (纸本)9789811393600

Recognition of touching characters in mathematical expressions is a challenging problem in the field of document image analysis. Various approaches for recognizing touching maths symbols have been reported in literature, but they mainly dealt with printed expressions and handwritten numeral strings. In this work, a new segmentation-free approach is proposed which matches convex shape portions of symbols occurring in various layout such as subscript, superscript, fraction etc. and is able to perform spotting of symbols present in a handwritten expression. Our contribution lies in the design of a novel feature which can handle touching symbols effectively in the presence of handwriting variations. this recognition-based approach helps in spotting symbols in an expression even in the presence of clutter created by the presence of other symbols. © Springer Nature Singapore Pte Ltd. 2019.

关键词： Character recognition

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A GPU based real-time CUDA implementation for obtaining visual saliency 14

A GPU based real-time CUDA implementation for obtaining visu...

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9th indian conference on computer vision, graphics and image processing, ICVGIP 2014

作者： Agrawal, Rahul Gupta, Soumyajit Mukherjee, Jayanta Layek, Ritwik Kumar Indian Institute of Technology Kharagpur WestBengal721302 India

ISBN: (纸本)1595930361

We present a GPU-based implementation of the saliency model proposed by Achanta et al. [1] to perform real-time and detailed saliency map generation. We map all the components of the algorithm to GPU-based kernels and data structures. the parallel version of the algorithm is able to accurately simulate the desired results in a very low time. We describe the streaming pipeline and address many issues in terms of obtaining high throughput on multi-core GPUs. We highlight the parallel performance of the algorithm on three different generations of GPUs. On a high-end NVIDIA Tesla K20m, we observe up to 600x order of magnitude performance improvement as compared to a singlethreaded CPU-based algorithm, and about 300x order of magnitude improvement over a CPU-based OpenCV implementation. Copyright 2014 ACM.

关键词： graphics processing unit

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Multiscale intuitionistic fuzzy roughness measure for color image segmentation 14

Multiscale intuitionistic fuzzy roughness measure for color ...

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9th indian conference on computer vision, graphics and image processing, ICVGIP 2014

作者： Dubey, Yogita K. Mushrif, Milind M. Nehare, Prajakta R. Department of Electronics and Telecommunication YCCE Nagpur India Department of Electronics and Communication SDMP Nagpur India

ISBN: (纸本)1595930361

In this paper, a method for color image segmentation using multiscale intuitionistic fuzzy roughness measure is proposed. the traditional roughness measure tends to over focus on the little important homogeneous regions but is not accurate enough to measure the homogeneity in an image. By applying the theories of scale space and using intuitionistic fuzzy representation for images, roughness is measured under multiple scales. Multiscale representation can tolerate the disturbance of trivial regions, and intuitionistic fuzzy representation deals with hesitancy in image boundary, therefore produces precise segmentation results. Copyright 2014 ACM.

关键词： Fuzzy sets

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High resolution 3-D MR image reconstruction from multiple views 12

High resolution 3-D MR image reconstruction from multiple vi...

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8th indian conference on computer vision, graphics and image processing, ICVGIP 2012

作者： Mondal, Prasenjit Mukherjee, Jayanta Sural, Shamik Bhattacharyya, Pinak Pani Department of Computer Science and Engineering Indian Institute of Technology Kharagpur India School of Information Technology Indian Institute of Technology Kharagpur India Department of Radiology Quadra Medical Services Pvt. Ltd. Kolkata India

ISBN: (纸本)9781450316606

this paper introduces an efficient technique to reconstruct the volume of human brain from low resolution MR image sequences acquired in sagittal, coronal and axial views. the algorithm uses image interpolation as the basis of volume reconstruction. It works in different stages. At first, the brightness and contrast of the MR images in different views are normalized based on the repetition time (TR) and echo time (TE) used during the MR imaging. Alignment of MR image sequences in different views is performed based on a standard 3D human brain anatomical model. Based on the alignment information, the spatial resolution of the MR images in all of the three views are normalized. Furthermore, a technique using normalized cross-correlation has been applied to refine the alignment process. Finally, the high resolution volume of the brain is reconstructed by interpolation based on inverse distance weighing. the proposed volume reconstruction scheme shows promising results producing good quality of the reconstructed volume images. © 2012 ACM.

关键词： Interpolation

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