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检索条件"任意字段=6th Indian Conference on Computer Vision, Graphics and Image Processing"

共 2009 条记录，以下是11-20 订阅

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

Proceedings of ICVGIP 2021 - 12th Indian Conference on Compu...

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

ISBN: (纸本)9781450391276

the proceedings contain 49 papers. the topics discussed include: teaching GANs to sketch in vector format;iterative gradient encoding network using feature co-occurrence loss for single image reflection removal;MSDNet: a novel multi-stage progressive image dehazing network;monocular multi-layer layout estimation for warehouse racks;cross-view kernel similarity metric learning using pairwise constraints for person re-identification;abnormality detection and classification of macular diseases from optical coherence tomography images: using feature space comparison;a novel unsupervised thresholding technique for Landsat image change detection;robust brain state decoding using bidirectional long short term memory networks in functional MRI;NTU-X: an enhanced large-scale dataset for improving pose-based recognition of subtle human actions;and interpretive self-supervised pre-training: boosting performance on visual medical data.

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Proceedings of ICVGIP 2023 - 14th indian conference on computer vision, graphics and image processing

Proceedings of ICVGIP 2023 - 14th Indian Conference on Compu...

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14th indian conference on computer vision, graphics and image processing, ICVGIP 2023

ISBN: (纸本)9798400716256

the proceedings contain 39 papers. the topics discussed include: single view homography estimation for an inclined textured planar surface: overcoming the inverse and ill-posed challenge!;MMAG: mutually motivated attention gates for simultaneous extraction of contextual and spatial information from a monocular image;automatic assessment of communication skill in real-world job interviews: a comparative study using deep learning and domain adaptation;an efficient motor imagery classification framework using sparse brain connectivity and class-consistent dictionary learning from electroencephalogram signals;mandala as computational art: vectorization and beyond;degradation aware multi-scale approach to no reference image quality assessment;dual stage semantic information based generative adversarial network for image super-resolution;knowledge distillation with ensemble calibration;and a novel framework for robust fingerprint representations using deep convolution network with attention mechanism.

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

Proceedings of ICVGIP 2022 - 13th Indian Conference on Compu...

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

ISBN: (纸本)9781450398237

the proceedings contain 59 papers. the topics discussed include: interpreting intrinsic image decomposition using concept activations;quaternion factorized simulated exposure fusion;learning from multiple datasets for recognizing human actions;topological shape matching using multi-dimensional Reeb graphs;convolutional ensembling based few-shot defect detection technique;performance, trust, or both? COVID-19 diagnosis and prognosis using deep ensemble transfer learning on x-ray images;Alzheimer’s severity classification using transfer learning and residual separable convolution network;detecting coronavirus (COVID–19) disease cues from chest radiography images;posture guided human action recognition for fitness applications;towards robust handwritten text recognition with on-the-fly user participation;low resource degraded quality document image binarization – domain adaptation is the way;a globally-connected and trainable hierarchical fine-attention generative adversarial network based adversarial defense;and overcoming label noise for source-free unsupervised video domain adaptation.

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8th National conference on computer vision, Pattern Recognition, image processing, and graphics, NCVPRIPG 2023

8th National Conference on Computer Vision, Pattern Recognit...

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8th National conference on computer vision, Pattern Recognition, image processing, and graphics, NCVPRIPG 2023

ISBN: (纸本)9789819752119

the proceedings contain 18 papers. the special focus in this conference is on computer vision, Pattern Recognition, image processing, and graphics. the topics include: RGB to Chlorophyll Fluorescence image Reconstruction of Maize for Plant Phenotyping;novel Unsupervised Disease Segmentation Framework Based on Clustering;YOLOv5-MasselNet: In-Field Maize Tassel Detection and Density Estimation Using YOLOv5;MuSiC V1.0: A Software Solution for Automated Mustard Silique Count Using YOLOv5;taPaSe: Tanjore Paddy Seed Dataset;processing 3D Point Clouds for High-throughput Plant Phenotyping;a Deep Learning-Driven Contactless Finger Recognition System;deep Features for Contactless Fingerprint Presentation Attack Detection: Can they Be Generalized?;unlocking Communication: Exploring Hand Gesture-Based Interaction in a Code-Mixed Conversational Speech-to-indian-Sign-Language Translator;a Touchless Palm-Photo Recognition System for Mobile and Handheld Devices;detection of Palmprint from Contactless Smartphone-Based Video Hand Dataset;improved Localization of Knuckle Regions for Contactless Acquisition;NCVPRIPG 2023 Summer Challenge on Writer Verification;C4MTS: Challenge on Categorizing Missing Traffic Signs from Contextual Cues;dePondFi’23 Challenge Summary;a Challenge on 3D Reconstruction and Restoration of indian Heritage from Partial and Noisy Scans.

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Novel Unsupervised Disease Segmentation Framework Based on Clustering 8th

Novel Unsupervised Disease Segmentation Framework Based on C...

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8th National conference on computer vision, Pattern Recognition, image processing and graphics-NCVPRIPG

作者： Singh, Rama Kant Aggarwal, Monika Lall, Brejesh Indian Inst Technol Delhi Bharti Sch New Delhi India Indian Inst Technol Delhi CARE New Delhi India Indian Inst Technol Delhi Elect Engg Dept New Delhi India

ISBN: (纸本)9789819752119;9789819752126

Plant disease is a major limiting factor in yield production. Traditionally, biologists rely on manual screening (localisation) of disease symptoms exhibited on plant leaves. However, this is a highly subjective and error-prone analysis. With the advancement of imaging devices, image-based analysis permits high-throughput disease localisation. In this context, state-of-the-art supervised deep learning-based methods have been presented. However, annotation of disease symptoms is time-consuming and is a current bottleneck. To relieve this limitation, we propose a novel unsupervised framework that utilises Cluster weight as well as Group-local Feature-weight learning using iteration in Fuzzy C-Means (CGFFCM) guided via differentiable clustering algorithm for accurate disease localisation. It is to be noted that the proposed framework does not rely on annotated image data. In this paper, we also performed an exhaustive comparison based on different clustering methods to show the efficacy of the proposed framework.

关键词： Disease phenotyping Unsupervised segmentation Differentiable clustering Fuzzy C-means CGFFCM

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NCVPRIPG 2023 Summer Challenge on Writer Verification 8th

NCVPRIPG 2023 Summer Challenge on Writer Verification

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8th National conference on computer vision, Pattern Recognition, image processing and graphics-NCVPRIPG

作者： Prabhat, Gyan Shahid, Abu Gatti, Prajwal Shah, Manan Chutia, Girin Sharma, Arvind Kumar Mishra, Anand Indian Inst Technol Jodhpur Jodhpur Rajasthan India Cashfree Payments India Pvt Ltd Bengaluru India HCL Technol Ltd Chennai Tamil Nadu India

ISBN: (纸本)9789819752119;9789819752126

this report presents the outcomes of the Summer Challenge on Writer Verification, hosted as part of the Eighth National conference on computer vision, Pattern Recognition, image processing, and graphics (NCVPRIPG) held at IIT Jodhpur on July 21-23, 2023. this challenge introduces a novel dataset comprising images of handwritten text contributed by 1,352 unique writers. Predominantly, these images feature handwritten Hindi text, but they also encompass a variety of elements such as numbers, mathematical symbols, and English text. Participants were tasked with developing a model capable of automatically determining whether the text in a given pair of images is authored by the same writer or different writers. the primary objective of this challenge was to advance research in the realm of handwritten text recognition. throughout the competition, we registered 108 teams, with 18 teams submitting results for the validation dataset. Out of these, 13 teams provided submissions for the semi-final dataset. the top six teams from the semi-finals were subsequently invited to compete in the finals. Additional details about the challenge can be found at https://***/challenges/wv2023/.

关键词： Writer verification Handwritten text Indic language Document analysis Handwritten text recognition

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A Challenge on 3D Reconstruction and Restoration of indian Heritage from Partial and Noisy Scans 8th

A Challenge on 3D Reconstruction and Restoration of Indian H...

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8th National conference on computer vision, Pattern Recognition, image processing and graphics-NCVPRIPG

作者： Pandey, Atharva Yadav, Vishal Karthikeyan, Akash Solanki, Deepanshu Nagar, Rajendra IIT Jodhpur Jodhpur Rajasthan India Thiagarajar Coll Engn Madurai Tamil Nadu India

ISBN: (纸本)9789819752119;9789819752126

the problem of 3D Reconstruction and restoration of indian heritage sites is a classical 3D computer vision problem which has been addressed in the indian vision and graphics research communities. the major focus of these approaches has been to reconstruct a point cloud model of the heritage sites from multiple colored images captured from different viewpoints. this essentially requires solving the structure from motion problem to be solved. this becomes a challenging problem to solve for large scale architectural sites. With the emergence of 3D scanners, we can obtain partial 3D scans of a site from different viewpoints. then, themain problem to solve is to fuse these noisy and partial 3Dscans to obtain the complete 3D model of the underlying surface of the heritage site. the problem of reconstructing the complete 3D model from the partial 3D scan can be solved using classical approaches as well as learning based approaches. Using machine learning based approaches in the context of indian heritage may suffer from the limited training dataset availability. Also, the order of points representing the 3D model of such sites can be in millions. therefore, reconstructing such high resolution 3D models using neural network may demand high-end parallel computing facility.

关键词： Heritage site restoration Point cloud registration Feature based registration

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Unlocking Communication: Exploring Hand Gesture-Based Interaction in a Code-Mixed Conversational Speech-to-indian-Sign-Language Translator 8th

Unlocking Communication: Exploring Hand Gesture-Based Intera...

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8th National conference on computer vision, Pattern Recognition, image processing and graphics-NCVPRIPG

作者： Saini, Neelam Mishra, Anand Indian Inst Technol Jodhpur Jodhpur Rajasthan India

ISBN: (纸本)9789819752119;9789819752126

Communication plays a vital role in society and is considered an essential life skill. However, individuals with hearing disabilities often encounter challenges when interacting with others, leading to feelings of isolation and reduced self-confidence. Sign language, a combination of manual gestures and facial expressions, serves as a means of communication for individuals with hearing and speaking disorders. Ordinary individuals are often unaware of sign language, making communication with them difficult. Additionally, the increasing prevalence of Code-Mixed languages, where multiple languages are used within a single sentence, poses a challenge for existing speech-to-sign translating systems to accurately recognize the code-mixed languages and generate the corresponding sign language. In this paper, we propose a novel system that facilitates communication between individuals with hearing impairments and those who can speak, specifically targeting code-mixed indian-English languages. Our system initially converts code-mixed speech to text and subsequently maps the generated text to the appropriate indian Sign Language, thereby enabling effective communication between these two user groups.

关键词： Speech-to-sign language conversion indian sign language Code-mixing Multilingual speech Hand-gesture interaction

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RGB to Chlorophyll Fluorescence image Reconstruction of Maize for Plant Phenotyping 8th

RGB to Chlorophyll Fluorescence Image Reconstruction of Maiz...

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8th National conference on computer vision, Pattern Recognition, image processing and graphics-NCVPRIPG

作者： Shukla, Ankit Upadhyay, Avinash Sharma, Manoj Saini, Anil Bennett Univ Greater Noida India CSIR CEERI Pilani Rajasthan India

ISBN: (纸本)9789819752119;9789819752126

the advancement in imaging devices has permitted high-throughput study of plant traits also termed as plant phenotyping. In this context, among the different imaging modalities employed in plant phenotyping, chlorophyll fluorescence imaging provides accurate characterisation of crucial plant traits such as photosynthetic efficiency, water use efficiency and nutrients use efficiency to name a few. However, chlorophyll fluorescence imaging is complex and expensive in contrast to widely adopted visible (RGB) images. this limits the reliable study of the aforementioned plant traits. To relieve this limitation, chlorophyll fluorescence image reconstruction algorithms from widely available visible images are a prime solution. thus in this paper, we propose a domain translation-based approach using cycle consistency loss for chlorophyll fluorescence image reconstruction from RGB images. the experimental results on the maize dataset demonstrate the efficiency of our approach with respect to this novel application.

关键词： Chlorophyll fluorescence image GAN Deep learning Domain translation Plant phenotyping Maize

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Detection of Palmprint from Contactless Smartphone-Based Video Hand Dataset 8th

Detection of Palmprint from Contactless Smartphone-Based Vid...

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8th National conference on computer vision, Pattern Recognition, image processing and graphics-NCVPRIPG

作者： Chodvadiya, Charulkumar Singh, Kinshuk Gaurav Vyas, Ritesh Pandit Deendayal Energy Univ Gandhinagar Gujarat India

ISBN: (纸本)9789819752119;9789819752126

A fast-expanding topic is the study of palmprint biometric identification in contactless scenario, which uses techniques from computer vision and machine learning to identify and authenticate people. In this study, we utilized a handcrafted video dataset with 60 distinct classes, each labelled as either a left or right hand, to investigate palmprint detection and matching tasks. the dataset showcases various variations in palmprint patterns, like distance from the sensor, orientation, finger positioning, and deformation, making it an ideal candidate for the development of robust and accurate palmprint recognition models. the major goal of the study is to identify palmprints in the video collection and match them with the right class or pattern. To accomplish this task, different machine learning (ML) and deep learning (DL) models were trained and evaluated. To find the best method for palmprint identification in a contactless manner, the accuracy of each model was tested. In conclusion, our study adds to the expanding body of knowledge on biometric palmprint identification and introduces a fresh handmade video dataset that can be used to compare the effectiveness of various models.

关键词： Palmprint biometric identification computer vision Deep learning model Palmprint patterns Transfer learning

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