Search Results for author:
Found 8 papers, 1 papers with code
Fine-grained Human Activity Recognition Using Virtual On-body Acceleration Data
In this work we first introduce a measure to quantitatively assess the subtlety of human movements that are underlying activities of interest--the motion subtlety index (MSI)--which captures local pixel movements and pose changes in the vicinity of target virtual sensor locations, and correlate it to the eventual activity recognition accuracy.
ColloSSL: Collaborative Self-Supervised Learning for Human Activity Recognition
In this paper, we extend this line of research and present a novel technique called Collaborative Self-Supervised Learning (ColloSSL) which leverages unlabeled data collected from multiple devices worn by a user to learn high-quality features of the data.
Matching Models for Graph Retrieval
Graph Retrieval has witnessed continued interest and progress in the past few years.
Integrating Transductive And Inductive Embeddings Improves Link Prediction Accuracy
In recent years, inductive graph embedding models, \emph{viz.
Towards an Interpretable Latent Space in Structured Models for Video Prediction
We work with models which are object-centric, i. e., explicitly work with object representations, and propagate a loss in the latent space.
Reinforcement Learning Based Asymmetrical DNN Modularization for Optimal Loading
Latency of DNN (Deep Neural Network) based prediction is the summation of model loading latency and inference latency.
Visually Aware Skip-Gram for Image Based Recommendations
The visual appearance of a product significantly influences purchase decisions on e-commerce websites.
KARNA at COIN Shared Task 1: Bidirectional Encoder Representations from Transformers with relational knowledge for machine comprehension with common sense
This paper describes our model for COmmonsense INference in Natural Language Processing (COIN) shared task 1: Commonsense Inference in Everyday Narrations.
