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Image Processing using Morphological Operations
Author(s): Ralph Caubalejo Computer Vision, Programming Morphing Time! (Image by Author) One of the most essential image processing techniques out there is the so-called morphological operation. As the name suggests, we use morphological operation in cleaning and correcting out the images. Normally, morphological …
Combining the Transformers Expressivity with the CNNs Efficiency for High-Resolution Image Synthesis
Author(s): Louis (What’s AI) Bouchard Tl;DR: They combined the efficiency of GANs and convolutional approaches with the expressivity of transformers to produce a powerful and… Continue reading on Towards AI » Published via Towards AI …
Yolov3 CPU Inference Performance Comparison — Onnx, OpenCV, Darknet
Author(s): Matan Kleyman Computer Vision Yolov3 CPU Inference Performance Comparison — Onnx, OpenCV, Darknet Opencv, Darknet, Onnxruntime Object Detection Frameworks | Image by author Choosing the right inference framework for real-time object detection applications became significantly challenging, especially when models should run on low-powered devices. In …
Deep Hashing for Similarity Search
Author(s): Rutuja Shivraj Pawar DEEP LEARNING, COMPUTER VISION An overview of the novel deep hashing neural networks from the literature Photo by Tolga Ulkan on Unsplash In recent years Approximate Nearest Neighbor (ANN) [1] search has become a prominent topic of research to effectively …
The AI-Powered Online Fitting Room: VOGUE
Author(s): Louis (What’s AI) Bouchard Google used a modified StyleGAN2 architecture to create an online fitting room where you can automatically try-on any pants or shirts you… Continue reading on Towards AI » Published via Towards AI …
The Strengths & Weaknesses of Face2Vec (FaceNet)
Author(s): Jacky Wong Computer Vision Face2Vec is the modern way of identifying the same/similar faces. Face2Vec refers to the process of transforming faces to vectors, a process named vectorization that transforms objects/images/text into numerical representations (if you would like to learn more, …
Image De-noising Using Deep Learning
Last Updated on January 23, 2021 by Editorial Team Author(s): Chintan Dave Computer Vision, Deep Learning Photo by Patrick Tomasso on Unsplash Denoising an image is a classical problem that researchers are trying to solve for decades. In earlier times, researchers used filters to …
DALL·E: Generate Images from Text Captions! Inspired by GPT-3 and Image-GPT from OpenAI
Author(s): Louis (What’s AI) Bouchard OpenAI successfully trained a network able to generate images from text captions. It is very similar to GPT-3 and Image GPT and produces… Continue reading on Towards AI » Published via Towards AI …
Tesseract OCR for Text Localisation and Detection
Author(s): Sharon Lim Automating the extraction of useful information from PDF files Continue reading on Towards AI » Published via Towards AI …
ResNeXt: from scratch
Author(s): Tanmay Debnath Source: Unsplash Computer Vision, Research ResNeXt follows a simple concept of ‘divide and conquer’. ResNeXt is often referred to as the Extended version of the ‘ResNet’. Some of its important applications are in the field of Biomedical Engineering department and …
Top 10 Computer Vision Papers 2020
Author(s): Louis (What’s AI) Bouchard The top 10 computer vision papers in 2020 with video demos, articles, code, and paper reference. Continue reading on Towards AI » Published via Towards AI …
Object Detection using OpenCV
Author(s): neupane parlad Object detection is an important part of image processing. The autonomous vehicle has to detect lanes, road surfaces, other vehicles… Continue reading on Towards AI » Published via Towards AI …
Efficient Biomedical Segmentation When Only a Few Label Images Are Available
Author(s): Makoto TAKAMATSU A Proposal for State-of-the-Art Unsupervised Segmentation Using Contrastive Learning Continue reading on Towards AI » Published via Towards AI …
CVPR2020 Paper Summary: Data Uncertainty in Face Recognition
Author(s): Makoto TAKAMATSU An facial recognition algorithm that effectively mitigates the negative impact of dirty samples during model training Continue reading on Towards AI » Published via Towards AI …
Making Hyper-personalized Books for Children: Faceswap on Illustrations
Author(s): Francesco Fumagalli Computer Vision Stories have always been part of human nature: we’ve been telling stories to children for as long as we’ve been around, to teach them about life, to warn them about dangers, to build up their character without …
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