Search Results for author:
Found 7 papers, 4 papers with code
Online Ensemble Model Compression using Knowledge Distillation
This paper presents a novel knowledge distillation based model compression framework consisting of a student ensemble.
Attentive CutMix: An Enhanced Data Augmentation Approach for Deep Learning Based Image Classification
In this paper, we propose Attentive CutMix, a naturally enhanced augmentation strategy based on CutMix.
O-MedAL: Online Active Deep Learning for Medical Image Analysis
Our online method enhances performance of its underlying baseline deep network.
An Empirical Analysis of Deep Audio-Visual Models for Speech Recognition
In this project, we worked on speech recognition, specifically predicting individual words based on both the video frames and audio.
MedAL: Deep Active Learning Sampling Method for Medical Image Analysis
Active learning techniques can be used to minimize the number of required training labels while maximizing the model's performance. In this work, we propose a novel sampling method that queries the unlabeled examples that maximize the average distance to all training set examples in a learned feature space.
A fully automated framework for lung tumour detection, segmentation and analysis
This paper introduces a novel fully automated framework which helps to detect and segment tumour, if present in a lung CT scan series.
Grammatical facial expression recognition using customized deep neural network architecture
This is carried out through recognition of facial expressions, which accompany the hand signs used in this language.
Facial Expression Recognition
Facial Expression Recognition (FER)
