148 citations · 310 across the 24 of their papers we have counts for
26 papers
Explainable Rule Mining of IPv6 Extension-Header Presence Patterns from Paired-Vantage Captures
Priyanka Sinha, Nikolaos Kekatos, Stylianos Basagiannis +5
IPv6 extension headers (EHs), such as fragmentation, segment routing, and in-situ telemetry, are operationally important yetwidely dropped in transit, and characterising their beha…
On the Evaluation of User Privacy in Deep Neural Networks using Timing Side Channel
Shubhi Shukla, Manaar Alam, Sarani Bhattacharya +2
Recent Deep Learning (DL) advancements in solving complex real-world tasks have led to its widespread adoption in practical applications. However, this opportunity comes with signi…
Texture Aware Autoencoder Pre-training And Pairwise Learning Refinement For Improved Iris Recognition
Manashi Chakraborty, Aritri Chakraborty, Prabir Kumar Biswas +1
This paper presents a texture aware end-to-end trainable iris recognition system, specifically designed for datasets like iris having limited training data. We build upon our previ…
Multilingual Audio-Visual Smartphone Dataset And Evaluation
Hareesh Mandalapu, Aravinda Reddy P N, Raghavendra Ramachandra +4
Smartphones have been employed with biometric-based verification systems to provide security in highly sensitive applications. Audio-visual biometrics are getting popular due to th…
Explaining Outcomes of Multi-Party Dialogues using Causal Learning
Priyanka Sinha, Pabitra Mitra, Antonio Anastasio Bruto da Costa +1
Multi-party dialogues are common in enterprise social media on technical as well as non-technical topics. The outcome of a conversation may be positive or negative. It is important…
Audio-Visual Biometric Recognition and Presentation Attack Detection: A Comprehensive Survey
Hareesh Mandalapu, P N Aravinda Reddy, Raghavendra Ramachandra +4
Biometric recognition is a trending technology that uses unique characteristics data to identify or verify/authenticate security applications. Amidst the classically used biometric…
Alternating Direction Method of Multipliers for Quantization
Tianjian Huang, Prajwal Singhania, Maziar Sanjabi +2
Quantization of the parameters of machine learning models, such as deep neural networks, requires solving constrained optimization problems, where the constraint set is formed by t…
Antarjami: Exploring psychometric evaluation through a computer-based game
Anirban Lahiri, Utanko Mitra, Sunreeta Sen +6
A number of questionnaire based psychometric testing frameworks are globally for example OCEAN (Five factor) indicator, MBTI (Myers Brigg Type Indicator) etc. However, questionnair…
Unsupervised Pre-trained, Texture Aware And Lightweight Model for Deep Learning-Based Iris Recognition Under Limited Annotated Data
Manashi Chakraborty, Mayukh Roy, Prabir Kumar Biswas +1
In this paper, we present a texture aware lightweight deep learning framework for iris recognition. Our contributions are primarily three fold. Firstly, to address the dearth of la…
ExTra: Transfer-guided Exploration
Anirban Santara, Rishabh Madan, Balaraman Ravindran +1
In this work we present a novel approach for transfer-guided exploration in reinforcement learning that is inspired by the human tendency to leverage experiences from similar encou…
PUNCH: Positive UNlabelled Classification based information retrieval in Hyperspectral images
Anirban Santara, Jayeeta Datta, Sourav Sarkar +3
Hyperspectral images of land-cover captured by airborne or satellite-mounted sensors provide a rich source of information about the chemical composition of the materials present in…
Segmentation of Lumen and External Elastic Laminae in Intravascular Ultrasound Images using Ultrasonic Backscattering Physics Initialized Multiscale Random Walks
Debarghya China, Pabitra Mitra, Debdoot Sheet
Coronary artery disease accounts for a large number of deaths across the world and clinicians generally prefer using x-ray computed tomography or magnetic resonance imaging for loc…
SUMNet: Fully Convolutional Model for Fast Segmentation of Anatomical Structures in Ultrasound Volumes
Sumanth Nandamuri, Debarghya China, Pabitra Mitra +1
Ultrasound imaging is generally employed for real-time investigation of internal anatomy of the human body for disease identification. Delineation of the anatomical boundary of org…
UltraCompression: Framework for High Density Compression of Ultrasound Volumes using Physics Modeling Deep Neural Networks
Debarghya China, Francis Tom, Sumanth Nandamuri +4
Ultrasound image compression by preserving speckle-based key information is a challenging task. In this paper, we introduce an ultrasound image compression framework with the abili…
Visual Attention for Behavioral Cloning in Autonomous Driving
Sourav Pal, Tharun Mohandoss, Pabitra Mitra
The goal of our work is to use visual attention to enhance autonomous driving performance. We present two methods of predicting visual attention maps. The first method is a supervi…
Improving Consistency and Correctness of Sequence Inpainting using Semantically Guided Generative Adversarial Network
Avisek Lahiri, Arnav Jain, Prabir Kumar Biswas +1
Contemporary benchmark methods for image inpainting are based on deep generative models and specifically leverage adversarial loss for yielding realistic reconstructions. However,…
BASS Net: Band-Adaptive Spectral-Spatial Feature Learning Neural Network for Hyperspectral Image Classification
Anirban Santara, Kaustubh Mani, Pranoot Hatwar +4
Deep learning based landcover classification algorithms have recently been proposed in literature. In hyperspectral images (HSI) they face the challenges of large dimensionality, s…
Recurrent Memory Addressing for describing videos
Arnav Kumar Jain, Abhinav Agarwalla, Kumar Krishna Agrawal +1
In this paper, we introduce Key-Value Memory Networks to a multimodal setting and a novel key-addressing mechanism to deal with sequence-to-sequence models. The proposed model natu…
WEPSAM: Weakly Pre-Learnt Saliency Model
Avisek Lahiri, Sourya Roy, Anirban Santara +2
Visual saliency detection tries to mimic human vision psychology which concentrates on sparse, important areas in natural image. Saliency prediction research has been traditionally…
Visual saliency detection: a Kalman filter based approach
Sourya Roy, Pabitra Mitra
In this paper we propose a Kalman filter aided saliency detection model which is based on the conjecture that salient regions are considerably different from our "visual expectatio…
Visualization Regularizers for Neural Network based Image Recognition
Biswajit Paria, Vikas Reddy, Anirban Santara +1
The success of deep neural networks is mostly due their ability to learn meaningful features from the data. Features learned in the hidden layers of deep neural networks trained in…
Ensemble of Deep Convolutional Neural Networks for Learning to Detect Retinal Vessels in Fundus Images
Debapriya Maji, Anirban Santara, Pabitra Mitra +1
Vision impairment due to pathological damage of the retina can largely be prevented through periodic screening using fundus color imaging. However the challenge with large scale sc…
Faster learning of deep stacked autoencoders on multi-core systems using synchronized layer-wise pre-training
Anirban Santara, Debapriya Maji, DP Tejas +2
Deep neural networks are capable of modelling highly non-linear functions by capturing different levels of abstraction of data hierarchically. While training deep networks, first t…
A dense subgraph based algorithm for compact salient image region detection
Souradeep Chakraborty, Pabitra Mitra
We present an algorithm for graph based saliency computation that utilizes the underlying dense subgraphs in finding visually salient regions in an image. To compute the salient re…