2 citations · 3 across the 6 of their papers we have counts for
6 papers
Interpretable AI for Time-Series: Multi-Model Heatmap Fusion with Global Attention and NLP-Generated Explanations
Jiztom Kavalakkatt Francis, Matthew J Darr
In this paper, we present a novel framework for enhancing model interpretability by integrating heatmaps produced separately by ResNet and a restructured 2D Transformer with global…
Multivariate Temporal Regression at Scale: A Three-Pillar Framework Combining ML, XAI, and NLP
Jiztom Kavalakkatt Francis, Matthew J Darr
This paper introduces a novel framework that accelerates the discovery of actionable relationships in high-dimensional temporal data by integrating machine learning (ML), explainab…
Learn and Search: An Elegant Technique for Object Lookup using Contrastive Learning
Chandan Kumar, Jansel Herrera-Gerena, John Just +2
The rapid proliferation of digital content and the ever-growing need for precise object recognition and segmentation have driven the advancement of cutting-edge techniques in the f…
Unsupervised learning based object detection using Contrastive Learning
Chandan Kumar, Jansel Herrera-Gerena, John Just +2
Training image-based object detectors presents formidable challenges, as it entails not only the complexities of object detection but also the added intricacies of precisely locali…
Pattern Based Multivariable Regression using Deep Learning (PBMR-DP)
Jiztom Kavalakkatt Francis, Chandan Kumar, Jansel Herrera-Gerena +2
We propose a deep learning methodology for multivariate regression that is based on pattern recognition that triggers fast learning over sensor data. We used a conversion of sensor…
CLAWS: Contrastive Learning with hard Attention and Weak Supervision
Jansel Herrera-Gerena, Ramakrishnan Sundareswaran, John Just +2
Learning effective visual representations without human supervision is a long-standing problem in computer vision. Recent advances in self-supervised learning algorithms have utili…