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10/13/2022
Reducing Annotation Effort by Identifying and Labeling Contextually Diverse Classes for Semantic Segmentation Under Domain Shift
In Active Domain Adaptation (ADA), one uses Active Learning (AL) to sele...
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09/25/2022
High-Resolution Satellite Imagery for Modeling the Impact of Aridification on Crop Production
The availability of well-curated datasets has driven the success of Mach...
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07/26/2022
Learning Hierarchy Aware Features for Reducing Mistake Severity
Label hierarchies are often available apriori as part of biological taxo...
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05/06/2022
Crop Type Identification for Smallholding Farms: Analyzing Spatial, Temporal and Spectral Resolutions in Satellite Imagery
The integration of the modern Machine Learning (ML) models into remote s...
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01/20/2022
Learning Estimates At The Edge Using Intermittent And Aged Measurement Updates
Cyber Physical Systems (CPS) applications have agents that actuate in th...
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10/30/2021
HIERMATCH: Leveraging Label Hierarchies for Improving Semi-Supervised Learning
Semi-supervised learning approaches have emerged as an active area of re...
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10/20/2021
Does Data Repair Lead to Fair Models? Curating Contextually Fair Data To Reduce Model Bias
Contextual information is a valuable cue for Deep Neural Networks (DNNs)...
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09/30/2021
Impact of Channel Variation on One-Class Learning for Spoof Detection
The value of Spoofing detection in increasing the reliability of the ASV...
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11/23/2020
Modeling Functional Similarity in Source Code with Graph-Based Siamese Networks
Code clones are duplicate code fragments that share (nearly) similar syn...
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08/13/2020
Contextual Diversity for Active Learning
Requirement of large annotated datasets restrict the use of deep convolu...
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06/18/2020
Dissecting Deep Networks into an Ensemble of Generative Classifiers for Robust Predictions
Deep Neural Networks (DNNs) are often criticized for being susceptible t...
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06/03/2020
DGSAC: Density Guided Sampling and Consensus
Robust multiple model fitting plays a crucial role in many computer visi...
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05/06/2020
GraCIAS: Grassmannian of Corrupted Images for Adversarial Security
Input transformation based defense strategies fall short in defending ag...
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05/06/2020
Automatic Detection and Recognition of Individuals in Patterned Species
Visual animal biometrics is rapidly gaining popularity as it enables a n...
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04/22/2020
Pseudo RGB-D for Self-Improving Monocular SLAM and Depth Prediction
Classical monocular Simultaneous Localization And Mapping (SLAM) and the...
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04/20/2020
Intelligent Querying for Target Tracking in Camera Networks using Deep Q-Learning with n-Step Bootstrapping
Surveillance camera networks are a useful infrastructure for various vis...
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07/22/2019
Product of Orthogonal Spheres Parameterization for Disentangled Representation Learning
Learning representations that can disentangle explanatory attributes und...
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07/03/2019
Primate Face Identification in the Wild
Ecological imbalance owing to rapid urbanization and deforestation has a...
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02/19/2019
Geometry of Deep Generative Models for Disentangled Representations
Deep generative models like variational autoencoders approximate the int...
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11/02/2018
Unique Identification of Macaques for Population Monitoring and Control
Despite loss of natural habitat due to development and urbanization, cer...
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07/26/2018
A Reinforcement Learning Approach to Target Tracking in a Camera Network
Target tracking in a camera network is an important task for surveillanc...
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07/10/2018
A Reinforcement Learning Approach to Jointly Adapt Vehicular Communications and Planning for Optimized Driving
Our premise is that autonomous vehicles must optimize communications and...
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06/05/2018
ClusterNet : Semi-Supervised Clustering using Neural Networks
Clustering using neural networks has recently demon- strated promising p...
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05/21/2018
Adversarial Learning of Raw Speech Features for Domain Invariant Speech Recognition
Recent advances in neural network based acoustic modelling have shown si...
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04/27/2018