Atrial fibrillation is one of the most common arrhythmias with significant clinical implications. When it comes to detecting and categorising different types of heart diseases, machine learning and deep learning techn...
详细信息
Recently, video text detection, tracking and recognition in natural scenes are becoming very popular in the computervision community. However, most existing algorithms and benchmarks focus on common text cases (e.g.,...
详细信息
Any generic deep machine learning algorithm is essentially a function fitting exercise, where the network tunes its weights and parameters to learn discriminatory features by minimizing some cost function. Though the ...
详细信息
To make predictions on unseen classes, few-shot segmentation becomes a research focus recently. However, most methods build on pixel-level annotation requiring quantity of manual work. Moreover, inherent information o...
详细信息
Image colorization is a well-known problem in computervision. However, due to the ill-posed nature of the task, image colorization is inherently challenging. Though several attempts have been made by researchers to m...
详细信息
Pose estimation of a pedestrian helps to gather information about the current activity or the instant behaviour of the subject. Such information is useful for autonomous vehicles, augmented reality, video surveillance...
详细信息
The recognition of human emotions remains a challenging task for social media images. This is due to distortions created by different social media conflict with the minute changes in facial expression. This study pres...
详细信息
Self-supervised contrastive learning frameworks have progressed rapidly over the last few years. In this paper, we propose a novel mutual information optimization-based loss function for contrastive learning. We model...
详细信息
The Background Linking task is a problem that focuses on providing users with suggestions for articles to read next, when the user is reading a news article. The suggested articles should provide adequate context and ...
The relevance of machine learning (ML) in our daily lives is closely intertwined with its explainability. Explainability can allow end-users to have a transparent and humane reckoning of a ML scheme's capability a...
详细信息
暂无评论