Machine learning based image compressor.pdf
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ML algorithms operate on raw picture pixels, ignoring the fact that images are typically compressed. As a result, the image compression technique reduces training complexity.
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RTL IP Design
A variety of digital protocols
Communication buses as1G, 10G Ethernet
PCIe
DIGRF
STM16/64
HDMI.
Logic Fruit Technologies is also an expert in developing,
software-defined radio (SDR) IPs
Encryption
Signal generation
Data analysis, and
Multiple Image Processing Techniques.
Recently Logic Fruit technologies are also exploring FPGA acceleration on data centers for real-time data processing.
**Our Social Media Channels**
Facebook: https://www.facebook.com/LogicFruit/
Twitter: https://twitter.com/logicfruit
LinkedIn: https://www.linkedin.com/company/logi…
Website: https://www.logic-fruit.com/
#LFT #LogicFruitTechnologies #LogicFruit
Interested to view more SlideShares, Click on the below links,
https://www.slideshare.net/LogicFruit/a-designers-practical-guide-to-arinc-429-standard-3pptx
https://www.slideshare.net/LogicFruit/a-swift-introduction-to-milstd
https://www.slideshare.net/LogicFruit/arinc-the-ultimate-guide-to-modern-avionics-protocol/LogicFruit/arinc-the-ultimate-guide-to-modern-avionics-protocol
https://www.slideshare.net/LogicFruit/arinc-629-digital-data-bus-specifications/LogicFruit/arinc-629-digital-data-bus-specifications
https://www.slideshare.net/LogicFruit/afdx
https://www.slideshare.net/LogicFruit/end-system-design-parameters-of-the-arinc-664-part-7
https://www.slideshare.net/LogicFruit/compute-express-link-cxl-everything-you-ought-to-know
https://www.logic-fruit.com/blog/fpga/what-is-fpga/
https://www.slideshare.net/LogicFruit/cxl-vs-pcie-gen-5-the-brief-comparison
https://www.slideshare.net/LogicFruit/fpga-technology-development-and-market-trends-in-the-new-decade
https://www.slideshare.net/LogicFruit/fpga-design-an-ultimate-guide-for-fpga-enthusiasts
https://www.slideshare.net/LogicFruit/fpga-vs-asic-design-comparison
https://www.slideshare.net/LogicFruit/afdx-a-timedeterministic-application-of-arinc-664-part-7
https://www.slideshare.net/LogicFruit/fpgas-expansion-in-adas-autonomous-driving
https://www.slideshare.net/LogicFruit/take-a-step-ahead-with-an-upgrade-to-arinc-818-revision-3-avionic
Machine Learning for Images
Machine Learning for Images - what's specific, various implementation of image recognition, what can be build using image recognition via machine learning. Image recognition frameworks, CNN, cuda-convnet2, coffee, torch7, theano, etc.
Enhanced Image Compression Using Wavelets
Data compression which can be lossy or lossless is required to decrease the storage requirement and better data transfer rate. One of the best image compression techniques is using wavelet transform. It is comparatively new and has many advantages over others. Wavelet transform uses a large variety of wavelets for decomposition of images. The state of the art coding techniques like HAAR, SPIHT (set partitioning in hierarchical trees) and use the wavelet transform as basic and common step for their own further technical advantages. The wavelet transform results therefore have the importance which is dependent on the type of wavelet used .In our thesis we have used different wavelets to perform the transform of a test image and the results have been discussed and analyzed. Haar, Sphit wavelets have been applied to an image and results have been compared in the form of qualitative and quantitative analysis in terms of PSNR values and compression ratios. Elapsed times for compression of image for different wavelets have also been computed to get the fast image compression method. The analysis has been carried out in terms of PSNR (peak signal to noise ratio) obtained and time taken for decomposition and reconstruction.
Color based image processing , tracking and automation using matlab
Image processing is a form of signal processing in which the input is an image, such as a photograph or video frame. The output of image processing may be either an image or, a set of characteristics or parameters related to the image. Most image-processing techniques involve treating the image as a two-dimensional signal and applying standard signal-processing techniques to it. This project aims at processing the real time images captured by a Webcam for motion detection and Color Recognition and system automation using MATLAB programming.
In color based image processing we work with colors instead of object. Color provides powerful information for object recognition. A simple and effective recognition scheme is to represent and match images on the basis of color histograms.
Tracking refers to detection of the path of the color once the color based processing is done the color becomes the object to be tracked this can be very helpful in security purposes.
Automation refers to an automated system is any system that does not require human intervention. In this project I’ve automated the mouse that work with our gesture and do the desired tasks.
remove background ai using outcut.docx
AI-powered background removal techniques have revolutionized the editing of images by using deep learning algorithms to automatically distinguish foreground and background elements. This allows for fast and accurate isolation of subjects from their surroundings, saving time for creators. As the technology continues to evolve, background removal is becoming faster, more precise, and is enabling new applications across industries like e-commerce, advertising, and video production by seamlessly integrating subjects into different contexts. The integration of AI in visual processing is poised to further transform creativity.
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Deuglo has top Software Developers in India. They are experts in software development and help design and create custom Software solutions.
Deuglo follows seven steps methods for delivering their services to their customers. They called it the Software development life cycle process (SDLC).
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👉👉 Click Here To Get More Info 👇👇
https://sumonreview.com/ai-fusion-buddy-review
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Graspan: A Big Data System for Big Code Analysis
We built a disk-based parallel graph system, Graspan, that uses a novel edge-pair centric computation model to compute dynamic transitive closures on very large program graphs.
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These analyses were used to augment the existing checkers; these augmented checkers found 132 new NULL pointer bugs and 1308 unnecessary NULL tests in Linux 4.4.0-rc5, PostgreSQL 8.3.9, and Apache httpd 2.2.18.
- Accepted in ASPLOS ‘17, Xi’an, China.
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Machine learning based image compressor.pdf
- 1. What's in the store? Image compression powered by machine learning?
- 2. What is Machine Learning? Machine learning is a subfield of artificial intelligence (AI) and computer science that focuses on using data and algorithms to mimic human learning processes and progressively increase accuracy.
- 3. How Machine Learning Powers Image Compression Image compression has undergone a revolution as a result of machine learning techniques, which enable algorithms to learn from massive quantities of data and adaptively alter compression schemes to obtain greater compression ratios while keeping acceptable image quality. In the future, we can anticipate even more effective and efficient picture compression techniques as machine learning develops.
- 4. Benefits of using Image Compression More photos can be saved in a given amount of disk or memory space by lowering file size. When broadcast over the internet or downloaded from a webpage, the image uses less bandwidth, minimizing network congestion and speeding up content delivery.
- 5. Choose ML-Powered Image Compression ML-PIC is a cutting-edge image compression method ML-PIC is a cutting-edge image compression method that uses machine learning to generate outstanding that uses machine learning to generate outstanding compression results while maintaining or even compression results while maintaining or even improving picture quality. It's especially well-suited for improving picture quality. It's especially well-suited for applications requiring high picture quality and applications requiring high picture quality and compression efficiency, such as medical imaging, compression efficiency, such as medical imaging, remote sensing, and multimedia communication. remote sensing, and multimedia communication.
- 6. The Future with ML-Powered Image Compression The future of ML-Powered picture Compression is one of enhanced efficiency, improved picture quality, and larger applicability across several disciplines. As machine learning and AI technologies evolve, ML-PIC will stay at the vanguard of data compression and play a critical role in changing how we store, transmit, and interact with visual data in the digital age.
- 7. Conclusion Machine learning-powered image compression is a promising technology that combines the advantages of data economy, picture quality preservation, and flexibility. As this subject develops, it has the potential to transform how we manage and transmit visual data in a variety of applications, eventually benefiting both companies and consumers.
- 8. Machine learning empowers image compression to find the delicate balance between preserving quality and optimizing data, reshaping the way we visualize and transmit the world.