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KANJAR DE
KANJAR DE
Fraunhofer Institute for Telecommunications - Heinrich-Hertz-Institut, HHI
Verified email at hhi.fraunhofer.de
Title
Cited by
Cited by
Year
Image sharpness measure for blurred images in frequency domain
K De, V Masilamani
Procedia Engineering 64, 149-158, 2013
1712013
Movie recommendation system using sentiment analysis from microblogging data
S Kumar, K De, PP Roy
IEEE Transactions on Computational Social Systems 7 (4), 915-923, 2020
1622020
Impact of colour on robustness of deep neural networks
K De, M Pedersen
Proceedings of the IEEE/CVF international conference on computer vision, 21-30, 2021
412021
An intelligent recommendation system using gaze and emotion detection
S Jaiswal, S Virmani, V Sethi, K De, PP Roy
Multimedia Tools and Applications 78, 14231-14250, 2019
412019
A new no-reference image quality measure for blurred images in spatial domain
K De, V Masilamani
Journal of Image and Graphics 1 (1), 39-42, 2013
242013
Rethinking the methods and algorithms for inner speech decoding and making them reproducible
F Simistira Liwicki, V Gupta, R Saini, K De, M Liwicki
NeuroSci 3 (2), 226-244, 2022
112022
Zero shot learning based script identification in the wild
P Keserwani, K De, PP Roy, U Pal
2019 international conference on document analysis and recognition (ICDAR …, 2019
112019
Nordic Vehicle Dataset (NVD): Performance of vehicle detectors using newly captured NVD from UAV in different snowy weather conditions.
H Mokayed, A Nayebiastaneh, K De, S Sozos, O Hagner, B Backe
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2023
102023
No-reference image sharpness measure using discrete cosine transform statistics and multivariate adaptive regression splines for robotic applications
K De, V Masilamani
Procedia computer science 133, 268-275, 2018
102018
Fast no-reference image sharpness measure for blurred images in discrete cosine transform domain
K De, V Masilamani
2016 IEEE Students’ Technology Symposium (TechSym), 256-261, 2016
92016
No-reference image contrast measure using image statistics and random forest
K De, V Masilamani
Multimedia tools and applications 76, 18641-18656, 2017
82017
Perceptual conditional generative adversarial networks for end-to-end image colourization
SS Halder, K De, PP Roy
Computer Vision–ACCV 2018: 14th Asian Conference on Computer Vision, Perth …, 2019
72019
A no-reference image quality measure for blurred and compressed images using sparsity features
K De, V Masilamani
Cognitive Computation 10 (6), 980-990, 2018
72018
No-reference image quality measure for images with multiple distortions using random forests for multi method fusion
K De, V Masilamani
Image Analysis and Stereology 37 (2), 105-117, 2018
72018
AIM 2024 challenge on compressed video quality assessment: Methods and results
M Smirnov, A Gushchin, A Antsiferova, D Vatolin, R Timofte, Z Jia, ...
arXiv preprint arXiv:2408.11982, 2024
52024
Bimodal electroencephalography-functional magnetic resonance imaging dataset for inner-speech recognition
F Simistira Liwicki, V Gupta, R Saini, K De, N Abid, S Rakesh, ...
Scientific Data 10 (1), 378, 2023
5*2023
Can self-supervised representation learning methodswithstand distribution shifts and corruptions?
PC Chhipa, JR Holmgren, K De, R Saini, M Liwicki
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023
52023
Image quality assessment for blurred images using nonsubsampled contourlet transform features
K De, V Masilamani
Journal of Computers 12 (2), 156-164, 2017
52017
Eai-net: Effective and accurate iris segmentation network
S Rajpal, D Sadhya, K De, PP Roy, B Raman
Pattern Recognition and Machine Intelligence: 8th International Conference …, 2019
42019
Functional Knowledge Transfer with Self-supervised Representation Learning
PC Chhipa, M Chopra, G Mengi, V Gupta, R Upadhyay, MS Chippa, K De, ...
2023 IEEE International Conference on Image Processing (ICIP), 3339-3343, 2023
32023
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