9 citations · 28 across the 10 of their papers we have counts for
11 papers
Automatic Recognition of Learning Resource Category in a Digital Library
Soumya Banerjee, Debarshi Kumar Sanyal, Samiran Chattopadhyay +2
Digital libraries often face the challenge of processing a large volume of diverse document types. The manual collection and tagging of metadata can be a time-consuming and error-p…
Incorporating Domain Knowledge To Improve Topic Segmentation Of Long MOOC Lecture Videos
Ananda Das, Partha Pratim Das
Topical Segmentation poses a great role in reducing search space of the topics taught in a lecture video specially when the video metadata lacks topic wise segmentation information…
Knowledge Distillation for Singing Voice Detection
Soumava Paul, Gurunath Reddy M, K Sreenivasa Rao +1
Singing Voice Detection (SVD) has been an active area of research in music information retrieval (MIR). Currently, two deep neural network-based methods, one based on CNN and the o…
Segmenting Scientific Abstracts into Discourse Categories: A Deep Learning-Based Approach for Sparse Labeled Data
Soumya Banerjee, Debarshi Kumar Sanyal, Samiran Chattopadhyay +2
The abstract of a scientific paper distills the contents of the paper into a short paragraph. In the biomedical literature, it is customary to structure an abstract into discourse…
Bharatanatyam Dance Transcription using Multimedia Ontology and Machine Learning
Tanwi Mallick, Patha Pratim Das, Arun Kumar Majumdar
Indian Classical Dance is an over 5000 years' old multi-modal language for expressing emotions. Preservation of dance through multimedia technology is a challenging task. In this p…
Beat Detection and Automatic Annotation of the Music of Bharatanatyam Dance using Speech Recognition Techniques
Tanwi Mallick, Partha Pratim Das, Arun Kumar Majumdar
Bharatanatyam, an Indian Classical Dance form, represents the rich cultural heritage of India. Analysis and recognition of such dance forms are critical for the preservation of cul…
Early Response Assessment in Lung Cancer Patients using Spatio-temporal CBCT Images
Bijju Kranthi Veduruparthi, Jayanta Mukherjee, Partha Pratim Das +5
We report a model to predict patient's radiological response to curative radiation therapy (RT) for non-small-cell lung cancer (NSCLC). Cone-Beam Computed Tomography images acquire…
Novel Radiomic Feature for Survival Prediction of Lung Cancer Patients using Low-Dose CBCT Images
Bijju Kranthi Veduruparthi, Jayanta Mukherjee, Partha Pratim Das +5
Prediction of survivability in a patient for tumor progression is useful to estimate the effectiveness of a treatment protocol. In our work, we present a model to take into account…
Posture and sequence recognition for Bharatanatyam dance performances using machine learning approach
Tanwi Mallick, Partha Pratim Das, Arun Kumar Majumdar
Understanding the underlying semantics of performing arts like dance is a challenging task. Dance is multimedia in nature and spans over time as well as space. Capturing and analyz…
HSD-CNN: Hierarchically self decomposing CNN architecture using class specific filter sensitivity analysis
K. Sai Ram, Jayanta Mukherjee, Amit Patra +1
Conventional Convolutional neural networks (CNN) are trained on large domain datasets and are hence typically over-represented and inefficient in limited class applications. An eff…
Analysis of Deformation Fields in Spatio-temporal CBCT images of lungs for radiotherapy patients
Bijju Kranthi Veduruparthi, Jayanta Mukherjee, Partha Pratim Das +5
Deformable registration of spatiotemporal Cone-Beam Computed Tomography (CBCT) images taken sequentially during the radiation treatment course yields a deformation field for a pair…