In this work, we analyze and apply various recent techniques in visual attribute recognition and labeling on a common benchmark dataset in order to motivate the design of a novel framework for this task. Using the large ...

Computational creativity is a field focused on the study and development of behaviors in computers an observer would deem creative. Traditionally, it has relied upon rules-based and search-based artificial intelligence. ...

As AI continues to advance, human-AI teams are inevitable. However, progress in AI is routinely measured in isolation, without a human in the loop. It is crucial to benchmark progress in AI, not just in isolation, but ...

In this work we propose a new approach to the object detection problem using Deep Neural Network, in the context of traffic sign detection. Our approach simplifies the detection head complexity by making the requirement ...

Data-driven paradigms now solve the world's hardest problems by automatically learning from data. Unfortunately, what is learned is often unknown to both the people who train the models and the people they impact. This has ...

Prokaryotic gene-prediction is the task of finding genes in archaeal or bacterial DNA sequences. These genomes consist of alternating gene-coding and non-coding regions, meaning the task is solved by determining the start ...

Answers to the most complex biological questions are rarely determined solely from the experimental evidence. It requires subsequent analysis of many data sources that are often heterogeneous. Most biological data repositories ...

Recommendation systems are emerging as an important business application as the demand for personalized services in E-commerce increases. Collaborative filtering techniques are widely used for predicting a user's preference ...

Supervised learning tasks like building a classifier, estimating the error rate of the predictors, are typically performed with labeled data. In most cases, obtaining labeled data is costly as it requires manual labeling. ...

This dissertation presents segmental discriminative analysis techniques for American Sign Language (ASL) recognition and verification. ASL recognition is a sequence classification problem. One of the most successful ...