23 citations · 42 across the 6 of their papers we have counts for
6 papers · 1 filter
Pick-Object-Attack: Type-Specific Adversarial Attack for Object Detection
Omid Mohamad Nezami, Akshay Chaturvedi, Mark Dras +1
Many recent studies have shown that deep neural models are vulnerable to adversarial samples: images with imperceptible perturbations, for example, can fool image classifiers. In t…
Towards Generating Stylized Image Captions via Adversarial Training
Omid Mohamad Nezami, Mark Dras, Stephen Wan +2
While most image captioning aims to generate objective descriptions of images, the last few years have seen work on generating visually grounded image captions which have a specifi…
Image Captioning using Facial Expression and Attention
Omid Mohamad Nezami, Mark Dras, Stephen Wan +1
Benefiting from advances in machine vision and natural language processing techniques, current image captioning systems are able to generate detailed visual descriptions. For the m…
Senti-Attend: Image Captioning using Sentiment and Attention
Omid Mohamad Nezami, Mark Dras, Stephen Wan +1
There has been much recent work on image captioning models that describe the factual aspects of an image. Recently, some models have incorporated non-factual aspects into the capti…
Automatic Recognition of Student Engagement using Deep Learning and Facial Expression
Omid Mohamad Nezami, Mark Dras, Len Hamey +3
Engagement is a key indicator of the quality of learning experience, and one that plays a major role in developing intelligent educational interfaces. Any such interface requires t…
Face-Cap: Image Captioning using Facial Expression Analysis
Omid Mohamad Nezami, Mark Dras, Peter Anderson +1
Image captioning is the process of generating a natural language description of an image. Most current image captioning models, however, do not take into account the emotional aspe…