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Found 6 papers, 1 papers with code
Improving Contrastive Learning on Visually Homogeneous Mars Rover Images
In this study, we propose two approaches to resolve this: 1) an unsupervised deep clustering step on the Mars datasets, which identifies clusters of images containing similar semantic content and corrects false negative errors during training, and 2) a simple approach which mixes data from different domains to increase visual diversity of the total training dataset.
Explainable Artificial Intelligence for Pharmacovigilance: What Features Are Important When Predicting Adverse Outcomes?
Using XAI, we quantified the contribution that specific drugs had on these ACS predictions, thus creating an XAI-based technique for pharmacovigilance monitoring, using ACS as an example of the adverse outcome to detect.
Explainable artificial intelligence
Explainable Artificial Intelligence (XAI)
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A Practical Tutorial on Graph Neural Networks
Graph neural networks (GNNs) have recently grown in popularity in the field of artificial intelligence (AI) due to their unique ability to ingest relatively unstructured data types as input data.
RGB-D image-based Object Detection: from Traditional Methods to Deep Learning Techniques
Deep learning techniques, coupled with the availability of large training datasets, have now revolutionized the field of computer vision, including RGB-D object detection, achieving an unprecedented level of performance.
Improving Image-Based Localization with Deep Learning: The Impact of the Loss Function
This work investigates the impact of the loss function on the performance of Neural Networks, in the context of a monocular, RGB-only, image localization task.
Optical Flow Techniques for Facial Expression Analysis -- a Practical Evaluation Study
Optical flow techniques are becoming increasingly performant and robust when estimating motion in a scene, but their performance has yet to be proven in the area of facial expression recognition.
