Understanding users’ context is essential in emerging mobile sensing applications, such as Metal Detector, Glint Finder, Facefirst. Over the last decade, Machine Learning (ML) techniques have evolved dramatically for ...

Deep Learning with depth cameras has enabled 3D hand pose estimation from RGBD images. Commercial solutions like Leap Motion and Intel RealSense™ use stereoscopic sensors or IR illumination-based methods to capture the ...

There are a lot of open source projects available on the internet. Specifically, due to the increasing interest of Deep Learning (DL), the number of DL open source projects is also increased. This project is motivated ...

In recent years, Deep Learning (DL) has shown promising results with regard to conducting AI tasks such as computer vision and speech recognition. Specifically, DL demonstrated the state-of-the-art in computer vision ...

Recommender systems have become increasingly popular by providing a wide range of products with a variety of styles. This trend has resulted in consumers expecting more intelligent and highly dynamic recommenders. The ...

Real-time event modeling and recognition is one of the major research areas that is yet to reach its fullest potential. In the exploration of a system to fit in the tremendous challenges posed by data growth, several big ...

Deep Learning technologies show promise for dramatic advances in fields such as image classification and speech recognition. Deep Learning (DL) is a class of Machine Learning algorithms that involves learning of multiple ...

In recent years, there has been explosive growth in the amount of biomedical data (e.g., publications, notes from EHRs, clinical trial results), with the majority being unstructured data. As the volume of data is ...

In recent years, there has been an explosive growth of the linked data of a global information space that often requires expensive computations to perform big graph analysis and query processing. Graph data represent ...

Sentiment analysis has proven to be very successful in text applications. Social media is also considered a quite rich source to get data regarding user’s behaviors and preference. Identifying social context would make ...

Machine learning has made significant progress for many real-world problems. The Deep Learning (DL) models proposed primarily concentrate on object detection, image classification, and image captioning. However, very ...

Big data analytics uncover hidden patterns and useful information from big data. It is a complex and time-consuming process. Recent advancements in parallel and distributed approaches have led to the evolution of big data ...

Deep Learning (DL) has received considerable attention from the AI community. However, we suffer from the lack of ability in interpretation and annotation of the outcomes from extensive and exhausting learning efforts. ...

Deep learning has received a lot of attention in the fields such as speech recognition and image classification because of the ability to learn multiple levels of features from raw data. However, 3D deep learning is ...

Image question answering has gained huge popularity in recent years due to advancements in Deep Learning technologies and computer processing hardware which are able to achieve higher accuracies with faster processing ...

In recent years, deep learning technologies have been increasingly applied to generate meaningful data for advanced research in humanities and sciences. Interpersonal communication skills are crucial to success in science. ...

Twitter and Facebook are the renowned social networking platforms where users post, share, interact and express to the world, their interests, personality, and behavioral information. User-created content on social media ...

The Internet has made it possible, in principle, for scientists to quickly find research papers of interest. In practice, the overwhelming volume of publications makes this a time consuming task. It is, therefore, important ...

Service Oriented Architecture (SOA) has become a popular paradigm for designing distributed systems where loosely coupled services (i.e. computational entities) can be integrated seamlessly to provide complex composite ...

Object detection has gained much attention in recent years because of its ability to localize and classify the objects in videos and images that can be incorporated into many applications. Traditional object detection ...