**Dreamweaver:** At this writing, Adobe has stopped updating its Adobe Dreamweaver web editing and authoring tool and has moved developers to Adobe Creative Suite 6 instead.

Figure 17-2 shows how the various tools on a page can be linked together.

I’ll break down what Photoshop Elements can do, the advanced features and how to use them. Some things like file resolution, duration and RAW files are covered in greater detail in the Photoshop Elements tutorial.

Computer

The computer you use to edit images can be a laptop, desktop, or even a mobile phone. As long as you have Adobe Photoshop Elements installed, you can edit images on a computer.

Adobe Photoshop Elements is for anyone who edits images. It is great for photographers, graphic designers and web designers.

Photoshop Elements is available in macOS and Windows. macOS users can run Photoshop Elements on a Mac or a Windows computer.

You can also run Photoshop Elements on a Chromebook. Simply download and install Photoshop Elements using Google Chrome.

Quick Access

Photoshop Elements has a shortcut bar at the top of the screen. If you’re viewing multiple pages in the program, you can access this shortcut bar with a keyboard shortcut.

Since you’re probably using it to edit images, here are the keyboard shortcuts:

1. Open ():

⇧ Shift + 1

⇧ Alt + 1

⇧ Ctrl + 1

2. Close ():

⇧ Shift + 2

⇧ Alt + 2

⇧ Ctrl + 2

Advanced Tools

In addition to shortcuts, Photoshop Elements lets you control your editing tools with hotkeys.

With Photoshop Elements, you can edit images, create new images, and more by using the following advanced tools:

Cropping: Adjust image details such as size, brightness, contrast, and color using a series of sliders and controls.

Adjust image details such as size, brightness, contrast, and color using a series of sliders and controls. File adjustments: A powerful tool for making basic edits to your images.

A powerful tool for making basic edits to your images. Color: Adjust colors and saturate images based on their colors.

Adjust colors and saturate images based on their colors. Grayscale: Convert images to grayscale, adjust the color, contrast, brightness and text.

Convert images to grayscale, adjust the color, contrast, brightness and text. History: Create a “go back” and “go forward” to a previous state in your image.

Create a “go back”
05a79cecff

. Noticeable improvements in accuracy and speed are achieved at both image resolutions.

**Training examples.** We first use a subset of images from the MS-COCO benchmark dataset [@lin2014microsoft], the *Microsoft COCO Dataset* which consists of 80,000 images with annotations of their instance segmentations and class labels. We utilize 20,000 images for training and 60,000 images for testing, and train DeepLabv3Plus on those images.

To evaluate the performance of DeepLabv3Plus without any assistance, we randomly select 25 images in the first 600 testing images, and the predictions are shown in Fig. \[fig:extract\](b). The CE in the bottom-right corner shows a localization error of about 9 pixels. To further verify the performance of DeepLabv3Plus in the presence of external data, we use the same testing images but add a few simple data augmentations using external data such as the Pascal VOC images [@everingham2015pascal] (these images have labels and instance segmentation masks). The results are shown in Fig. \[fig:extract\](c) and (d). DeepLabv3Plus obtains better performance after adding external data. The CE for DeepLabv3Plus in Fig. \[fig:extract\](d) is much smaller than that without external data. These results are consistent with a previous study [@Liu_2017_CVPR], that adding external data to the backbone network can improve the accuracy and robustness of a CNN.

**Visualization.** We further show some visualizations of the proposed approach in Fig. \[fig:all\_sample\], where all the latent semantic segmentation masks and corresponding labels are given. One can see that DeepLabv3Plus generates discriminative semantic segmentations, and it is fairly reliable for the boundaries.

Conclusion
==========

In this paper, we propose to effectively use the recursive strategy for CNN training. The proposed approach is more robust and faster than state-of-the-art full CNN training methods. The improved performance comes from two-fold. We first find that the reconstruction constraint at each latent-semantic level can suppress the gradients back to the low-level output of the previous layer. This helps to alleviate over-fitting to the low-level detail of the original images. This is achieved through a novel

The state has invested $25 million in cash or debt in next year’s budget, and more is planned, under the guidelines Gov. Jerry Brown and his revenue watchdogs outlined Wednesday.

The budget deals with issues ranging from state firefighting to healthcare for the homeless, more funds for college scholarships, and money for the California Arts Council, the Reentry Program and the Health Workers for Health Equity initiative.

The administration has also taken on some of the more arcane parts of government, turning over child-support collections to private contractors, or consulting the U.S. Department of Homeland Security for help on fire-prevention measures.

The governor proposed a 5 percent funding boost for some state agencies under a formula that was added as a major state policy shift in December.

But the main emphasis of the new budget plan remains on what the administration terms Brown’s “Plan B” — redirecting money that has been held up in court for high-cost appellate litigation against the budget cuts Brown implemented last year.

On Wednesday, Brown pointed out the cap-and-trade program and the cap on gas-guzzling trucks as areas where Californians are receiving relief after the 2011-12 state budget cut $2 billion.

The “truck relief” has been replaced with money for an “Alternative Fuel Assistance Program” that will pay up to $100 for a covered truck that runs on compressed natural gas.

The program will be reviewed in October to determine whether it still should be funded in the 2014-15 budget.

“If the numbers are right, it’s money well spent,” said Brown, as the cap-and-trade program faces a possible legal challenge from the Western Center on Law and Poverty.

Brown’s transportation department has been directed to expand an electronic toll program with new technology that will replace cash when cars begin paying tolls on all major roads entering Los Angeles.

He also plans to boost the four-year-old program by $24 million.

The cash payments into the state’s education programs would go toward scholarships for college and UC or CSU students, as well as for students in schools operating at 100% of capacity.

Brown said he supports the governor’s 2014 budget proposal to redirect $15 million of the state’s cap-and-trade revenue to education from criminal justice.

The state is currently using

Windows
Intel Pentium 4/AMD Athlon 64 3000+/AMD Opteron 2200
2 GB of RAM (enough RAM for up to 4 players)
1024 x 768 Display
DirectX 9.0c compatible video card
Basic knowledge of C++
Windows Vista Home Premium or Windows 7 Starter
Mac
Intel Core 2 Duo (Intel Core 2 Duo Macs only run Mac OS X 10.5.7 or higher)
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