118 citations · 151 across the 10 of their papers we have counts for
10 papers
Iterative collaborative routing among equivariant capsules for transformation-robust capsule networks
Sai Raam Venkataraman, S. Balasubramanian, R. Raghunatha Sarma
Transformation-robustness is an important feature for machine learning models that perform image classification. Many methods aim to bestow this property to models by the use of da…
Robustcaps: a transformation-robust capsule network for image classification
Sai Raam Venkataraman, S. Balasubramanian, R. Raghunatha Sarma
Geometric transformations of the training data as well as the test data present challenges to the use of deep neural networks to vision-based learning tasks. In order to address th…
Dynamic Adaptive Threshold based Learning for Noisy Annotations Robust Facial Expression Recognition
Darshan Gera, Naveen Siva Kumar Badveeti, Bobbili Veerendra Raj Kumar +1
The real-world facial expression recognition (FER) datasets suffer from noisy annotations due to crowd-sourcing, ambiguity in expressions, the subjectivity of annotators and inter-…
Can you even tell left from right? Presenting a new challenge for VQA
Sai Raam Venkatraman, Rishi Rao, S. Balasubramanian +2
Visual Question Answering (VQA) needs a means of evaluating the strengths and weaknesses of models. One aspect of such an evaluation is the evaluation of compositional generalisati…
Imponderous Net for Facial Expression Recognition in the Wild
Darshan Gera, S. Balasubramanian
Since the renaissance of deep learning (DL), facial expression recognition (FER) has received a lot of interest, with continual improvement in the performance. Hand-in-hand with pe…
Affect Expression Behaviour Analysis in the Wild using Spatio-Channel Attention and Complementary Context Information
Darshan Gera, S Balasubramanian
Facial expression recognition(FER) in the wild is crucial for building reliable human-computer interactive systems. However, current FER systems fail to perform well under various…
Learning Compositional Structures for Deep Learning: Why Routing-by-agreement is Necessary
Sai Raam Venkatraman, Ankit Anand, S. Balasubramanian +1
A formal description of the compositionality of neural networks is associated directly with the formal grammar-structure of the objects it seeks to represent. This formal grammar-s…
Landmark Guidance Independent Spatio-channel Attention and Complementary Context Information based Facial Expression Recognition
Darshan Gera, S Balasubramanian
A recent trend to recognize facial expressions in the real-world scenario is to deploy attention based convolutional neural networks (CNNs) locally to signify the importance of fac…
Building Deep, Equivariant Capsule Networks
Sairaam Venkatraman, S. Balasubramanian, R. Raghunatha Sarma
Capsule networks are constrained by the parameter-expensive nature of their layers, and the general lack of provable equivariance guarantees. We present a variation of capsule netw…
RES-SE-NET: Boosting Performance of Resnets by Enhancing Bridge-connections
Varshaneya V, Balasubramanian S, Darshan Gera
One of the ways to train deep neural networks effectively is to use residual connections. Residual connections can be classified as being either identity connections or bridge-conn…