The philosophy of computational object recognition, scene understanding, machine learning, and musings on the future of computer vision.
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Computer Vision and Visual SLAM vs. AI Agents

With all the recent advancements in end-to-end deep learning, it is now possible to train AI agents to perform many different tasks (some in simulation and some in the real-world). End-to-end learning allows one to replace a multi-component, hand-engineered system with a single learning network that can process raw sensor data and output actions for...

Tue Nov 19, 2019 12:18
DeepFakes: AI-powered deception machines

Driven by computer vision and deep learning techniques, a new wave of imaging attacks has recently emerged which allows anyone to easily create highly realistic "fake" videos. These false videos are known as Deep Fakes. While highly entertaining at times, DeepFakes can be used to perturb society and some would argue that the pre-shock has already begun....

Wed May 16, 2018 22:23
Nuts and Bolts of Building Deep Learning Applications: Ng @ NIPS2016

You might go to a cutting-edge machine learning research conference like NIPS hoping to find some mathematical insight that will help you take your deep learning system's performance to the next level. Unfortunately, as Andrew Ng reiterated to a live crowd of 1,000+ attendees this past Monday, there is no secret AI equation that will let you escape...

Fri Dec 16, 2016 07:13
Making Deep Networks Probabilistic via Test-time Dropout

In Quantum Mechanics, Heisenberg's Uncertainty Principle states that there is a fundamental limit to how well one can measure a particle's position and momentum. In the context of machine learning systems, a similar principle has emerged, but relating interpretability and performance. By using a manually wired or shallow machine learning model, you'll...

Fri Jun 17, 2016 14:24
Deep Learning Trends @ ICLR 2016

Started by the youngest members of the Deep Learning Mafia [1], namely Yann LeCun and Yoshua Bengio, the ICLR conference is quickly becoming a strong contender for the single most important venue in the Deep Learning space. More intimate than NIPS and less benchmark-driven than CVPR, the world of ICLR is arXiv-based and moves fast. Today's post is...

Wed Jun 1, 2016 12:22
The Future of Real-Time SLAM and "Deep Learning vs SLAM"

Last month's International Conference of Computer Vision (ICCV) was full of Deep Learning techniques, but before we declare an all-out ConvNet victory, let's see how the other "non-learning" geometric side of computer vision is doing.  Simultaneous Localization and Mapping, or SLAM, is arguably one of the most important algorithms in Robotics, with...

Wed Jan 13, 2016 11:20

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