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...
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.
this report presents the outcomes of the Summer Challenge on Writer Verification, hosted as part of the Eighth National conference on computervision, Pattern Recognition, imageprocessing, and graphics (NCVPRIPG) hel...
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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 computervision, Pattern Recognition, imageprocessing, 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/.
the proceedings contain 18 papers. the special focus in this conference is on computervision, Pattern Recognition, imageprocessing, and graphics. the topics include: RGB to Chlorophyll Fluorescence image Reconstruct...
ISBN:
(纸本)9789819752119
the proceedings contain 18 papers. the special focus in this conference is on computervision, Pattern Recognition, imageprocessing, 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.
Many innovative text input methods exist but are scarce in indian languages. In this paper, we aim to explore a novel text input method for the Malayalam language. this method is gesture-based, where specific hand mov...
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ISBN:
(纸本)9783031808319;9783031808326
Many innovative text input methods exist but are scarce in indian languages. In this paper, we aim to explore a novel text input method for the Malayalam language. this method is gesture-based, where specific hand movements using the natural demarcations of the hand are mapped to particular characters, which enables typing. this is implemented using an imageprocessing program to track key points on our hands, which allows us to distinguish between different gestures accurately. We conducted a study to identify which gestures provide higher accuracy, and least confusion. Using the results, we mapped the gestures to Malayalam and conducted an empirical longitudinal study, which analyzed the speed and accuracy of this prototype. this method yielded a 40+ CPM, which is comparable to similar text input studies in other languages. this technology can be further developed to assist users in various ways, such as providing a communication guide or aiding in daily activities.
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 e...
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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. Withthe 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.
the problem of 3D Reconstruction and restoration of indian heritage sites is a classical 3D computervision problem which has been addressed in the indianvision and graphics research communities. the major focus of t...
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ISBN:
(纸本)9789819752119;9789819752126
the problem of 3D Reconstruction and restoration of indian heritage sites is a classical 3D computervision problem which has been addressed in the indianvision 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. Withthe 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.
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 iso...
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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 withthem 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.
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, chlorophy...
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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.
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