347 citations · 469 across the 4 of their papers we have counts for
6 papers
One-shot Information Extraction from Document Images using Neuro-Deductive Program Synthesis
Vishal Sunder, Ashwin Srinivasan, Lovekesh Vig +2
Our interest in this paper is in meeting a rapidly growing industrial demand for information extraction from images of documents such as invoices, bills, receipts etc. In practice…
ConvTimeNet: A Pre-trained Deep Convolutional Neural Network for Time Series Classification
Kathan Kashiparekh, Jyoti Narwariya, Pankaj Malhotra +2
Training deep neural networks often requires careful hyper-parameter tuning and significant computational resources. In this paper, we propose ConvTimeNet (CTN): an off-the-shelf d…
Predicting Remaining Useful Life using Time Series Embeddings based on Recurrent Neural Networks
Narendhar Gugulothu, Vishnu TV, Pankaj Malhotra +3
We consider the problem of estimating the remaining useful life (RUL) of a system or a machine from sensor data. Many approaches for RUL estimation based on sensor data make assump…
TimeNet: Pre-trained deep recurrent neural network for time series classification
Pankaj Malhotra, Vishnu TV, Lovekesh Vig +2
Inspired by the tremendous success of deep Convolutional Neural Networks as generic feature extractors for images, we propose TimeNet: a deep recurrent neural network (RNN) trained…
LSTM-based Encoder-Decoder for Multi-sensor Anomaly Detection
Pankaj Malhotra, Anusha Ramakrishnan, Gaurangi Anand +3
Mechanical devices such as engines, vehicles, aircrafts, etc., are typically instrumented with numerous sensors to capture the behavior and health of the machine. However, there ar…
ODE - Augmented Training Improves Anomaly Detection in Sensor Data from Machines
Mohit Yadav, Pankaj Malhotra, Lovekesh Vig +2
Machines of all kinds from vehicles to industrial equipment are increasingly instrumented with hundreds of sensors. Using such data to detect anomalous behaviour is critical for sa…