56 citations · 84 across the 7 of their papers we have counts for
7 papers
MTCNET: Multi-task Learning Paradigm for Crowd Count Estimation
Abhay Kumar, Nishant Jain, Suraj Tripathi +2
We propose a Multi-Task Learning (MTL) paradigm based deep neural network architecture, called MTCNet (Multi-Task Crowd Network) for crowd density and count estimation. Crowd count…
Visual Context-aware Convolution Filters for Transformation-invariant Neural Network
Suraj Tripathi, Abhay Kumar, Chirag Singh
We propose a novel visual context-aware filter generation module which incorporates contextual information present in images into Convolutional Neural Networks (CNNs). In contrast…
Focal Loss based Residual Convolutional Neural Network for Speech Emotion Recognition
Suraj Tripathi, Abhay Kumar, Abhiram Ramesh +2
This paper proposes a Residual Convolutional Neural Network (ResNet) based on speech features and trained under Focal Loss to recognize emotion in speech. Speech features such as S…
Deep Learning based Emotion Recognition System Using Speech Features and Transcriptions
Suraj Tripathi, Abhay Kumar, Abhiram Ramesh +2
This paper proposes a speech emotion recognition method based on speech features and speech transcriptions (text). Speech features such as Spectrogram and Mel-frequency Cepstral Co…
From Fully Supervised to Zero Shot Settings for Twitter Hashtag Recommendation
Abhay Kumar, Nishant Jain, Suraj Tripathi +1
We propose a comprehensive end-to-end pipeline for Twitter hashtags recommendation system including data collection, supervised training setting and zero shot training setting. In…
Learning Discriminative features using Center Loss and Reconstruction as Regularizer for Speech Emotion Recognition
Suraj Tripathi, Abhiram Ramesh, Abhay Kumar +2
This paper proposes a Convolutional Neural Network (CNN) inspired by Multitask Learning (MTL) and based on speech features trained under the joint supervision of softmax loss and c…