Deep learning applies multiple processing layers to learn representations of data with
multiple levels of feature extraction. This emerging technique has reshaped the research …

The quality and size of training set have a great impact on the results of deep learning-
based face-related tasks. However, collecting and labeling adequate samples with high …

We propose a method designed to push the frontiers of unconstrained face recognition in
the wild with an emphasis on extreme out-of-plane pose variations. Existing methods either …

Facial recognition using deep convolutional neural networks relies on the availability of
large datasets of face images. Many examples of identities are needed, and for each …

The availability of large-scale face datasets has been key in the progress of face recognition.
However, due to licensing issues or copyright infringement, some datasets are not available …

We identify two issues as key to developing effective face recognition systems: maximizing
the appearance variations of training images and minimizing appearance variations in test …

Abstract Machine Learnt Models (MLMs) are now commonly used in self-driving cars,
particularly for tasks such as object detection and classification within the perception …

The quality and size of training set have great impact on the results of deep learning-based
face related tasks. However, collecting and labeling adequate samples with high quality and …

Lung cancer is deadly cancer same as colon cancer, both of them can grow simultaneously.
Most researchers conduct research to detect one disease on one single body organ. So, in …

The use of computer vision for product and assembly quality control is becoming ubiquitous
in the manufacturing industry. Lately, it is apparent that machine learning based solutions …