RWTHx’s Post

Thrilled to have completed the Image Processing Onramp course with MathWorks! I'm excited to apply the cutting-edge techniques learned to solve real-world problems. #ImageProcessing #MATLAB #TechEducation #MachineLearning

Image processing is the technique of enhancing digital images using computer algorithms. It involves a wide range of techniques to enhance, restore, analyze, and interpret images. In essence, image processing is a versatile field with a wide range of applications. GCE, Karad has setup a COE for Image Processing so students can understand the fundamental techniques and leveraging powerful tools, and can unlock the potential of digital images and gain valuable insights from the visual world. #imageprocessing #Centersofexcellence #gcekarad #mygcek

Article on Digital Image Processing. Digital Image Processing means processing digital image by means of a digital computer. We can also say that it is a use of computer algorithms, in order to get enhanced image either to extract some useful information. Digital image processing is the use of algorithms and mathematical models to process and analyze digital images. The goal of digital image processing is to enhance the quality of images, extract meaningful information from images, and automate image-based tasks. #snsdesignthinkers #snsinstitutions #designthinking #snsct

📢 Excited to share our latest blog post on "Function based sim-to-real learning for shape control of deformable free-form surfaces" on arXiv:2405.08935v1! In this post, we introduce a novel deformation function based sim-to-real learning method that bridges the gap between simulated and physically deformed shapes. Our approach accommodates sparsely distributed markers and effectively handles missing markers in captured frames. To learn more about this breakthrough in sim-to-real learning, click the link to read the full article: https://bit.ly/4dVzQZF. #Simulation #ShapeControl #DeformableSurfaces #InnovativeResearch

"Tutorial on Diffusion Models for Imaging and Vision" by Stanley Chan "The astonishing growth of generative tools in recent years has empowered many exciting applications in text-to-image generation and text-to-video generation. The underlying principle behind these generative tools is the concept of diffusion, a particular sampling mechanism that has overcome some shortcomings that were deemed difficult in the previous approaches. The goal of this tutorial is to discuss the essential ideas underlying the diffusion models. The target audience of this tutorial includes undergraduate and graduate students who are interested in doing research on diffusion models or applying these models to solve other problems." Paper: https://lnkd.in/dYmgWg-y #machinelearning #vae #diffusionmodels

https://lnkd.in/etGZj8YR Introduction to the mathematical foundations of signal and image processing using Fourier and Wavelet Transforms. Look for "Read and Download Links" section to download. #FourierSignalProcessing #WaveletSignalProcessing #dsp #imageprocessing #SignalProcessing

Another one! Wrapping up MathWorks Image Processing for Engineering and Science Specialisation with Course 3: Automating Image Processing! Throughout the course, I learned to: 🔹 Manipulate and threshold images to focus on key objects. 🔹 Reduce noise with spatial filters and enhance masks with morphology. 🔹 Calculate region properties like area, orientation, and perimeter. 🔹 Statistically identify and address outliers. For the final project, I applied these skills to detect moving cars in a video. Excited to apply these skills to projects and progress with the next course! 🌟 #ImageProcessing #ComputerVision #MATLAB #CPD

Efficient High-Resolution Image Synthesis with Linear Diffusion Transformer

Finding the similarity between paths even in a 2D is a challenging task. A combination of image processing and heuristic optimisations is used to solve. The methodology will be published soon.

If you're attending #NeurIPS2024 and interested in 3D vision and recent advances in Gaussian Splatting for reconstruction and normal estimation, be sure to visit another paper from my lab, #VL4AI, at the poster session tomorrow, 12th December, 4:30 - 7:30 p.m. PST. The poster will be presented by our PhD student, Meng Wei. Our paper, Normal-GS: 3D Gaussian Splatting with Normal-Involved Rendering, addresses key challenges in rendering and reconstruction in computer vision and graphics. We introduce Normal-GS, a novel approach that integrates normal vectors into the 3DGS rendering pipeline, improving both rendering quality and surface normal accuracy while maintaining real-time performance. Check out the paper here: https://lnkd.in/gPK9fWZu #3DVision #NeurIPS2024 #AI #ComputerVision #Research