Search Results for author:
Found 10 papers, 4 papers with code
DSC-IIT ISM at WNUT-2020 Task 2: Detection of COVID-19 informative tweets using RoBERTa
Social media such as Twitter is a hotspot of user-generated information.
Online Learning under Haphazard Input Conditions: A Comprehensive Review and Analysis
The domain of online learning has experienced multifaceted expansion owing to its prevalence in real-life applications.
Modelling Irregularly Sampled Time Series Without Imputation
Modelling irregularly-sampled time series (ISTS) is challenging because of missing values.
Aux-Drop: Handling Haphazard Inputs in Online Learning Using Auxiliary Dropouts
Many real-world applications based on online learning produce streaming data that is haphazard in nature, i. e., contains missing features, features becoming obsolete in time, the appearance of new features at later points in time and a lack of clarity on the total number of input features.
MABNet: Master Assistant Buddy Network with Hybrid Learning for Image Retrieval
We present a novel Master Assistant Buddy Network (MABNet) for image retrieval which incorporates both learning mechanisms.
Transformer Assisted Convolutional Network for Cell Instance Segmentation
Region proposal based methods like R-CNN and Faster R-CNN models have proven to be extremely successful in object detection and segmentation tasks.
Detection of COVID-19 informative tweets using RoBERTa
Social media such as Twitter is a hotspot of user-generated information.
Auxiliary Network: Scalable and agile online learning for dynamic system with inconsistently available inputs
Streaming classification methods assume the number of input features is fixed and always received.
Simulation-supervised deep learning for analysing organelles states and behaviour in living cells
Performing artificial intelligence (AI) tasks such as segmentation, tracking, and analytics of small sub-cellular structures such as mitochondria in microscopy videos of living cells is a prime example.
C-Net: Contextual Network for Sarcasm Detection
Automatic Sarcasm Detection in conversations is a difficult and tricky task.
