Demetri Martin Visual Jokes
- Length: 6:29
- Rating: 4.87 (1812 ratings)
- Views: 648097' favoriteCount='6684
- Author: unpaidintern
Tags: comedy demetri doublehawk fruit funny grapes hope jokes martin of speical
"About a month ago I got a cactus, and a week later it died. And I got really depressed because I realised, damn . . . I am less nurturing than a desert"
The Orthodox Church - A visual journey
- Length: 4:31
- Rating: 4.76 (277 ratings)
- Views: 91957' favoriteCount='419
- Author: Orthros05
This video presents some sights and sounds of the Orthodox Church.
Mobile Visual Search Engine on the Apple iPhone
- Length: 4:6
- Rating: 4.47 (55 ratings)
- Views: 99473' favoriteCount='83
- Author: EvolutionRobotics
Tags: Camera Evolution Mobile Patten Phone Recognition Robotic Robotics Search ViPR Vision Visual
Imagine you could search the Internet just by taking a picture of something, such snapping a picture of a music CD to look up reviews and listen to the tracks, instantly getting information on a product featured in a magazine, or looking up recommend places to visit by taking a picture of a famous landmark. Millions of mobile phone users can "visually search" the Internet today with the help of this revolutionary search engine powered by Evolution Robotics' Visual Pattern Recognition technology. (ViPR®) Evolution is developing a number of applications for visual search, and we came up with this quick demo for the iPhone to showcase some of the the possibilities . For more information, please visit www.evolution.com.
alice nine. - Visual Shock (10.05.2007)
- Length: 6:46
- Rating: 4.98 (118 ratings)
- Views: 64830' favoriteCount='260
- Author: regina404master
Tags: alice Hiroto Nao NHK nine Saga Shock Shou Tora Visual アリス九號
alice nine. in Visual Shock Performance from NHK (28.04.2007)- open air[birth in white rose]: Velvet, WHITE PRAYER, heisei juushichinen shichigatsu nanoka, shunkashuutou . Tora's new look is a little weird ... that half yellow head was stupid idea and short hair makes him older...
Visual Perception with Deep Learning
- Length: 57:25
- Rating: 4.67 (6 ratings)
- Views: 3051' favoriteCount='22
- Author: googletechtalks
Tags: education engedu google googletechtalks talk talks techtalk techtalks
Google Tech Talks April, 9 2008 ABSTRACT A long-term goal of Machine Learning research is to solve highy complex "intelligent" tasks, such as visual perception auditory perception, and language understanding. To reach that goal, the ML community must solve two problems: the Deep Learning Problem, and the Partition Function Problem. There is considerable theoretical and empirical evidence that complex tasks, such as invariant object recognition in vision, require "deep" architectures, composed of multiple layers of trainable non-linear modules. The Deep Learning Problem is related to the difficulty of training such deep architectures. Several methods have recently been proposed to train (or pre-train) deep architectures in an unsupervised fashion. Each layer of the deep architecture is composed of an encoder which computes a feature vector from the input, and a decoder which reconstructs the input from the features. A large number of such layers can be stacked and trained sequentially, thereby learning a deep hierarchy of features with increasing levels of abstraction. The training of each layer can be seen as shaping an energy landscape with low valleys around the training samples and high plateaus everywhere else. Forming these high plateaus constitute the so-called Partition Function problem. A particular class of methods for deep energy-based unsupervised learning will be described that solves the Partition Function problem by imposing sparsity constraints on the features. The method can learn multiple levels of sparse and overcomplete representations of data. When applied to natural image patches, the method produces hierarchies of filters similar to those found in the mammalian visual cortex. An application to category-level object recognition with invariance to pose and illumination will be described (with a live demo). Another application to vision-based navigation for off-road mobile robots will be described (with videos). The system autonomously learns to discriminate obstacles from traversable areas at long range. This is joint work with Y-Lan Boureau, Sumit Chopra, Raia Hadsell, Fu-Jie Huang, Koray Kavakcuoglu, and Marc'Aurelio Ranzato. Speaker: Yann Le Cun Computational and Biological Learning Lab, Courant Institute of Mathematical Sciences, New York University.
Page: 1 of 21535