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Mor A, Kumar M, Chaudhury S. Smart City Umbrella Ontology :Context -Driven Framework For Traffic Planning. FORUM FOR INFORMATION RETRIEVAL EVALUATION 2021. [DOI: 10.1145/3503162.3503170] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/19/2023]
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Bhugra S, Kaushik V, Mateos IC, Chaudhury S, Lall B. Unsupervised Learning of Affinity for Image Segmentation: An Inpainting based Approach. 2021 36TH INTERNATIONAL CONFERENCE ON IMAGE AND VISION COMPUTING NEW ZEALAND (IVCNZ) 2021. [DOI: 10.1109/ivcnz54163.2021.9653321] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/19/2023]
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Sharma R, Sharma M, Shukla A, Chaudhury S. Conditional Deep 3D-Convolutional Generative Adversarial Nets for RGB-D Generation. MATHEMATICAL PROBLEMS IN ENGINEERING 2021; 2021:1-8. [DOI: 10.1155/2021/8358314] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/19/2023]
Abstract
Generation of synthetic data is a challenging task. There are only a few significant works on RGB video generation and no pertinent works on RGB-D data generation. In the present work, we focus our attention on synthesizing RGB-D data which can further be used as dataset for various applications like object tracking, gesture recognition, and action recognition. This paper has put forward a proposal for a novel architecture that uses conditional deep 3D-convolutional generative adversarial networks to synthesize RGB-D data by exploiting 3D spatio-temporal convolutional framework. The proposed architecture can be used to generate virtually unlimited data. In this work, we have presented the architecture to generate RGB-D data conditioned on class labels. In the architecture, two parallel paths were used, one to generate RGB data and the second to synthesize depth map. The output from the two parallel paths is combined to generate RGB-D data. The proposed model is used for video generation at 30 fps (frames per second). The frame referred here is an RGB-D with the spatial resolution of 512 × 512.
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Pareek V, Chaudhury S, Singh S. Hybrid 3DCNN-RBM Network for Gas Mixture Concentration Estimation With Sensor Array. IEEE SENSORS JOURNAL 2021; 21:24263-24273. [DOI: 10.1109/jsen.2021.3105414] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/19/2023]
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Prakash J, Saldanha D, Chaudhury S, Chatterjee K, Srivastava K. All, that was not bad in COVID crisis: Pearls of goodness from the furls of furnace. Ind Psychiatry J 2021; 30:S1-S2. [PMID: 34908654 PMCID: PMC8611528 DOI: 10.4103/0972-6748.328779] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/25/2021] [Revised: 09/05/2021] [Accepted: 09/12/2021] [Indexed: 11/04/2022] Open
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Pareek V, Chaudhury S. Deep learning-based gas identification and quantification with auto-tuning of hyper-parameters. Soft comput 2021. [DOI: 10.1007/s00500-021-06222-1] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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Pareek V, Chaudhury S, Singh S. Online Pattern Recognition of Time-series Gas Sensor Data with Adaptive 2D-CNN Ensemble. 2021 11TH IEEE INTERNATIONAL CONFERENCE ON INTELLIGENT DATA ACQUISITION AND ADVANCED COMPUTING SYSTEMS: TECHNOLOGY AND APPLICATIONS (IDAACS) 2021. [DOI: 10.1109/idaacs53288.2021.9660930] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/19/2023]
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Pareek V, Chaudhury S, Singh S. Gas Discrimination & Quantification using Sensor Array with 3D Convolution Regression Dual Network. 2021 11TH IEEE INTERNATIONAL CONFERENCE ON INTELLIGENT DATA ACQUISITION AND ADVANCED COMPUTING SYSTEMS: TECHNOLOGY AND APPLICATIONS (IDAACS) 2021. [DOI: 10.1109/idaacs53288.2021.9660938] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/19/2023]
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Malladi SPK, Mukhopadhyay J, Larabi C, Chaudhury S. Lighter and Faster Cross-Concatenated Multi-Scale Residual Block Based Network for Visual Saliency Prediction. 2021 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP) 2021. [DOI: 10.1109/icip42928.2021.9506710] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/19/2023]
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Pal S, Maity S, Balachandran S, Chaudhury S. "In-vitro Effects of Chlorpyrifos and Monocrotophos on the Activity of Acetylcholinesterase (AChE) in Different Tissues of Apple Snail Pila globosa (Swainson, 1822)". NATURE ENVIRONMENT AND POLLUTION TECHNOLOGY 2021. [DOI: 10.46488/nept.2021.v20i03.037] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
The impact of two organophosphorus insecticides [Chlorpyrifos (CPF) and Monocrotophos (MCP)] on non-target wild natural gastropod, Pila globosa (apple snail) from the paddy fields was studied. The activity of acetylcholinesterase (AChE) was monitored on foot-muscle and hepatopancreas tissues of control and exposed snails. In the foot- muscle AChE inhibition progressed and reached 54.19% and 63.13% of the control, whereas, the AChE inhibition in the hepatopancreas reached 46.96% and 53.67% over control after 48 hours of exposure to 1.5 mL.L-1 and 2.5 mL.L-1 CPF respectively. After 48 hours of MCP exposure at 1.5 mL.L-1 and 2.5 mL.L-1 separately, the AChE inhibition of foot muscle was 49.07% and 57.59% respectively while in hepatopancreas it was 44.65% and 48.84% respectively. Our results show more inhibition of AChE activities on the foot-muscle than hepatopancreas in a concentration and time-dependent manner with greater severity by CPF in comparison to MCP. AChE inhibition increased with the increasing exposure time.
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Pareek V, Prajesh R, Chaudhury S, Singh S. Smart Gas Sensing using Single MOS Gas Sensor with Adaptive Gradient Boosting. 2021 JOINT 10TH INTERNATIONAL CONFERENCE ON INFORMATICS, ELECTRONICS & VISION (ICIEV) AND 2021 5TH INTERNATIONAL CONFERENCE ON IMAGING, VISION & PATTERN RECOGNITION (ICIVPR) 2021. [DOI: 10.1109/icievicivpr52578.2021.9564180] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/19/2023]
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Madan S, Chaudhury S, Gandhi TK. Automated detection of COVID-19 on a small dataset of chest CT images using metric learning. 2021 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN) 2021. [DOI: 10.1109/ijcnn52387.2021.9533831] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/19/2023]
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Rituraj, Tiwari A, Chaudhury S, Singh S, Saurav S. Video Classification using SlowFast Network via Fuzzy rule. 2021 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ-IEEE) 2021. [DOI: 10.1109/fuzz45933.2021.9494542] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/19/2023]
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Pandey CK, Singh A, Chaudhury S. A simulation-based analysis of effect of interface trap charges on dc and analog/HF performances of dielectric pocket SOI-Tunnel FET. MICROELECTRONICS RELIABILITY 2021; 122:114166. [DOI: 10.1016/j.microrel.2021.114166] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/19/2023]
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Singh P, Chaudhury S, Panigrahi BK. Hybrid MPSO-CNN: Multi-level Particle Swarm optimized hyperparameters of Convolutional Neural Network. SWARM AND EVOLUTIONARY COMPUTATION 2021; 63:100863. [DOI: 10.1016/j.swevo.2021.100863] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/19/2023]
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Pahal N, Lall B, Chaudhury S. An Ontology Representation Language for Multimedia Event Applications. JOURNAL OF WEB ENGINEERING 2021. [DOI: 10.13052/jwe1540-9589.2021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/19/2023]
Abstract
This paper presents formalization of a new Multimedia Web Ontology Language (E-MOWL) to handle events with media depictions. The temporal, spatial and entity aspects that are implicitly linked to an event are represented through this language to model the context of events. The already existing Multimedia Web Ontology Language (MOWL) can be leveraged for perceptual modelling of a domain, where the concepts manifest into media patterns in the multimedia document and helps in semantic processing of the contents. The language E-MOWL provides a rich method for representing knowledge corresponding to a specific domain wherein the context specifies the intended meaning of each element of the domain of discourse; an element in different context may correspond to different functional role. The context information associated with an event ties the audiovisual data with event related aspects. All these aspects when considered altogether provide the evidence and contribute towards recognizing an event from multimedia documents. The language also enables reasoning with the uncertainty associated with the events and is organized in the form of Bayesian Network (BN). The media items that are semantically relevant can be assimilated together on the basis of their association with events. We have demonstrated the efficacy of our approach by utilizing an ontology for the entertainment category in news domain to offer an application \textit{news aggregation} and event-based book recommendations.
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Tripathi A, Srivastava S, Lall B, Chaudhury S. Using Scene Graphs for Detecting Visual Relationships. 2020 25TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION (ICPR) 2021. [DOI: 10.1109/icpr48806.2021.9412337] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/19/2023]
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Ralekar C, Gandhi TK, Chaudhury S. Collaborative Human Machine Attention Module for Character Recognition. 2020 25TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION (ICPR) 2021. [DOI: 10.1109/icpr48806.2021.9413229] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/19/2023]
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Bhugra S, Garg K, Chaudhury S, Lall B. A Hierarchical Framework for Leaf Instance Segmentation: Application to Plant Phenotyping. 2020 25TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION (ICPR) 2021. [DOI: 10.1109/icpr48806.2021.9411981] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/19/2023]
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Mittal S, Venugopal VK, Agarwal VK, Malhotra M, Chatha JS, Kapur S, Gupta A, Batra V, Majumdar P, Malhotra A, Thakral K, Chhabra S, Vatsa M, Singh R, Chaudhury S. A Novel Abnormality Annotation Database for COVID-19 Affected Frontal Lung X-rays.. [DOI: 10.1101/2021.01.07.21249323] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/19/2023]
Abstract
AbstractPurposeTo advance the usage of CXRs as a viable solution for efficient COVID-19 diagnostics by providing large-scale annotations of the abnormalities in frontal CXRs in BIMCV-COVID19+ database, and to provide a robust evaluation mechanism to facilitate its usage.Materials and MethodsWe provide the abnormality annotations in frontal CXRs by creating bounding boxes. The frontal CXRs are a part of the existing BIMCV-COVID19+ database. We also define four different protocols for robust evaluation of semantic segmentation and classification algorithms. Finally, we benchmark the defined protocols and report the results using popular deep learning models as a part of this study.ResultsFor semantic segmentation, Mask-RCNN performs the best among all the models with a DICE score of 0.43 ± 0.01. For classification, we observe that MobileNetv2 yields the best results for 2-class and 3-class classification. We also observe that deep models report a lower performance for classifying other classes apart from the COVID class.ConclusionBy making the annotated data and protocols available to the scientific community, we aim to advance the usage of CXRs as a viable solution for efficient COVID-19 diagnostics. This large-scale data will be useful for ML algorithms and can be used for learning radiological patterns observed in COVID-19 patients. Further, the protocols will facilitate ML practitioners for unified large-scale evaluation of their algorithms.Data Availability StatementThe data associated with this work is available here : Radiologists’ Annotations on COVID-19+ X-rays https://osf.io/b35xu/ via @OSFramework andhttp://covbase4all.igib.res.in/.
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Chaudhury S, Nanda N, Tyagi B. Green-Field Versus Merger and Acquisition: Role of FDI in Economic Growth of South Asia. TRADE, INVESTMENT AND ECONOMIC GROWTH 2021:157-167. [DOI: 10.1007/978-981-33-6973-3_10] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/19/2023]
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Gupta S, Mukherjee P, Chaudhury S, Lall B, Sanisetty H. DFTNet: Deep Fish Tracker With Attention Mechanism in Unconstrained Marine Environments. IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 2021; 70:1-13. [DOI: 10.1109/tim.2021.3109731] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/19/2023]
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Madan S, Gandhi T, Chaudhury S. Bone Age Assessment for Lower Age Groups Using Triplet Network in Small Dataset of Hand X-Rays. INTELLIGENT HUMAN COMPUTER INTERACTION 2021:142-153. [DOI: 10.1007/978-3-030-68449-5_15] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/19/2023]
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Sinha H, Kumar S, Chaudhury S. A Variational Training Perspective to GANs for Hyperspectral Image Generation. ADVANCES IN INTELLIGENT SYSTEMS AND COMPUTING 2021:417-429. [DOI: 10.1007/978-981-16-2709-5_32] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/19/2023]
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Mohan R, Chaudhury S, Lall B. Temporal Causal Modelling on Large Volume Enterprise Data. IEEE TRANSACTIONS ON BIG DATA 2021:1-1. [DOI: 10.1109/tbdata.2021.3053879] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/19/2023]
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