05-08-2022, 03:36 AM
Western sanctions are now being introduced and may include full and most punitive measures. Previous disagreements between the EU, US and UK on the scale of sanctions seem to have been overcome. Russian actions have, if anything, strengthened western resolve, as is clear from the immediate responses from countries like the UK and Germany, which has announced it won’t certify Russia’s Nord Stream 2 gas pipeline. The current crisis is about more than the status of “certain areas of Donetsk and Luhansk regions”, as the territories are referred to in the Minsk agreement. It does not resolve the broader tensions between Russia. The west over the future European security order. It is obvious that Putin has become convinced that the continuing status of Donetsk and Luhansk as de facto states within Ukraine - and thus as an instrument of leverage over Ukraine and, by extension, over its western partners - had ceased to serve Russia’s purposes. But his hour-long televised speech has given little cause for optimism that their recognition has put an end to the “Ukrainian issue”.|Reducing redundancy is crucial for improving the efficiency of video recognition models. An effective approach is to select informative content from the holistic video, yielding a popular family of dynamic video recognition methods. However, existing dynamic methods focus on either temporal or spatial selection independently while neglecting a reality that the redundancies are usually spatial and temporal, simultaneously. Moreover, their selected content is usually cropped with fixed shapes (e.g., temporally-cropped frames, spatially-cropped patches), while the realistic distribution of informative content can be much more diverse. With these two insights, this paper proposes to integrate temporal and spatial selection into an Action Keypoint Network (AK-Net). From different frames and positions, AK-Net selects some informative points scattered in arbitrary-shaped regions as a set of “action keypoints” and then transforms the video recognition into point cloud classification. More concretely, AK-Net has two steps, i.e., the keypoint selection and the point cloud classification. First, it inputs the video into a baseline network and outputs a feature map from an intermediate layer. What we're talking about here is electrotactile stimulation for sensory augmentation or substitution, an area of study that involves using encoded electric current to represent sensory information -- information that a person cannot receive through the traditional channel -- and applying that current to the skin, which sends the information to the brain. The brain then learns to interpret that sensory information as if it were being sent through the traditional channel for such data. In the 1960s and '70s, this process was the subject of ground-breaking research in sensory substitution at the Smith-Kettlewell Institute led by Paul Bach-y-Rita, MD, Professor of Orthopedics and Rehabilitation and Biomedical Engineering at the University of Wisconsin, Madison. Now it's the basis for Wicab's BrainPort technology (Dr. Bach-y-Rita is also Chief Scientist and Chairman of the Board of Wicab). Eyeglasses are a typical example of sensory augmentation. Braille is a typical example of sensory substitution -- in this case, you're using one sense, touch, to take in information normally intended for another sense, vision. bbc world
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