Abhay Kumar

Orcid: 0000-0003-4853-0951

Affiliations:
  • Walmart, Sunnyvale, CA, USA
  • University of Wisconsin-Madison, WI, USA (2019 - 2021)
  • Samsung R&D Institute India, Bangalore, India (2016 - 2019)
  • Indian Institute of Technology Kanpur, India (2012 - 2016)


According to our database1, Abhay Kumar authored at least 13 papers between 2015 and 2020.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Other 

Links

Online presence:

On csauthors.net:

Bibliography

2020
Input-conditioned convolution filters for feature learning.
Proceedings of the MoMM '20: The 18th International Conference on Advances in Mobile Computing and Multimedia, Chiang Mai, Thailand, November 30, 2020

2019
MTCNET: Multi-task Learning Paradigm for Crowd Count Estimation.
CoRR, 2019

Visual Context-aware Convolution Filters for Transformation-invariant Neural Network.
CoRR, 2019

Focal Loss based Residual Convolutional Neural Network for Speech Emotion Recognition.
CoRR, 2019

Deep Learning based Emotion Recognition System Using Speech Features and Transcriptions.
CoRR, 2019

From Fully Supervised to Zero Shot Settings for Twitter Hashtag Recommendation.
CoRR, 2019

Exploiting SIFT Descriptor for Rotation Invariant Convolutional Neural Network.
CoRR, 2019

Bidirectional Transformer Based Multi-Task Learning for Natural Language Understanding.
Proceedings of the Natural Language Processing and Information Systems, 2019

Deceptive Reviews Detection Using Deep Learning Techniques.
Proceedings of the Natural Language Processing and Information Systems, 2019

Learning Discriminative Features using Center Loss and Reconstruction as Regularizer for Speech Emotion Recognition.
Proceedings of the Workshop on Artificial Intelligence in Affective Computing, 2019

Emoception: An Inception Inspired Efficient Speech Emotion Recognition Network.
Proceedings of the IEEE Automatic Speech Recognition and Understanding Workshop, 2019

2018
Speech Emotion Recognition Using Spectrogram & Phoneme Embedding.
Proceedings of the 19th Annual Conference of the International Speech Communication Association, 2018

2015
Hybrid maximum depth-kNN method for real time node tracking using multi-sensor data.
Proceedings of the 2015 IEEE International Conference on Communications, 2015


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