Multimedia Deep Learning

Deep Learning For Multimedia Processing - Predicting Media Interestingness

This thesis explores the application of a deep learning approach for the prediction of media interestingness. Two different models are investigated, one for the prediction of image and one for the prediction of video interestingness. For the prediction of image interestingness, the ResNet50 network is fine-tuned to obtain best results. First, some layers are added. Next, the model is trained an...

Correlation-Based Deep Learning for Multimedia Semantic Concept Detection

Nowadays, concept detection from multimedia data is considered as an emerging topic due to its applicability to various applications in both academia and industry. However, there are some inevitable challenges including the high volume and variety of multimedia data as well as its skewed distribution. To cope with these challenges, in this paper, a novel framework is proposed to integrate two c...

IEEE Transaction on Multimedia Guest Editorial: Deep Learning for Multimedia Computing

Conventional multimedia computing is often built on top of handcrafted features, which are often much restrictive in capturing complex multimedia content such as images, audios, text and user-generated data with domain-specific knowledge. Recent progress on deep learning opens an exciting new era, placing multimedia computing on a more rigorous foundation with automatically learned representati...

Melanoma detection with a deep learning model

Background: Skin cancer is one of the most common forms of cancer in the world and melanoma is the deadliest type of skin cancer. Both melanoma and melanocytic nevi begin in melanocytes (cells that produce melanin). However, melanocytic nevi are benign whereas melanoma is malignant. This work proposes a deep learning model for classification of these two lesions.    Methods: In this analytic s...

Bayesian Deep Learning | Uncertainty in Deep Learning