


Convolutional Neural Networks Lecture
Convolutional Neural Networks form the backbone of current AI revolution and are used in a multitude of classification and regression problems. This lecture overviews the transition from multilayer perceptrons to deep architectures.



MultiDrone Datasets
This lecture overviews MultiDrone Datasets that has many applications in autonomous drone research and development.



Natural Language Processing
This lecture overviews Natural Language Processing (NLP) that has many applications in text analytics, Linguistics, Machine translation and sentiment analysis.



Recurrent Neural Networks. LSTMs
This lecture overviews Recurrent Neural Networks and Long Short-Term Memory (LSTM) networks that have many applications in signal and video analysis. It covers the following topics in detail: Neural Networks for Sequence Analysis.



Neural Speech Recognition
This lecture overviews Neural Speech Recognition is a special case of Automatic Speech Recognition (ASR), i.e., the transcription of speech to text that has many applications e.g., in call centers, dictation, meeting minutes creation, Smart assist



Deep Object Detection
Recently, Convolutional Neural Networks (CNNs) have been used for object/target (e.g., face, person, car, pedestrian, road sign) detection with great results.