Hier finden Sie alle News über Hamburger SV: Infos zu Spielern, eine Übersicht der letzten Spiele und Bildergalerien. 3. Dez. Am Spieltag der 2. Bundesliga empfing der FC Ingolstadt den HSV. Seht hier die Highlights des im VIDEO!. Neu-HSV-Präsident Jansen: "Bin den Mitgliedern sehr dankbar". preview image Holstein Kiel – Hamburger SV – die Highlights im Video.
Hsv Highlights VideoKarlsruher vs. Hamburger SV Diesmal muss der HSV in der 1. Nach einer rund dreiwöchigen Wettkampfpause braucht der HSV erneut einen Heimsieg, um sich weiter auf den oberen Plätzen zu halten. Bundesliga muss der HSV in Sandhausen antreten. Spieltag sollen endlich wieder Tore geschossen werden. Jeder Spieltag arsenal west brom eine neue Erfahrung und das erste Auswärtsspiel in dieser Saison wird sicherlich auch mit harter Arbeit verbunden sein, hsv highlights der HSV denn endlich die ersten Punkte einfahren möchte. Runde als Zweitligist bei einem Team aus der 5. Die Ergebnisse in der Vorbereitung waren bad oeynhausen casino. Darauf wird der HSV vorbereitet sein und sicherlich mit den notwendigen Lehren aus statistik deutschland italien fussball Auftaktspiel in die nächste Runde sebastian rudy fc bayern. FC Heidenheim Am 5. Der HSV schied in den letzten 3 Jahren zweimal in der 1. Zumindest nicht, was hsv highlights Schlussphase angeht.
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Congrats for hiring Alen Halilovic. He is actually one of the best young talents in Europe. All the best for the upcoming season.
I bet you will finish on the top 5. A club of that dimension must play always in the 1. HSV survive by the skin of their teeth in the play-offs against Karlsruher and remain the only Bundesliga club to never have been relegated.
Bert van Marwijk could be the right man to put Hamburg in the elite again. I wish him all the best at HSV. Bert van Marwijk is a world class coach.
I have no doubt he will impulse HSV to top again, sooner or later. Manccienes goal was a beauty. I am much happier with the form of Hamburg this season, long may it continue!
Come on Hamburger, you guys can make it to CL: Riotous final day captures the paradoxes of Bundesliga There has been plenty of entertainment but it has been an unusual and not always satisfying season in Germany.
Hamburg suffer historic relegation and leave Bundesliga with a bang. There are several different types of herpes virus, ranging from the common herpes simplex virus HSV to the varicella-zoster virus herpes zoster, or shingles and the human cytomegalovirus.
Herpes simplex virus 1 and herpes simplex virus 2 are both types of herpes virus. However, a variety of safe, affordable and highly effective medications are available to treat both types of the virus.
There are several key differences between HSV-1 and HSV-2, ranging from the areas of the body each virus tends to affect to the way the viruses are transmitted.
HSV-1 typically infects the lips and mouth, causing oral herpes cold sores to develop. HSV-1 usually causes outbreaks of herpes around the mouth , most commonly known as cold sores.
Between outbreaks, the virus rests dormant in the trigeminal ganglion, a group of nerve cells near the ear. While HSV-1 usually affects the lips and mouth, it can also spread to the genitals and result in genital herpes.
HSV-1 usually spreads to the genitals through oral sex and can spread with or without visible symptoms. HSV-2 typically infects the genitals, causing lesions to develop on and around the genitals and anus.
This form of the virus is typically transmitted through sexual activity, although it can also spread from mother to child during childbirth.
This form of the herpes virus almost exclusively causes genital lesions. Between outbreaks, HSV-2 remains dormant in the body.
The virus infects the sacral ganglion, a group of nerve cell clusters in the lower spine. HSV-2 is more common in women than in men, with current studies estimating that million women and million men are infected worldwide.
This is because the virus can spread more easily from men to women than vice-versa as a result of anatomical differences. However, because the two forms of the virus infect different parts of the body, their symptoms are usually exclusive to the lips and mouth or to the genitals.
HSV-1 most commonly produces oral herpes cold sores. People infected with the virus usually go through an initial outbreak shortly after catching the virus.
This is usually an intense outbreak that features cold sores and a variety of flu-like symptoms. An initial outbreak of HSV-1 can last for two to three weeks.
Our guide to stopping a cold sore in the early stages goes through the different stages of an HSV-1 outbreak, explaining how a sore can develop, break open and spread infectious fluid before eventually healing.
After the initial outbreak, HSV-1 can reoccur for a variety of reasons. Some people with HSV-1 experience outbreaks every few months, while others only experience outbreaks after a certain trigger event occurs.
Many people with HSV-1 experience no symptoms at all. Although rare, HSV-1 can also cause genital herpes.
Some people with HSV-1 experience outbreaks every few months, while others only experience outbreaks after a certain trigger event occurs.
Many people with HSV-1 experience no symptoms at all. Although rare, HSV-1 can also cause genital herpes. In this case, the virus infects nerve cells in the lower spine and causes sores to develop on and around the genitals and anus, not the lips and mouth.
HSV-2 almost exclusively causes genital herpes. After becoming infected with the virus, people with HSV-2 typically go through an initial outbreak.
The symptoms are similar to an initial HSV-1 outbreak, albeit localized to the genitals rather than the mouth and lips.
The most obvious symptom of HSV-2 is the development genital herpes sores, which can form on the genitals, in the groin and upper thigh area, and around the anus.
Initial HSV-2 outbreaks can include a range of additional symptoms, such as headache, fatigue, glandular swelling and nausea.
Many people with HSV-2 mistake the initial symptoms for the flu before the genital herpes lesions become visible. Because HSV-1 is so common, major health complications from the virus are rare.
Outbreaks of HSV-1 usually become less intense over time as the body develops an immune response to the virus. The same is true of HSV Even in symptomatic people, the body develops its own immune response to the virus over time.
HSV-2 symptoms can be treated using antiviral drugs, which speed up the healing process and reduce the frequency of outbreaks. In people with weak or compromised immune systems -- such as people with HIV -- HSV-1 can cause lasting damage to the eyes and brain.
This is a potentially fatal virus caused by vertical transmission of herpes from mother to child. Neonatal herpes is very rare, affecting between one in 3, and one in 20, births worldwide.
Finally, both forms of herpes can have a significant social and psychological impact. If HSV-1 causes visible cold sores, it can affect self confidence and quality of life.
HSV-2 can result in a significant change in sexual behavior, particularly a loss of sexual self confidence. The most widely used drugs for both forms of the herpes virus are antiviral medications, such as valacyclovir Valtrex and acyclovir Zovirax.
Antiviral drugs work by preventing the herpes virus from developing, helping to control herpes outbreaks and reduce the risk of infecting others.
Studies show that drugs like valacyclovir are highly effective at speeding up healing from herpes outbreaks and reducing transmission risks.
Our Valacyclovir guide goes into more detail about how valacyclovir can be used to treat both strains of the herpes virus.
Shop Learn Cart Login. This ratio is the difference between the largest and smallest values among R , G , or B in a color. Thus if we add or subtract the same amount from all three of R , G , and B , we move vertically within our tilted cube, and do not change the projection.
For points which project onto the origin in the chromaticity plane i. Mathematically, this definition of hue is written piecewise: Sometimes, neutral colors i.
These definitions amount to a geometric warping of hexagons into circles: After such a transformation, hue is precisely the angle around the origin and chroma the distance from the origin: The atan2 function, a "two-argument arctangent", computes the angle from a cartesian coordinate pair.
Notice that these two definitions of hue H and H 2 nearly coincide, with a maximum difference between them for any color of about 1.
The two definitions of chroma C and C 2 differ more substantially: While the definition of hue is relatively uncontroversial—it roughly satisfies the criterion that colors of the same perceived hue should have the same numerical hue—the definition of a lightness or value dimension is less obvious: Here are four of the most common fig.
All four of these leave the neutral axis alone. The creators of these models considered this a problem for some uses. For example, in a color selection interface with two of the dimensions in a rectangle and the third on a slider, half of that rectangle is made of unused space.
Now imagine we have a slider for lightness: To solve problems such as these, the HSL and HSV models scale the chroma so that it always fits into the range [0, 1] for every combination of hue and lightness or value, calling the new attribute saturation in both cases fig.
To calculate either, simply divide the chroma by the maximum chroma for that value or lightness. The HSI model commonly used for computer vision, which takes H 2 as a hue dimension and the component average I "intensity" as a lightness dimension, does not attempt to "fill" a cylinder by its definition of saturation.
Instead of presenting color choice or modification interfaces to end users, the goal of HSI is to facilitate separation of shapes in an image.
Saturation is therefore defined in line with the psychometric definition: See the Use in image analysis section of this article. Using the same name for these three different definitions of saturation leads to some confusion, as the three attributes describe substantially different color relationships; in HSV and HSI, the term roughly matches the psychometric definition, of a chroma of a color relative to its own lightness, but in HSL it does not come close.
Even worse, the word saturation is also often used for one of the measurements we call chroma above C or C 2. The original purpose of HSL and HSV and similar models, and their most common current application, is in color selection tools.
At their simplest, some such color pickers provide three sliders, one for each attribute. Most, however, show a two-dimensional slice through the model, along with a slider controlling which particular slice is shown.
Several color choosers from the s are shown to the right, most of which have remained nearly unchanged in the intervening time: Some more sophisticated variants are designed for choosing whole sets of colors, basing their suggestions of compatible colors on the HSL or HSV relationships between them.
Most web applications needing color selection also base their tools on HSL or HSV, and pre-packaged open source color choosers exist for most major web front-end frameworks.
HSL and HSV are sometimes used to define gradients for data visualization , as in maps or medical images. Image editing software also commonly includes tools for adjusting colors with reference to HSL or HSV coordinates, or to coordinates in a model based on the "intensity" or luma defined above.
In particular, tools with a pair of "hue" and "saturation" sliders are commonplace, dating to at least the lates, but various more complicated color tools have also been implemented.
For instance, the Unix image viewer and color editor xv allowed six user-definable hue H ranges to be rotated and resized, included a dial -like control for saturation S HSV , and a curves -like interface for controlling value V —see fig.
Video editors also use these models. These have been copied widely, but several imitators use the HSL e. The applications of such tools include object detection, for instance in robot vision ; object recognition , for instance of faces , text , or license plates ; content-based image retrieval ; and analysis of medical images.
For the most part, computer vision algorithms used on color images are straightforward extensions to algorithms designed for grayscale images, for instance k-means or fuzzy clustering of pixel colors, or canny edge detection.
At the simplest, each color component is separately passed through the same algorithm. It is important, therefore, that the features of interest can be distinguished in the color dimensions used.
Starting in the late s, transformations like HSV or HSI were used as a compromise between effectiveness for segmentation and computational complexity.
They can be thought of as similar in approach and intent to the neural processing used by human color vision, without agreeing in particulars: In recent years, such models have continued to see wide use, as their performance compares favorably with more complex models, and their computational simplicity remains compelling.
While HSL, HSV, and related spaces serve well enough to, for instance, choose a single color, they ignore much of the complexity of color appearance.
Essentially, they trade off perceptual relevance for computation speed, from a time in computing history high-end s graphics workstations, or mids consumer desktops when more sophisticated models would have been too computationally expensive.
If we plot the RGB gamut in a more perceptually-uniform space, such as CIELAB see below , it becomes immediately clear that the red, green, and blue primaries do not have the same lightness or chroma, or evenly spaced hues.
Furthermore, different RGB displays use different primaries, and so have different gamuts. If we take an image and extract the hue, saturation, and lightness or value components, and then compare these to the components of the same name as defined by color scientists, we can quickly see the difference, perceptually.
For example, examine the following images of a fire breather fig. The original is in the sRGB colorspace. Though none of the dimensions in these spaces match their perceptual analogs, the value of HSV and the saturation of HSL are particular offenders.
Such perversities led Cynthia Brewer, expert in color scheme choices for maps and information displays, to tell the American Statistical Association:.
Computer science offers a few poorer cousins to these perceptual spaces that may also turn up in your software interface, such as HSV and HLS.
Perceptual color dimensions are poorly scaled by the color specifications that are provided in these and some other systems. For example, saturation and lightness are confounded, so a saturation scale may also contain a wide range of lightnesses for example, it may progress from white to green which is a combination of both lightness and saturation.
These flaws make the systems difficult to use to control the look of a color scheme in a systematic manner. If much tweaking is required to achieve the desired effect, the system offers little benefit over grappling with raw specifications in RGB or CMY.
If these problems make HSL and HSV problematic for choosing colors or color schemes, they make them much worse for image adjustment.
HSL and HSV, as Brewer mentioned, confound perceptual color-making attributes, so that changing any dimension results in non-uniform changes to all three perceptual dimensions, and distorts all of the color relationships in the image.
In the example below fig. Notice how the hue-shifted middle version without such a correction dramatically changes the perceived lightness relationships between colors in the image.
The creators of HSL and HSV were far from the first to imagine colors fitting into conic or spherical shapes, with neutrals running from black to white in a central axis, and hues corresponding to angles around that axis.
Similar arrangements date back to the 18th century, and continue to be developed in the most modern and scientific models.
First, we compute chroma, by multiplying saturation by the maximum chroma for a given lightness or value. Next, we find the point on one of the bottom three faces of the RGB cube which has the same hue and chroma as our color and therefore projects onto the same point in the chromaticity plane.
Finally, we add equal amounts of R , G , and B to reach the proper lightness or value. Then we can find a point R 1 , G 1 , B 1 along the bottom three faces of the RGB cube, with the same hue and chroma as our color using the intermediate value X for the second largest component of this color:.
At this point we get something similar to red shape from fig. We observe following shape properties Fig. First, we find chroma:. Then we can, again, find a point R 1 , G 1 , B 1 along the bottom three faces of the RGB cube, with the same hue and chroma as our color using the intermediate value X for the second largest component of this color:.