RepVGG: A detailed Explanation for Structural Re-parameterization
Author(s): Gavin Originally published on Towards AI. Demystifying RepVGG: Unveiling the Secrets of Structural Re-parameterization This member-only story is on us. Upgrade to access all of Medium. — Why I’m writing this article about RepVGG when there are already several excellent resources …
Multiclass Image Classification — Hands-On with Keras and TensorFlow
Author(s): Carla Martins Originally published on Towards AI. Part 1 — Xception Image classification or computer vision is a branch of artificial intelligence where the task is to design systems that can recognize or classify objects based on digital images. It is …
Review: DCNv2 — Deformable ConvNets v2 (Object Detection & Instance Segmentation)
Author(s): Sik-Ho Tsang Originally published on Towards AI. Enhanced DCN / DCNv1, More Deformable, Better Results Deformable RoI Pooling In this article, Deformable ConvNets v2 (DCNv2), by the University of Science and Technology of China and Microsoft Research Asia (MSRA), is reviewed. …
Reading: ESRGAN — Enhanced Super-Resolution Generative Adversarial Networks (Super Resolution & GAN)
Author(s): Sik-Ho Tsang Originally published on Towards AI. Deep Learning Outperforms SRCNN, EDSR and RCAN, and SRGAN. Also, won the First Place in PIRM2018-SR challenge ESRGAN can have a sharper result than SRGAN In this story, Enhanced Super-Resolution Generative Adversarial Networks (ESRGAN), …
Reading: MegDet — A Large Mini-Batch Object Detector, 1st Place of COCO 2017 Detection Challenge (Object Detection)
Author(s): Sik-Ho Tsang Originally published on Towards AI. Computer Vision Large Mini-Batch Size of 256 With Warmup Learning Rate Policy and Cross-GPU Batch Normalization, the training time is reduced From 33 hrs To 4 hrs mmAP increases much faster with 256-batch In …
Let’s See How a Computer Sees…
Author(s): Pratik Originally published on Towards AI. Deep Learning, Programming Photo by Robina Weermeijer on Unsplash In humans, there are multiple stages to understand visual information, and the computer also follows this process. Let’s now try to zoom in a bit on …
From Pixels to Predictions: Unraveling Convolutional Neural Networks and the Magic of Transfer Learning
Author(s): Raman Rounak Originally published on Towards AI. Photo by Drew Dizzy Graham on Unsplash Introduction Hey there! Welcome to the AI wonderland, where mind-blowing technology is rocking the accuracy and brainpower charts. In this article, we’re diving headfirst into the captivating …
AlexNet: Implementation from Scratch
Author(s): Muhammad Arham Originally published on Towards AI. A PyTorch series for people starting with Deep Learning. Following an implementation-based approach of various well-known architectures. Image from Paper Introduction The Alexnet architecture was a breakthrough at the time of its publication, achieving …
DEEP LEARNING REVOLUTION: Unveiling the Potential of CONVOLUTIONAL NEURAL NETWORKS (CNNs) in Brain Tumor Detection
Author(s): Data Science meets Cyber Security Originally published on Towards AI. “From Basics to Advanced Techniques: A Comprehensive Guide and Case Study in Medical Image Analysis” SOURCE: https://gencraft.com/ INTRODUCTION: Welcome, curious minds, to a captivating journey that intertwines medicine, technology, and the …
Deep Learning from Scratch in Modern C++: Convolutions
Author(s): Luiz doleron Originally published on Towards AI. Let’s have fun by implementing 2D Convolution in C++. In the previous story, we covered some of the most relevant coding aspects of machine learning such as functional programming, vectorization, and linear algebra programming. …
Image classification with neural network Part — 2
Author(s): Mugunthan Originally published on Towards AI. Deep Learning If you missed my earlier blog, have a read here. My previous blog is little on the convolutional layer. One of the disadvantages of using a feed-forward network on images is a number …
Outline
Author(s): Sik-Ho Tsang Originally published on Towards AI. Review: DBPN & D-DBPN — Deep Back-Projection Networks For Super-Resolution (Super Resolution) Iterative Up & Down Projection Units, Outperforms SRCNN, FSRCNN, VDSR, DRCN, DRRN, LapSRN, and EDSR In this story, Deep Back-Projection Networks (DBPN) …
Review: G-RMI — 1st Runner Up in COCO KeyPoint Detection Challenge 2016 (Human Pose Estimation)
Author(s): Sik-Ho Tsang Originally published on Towards AI. Two-Stage Top-Down Approach: First, Person Detection. Then, Keypoint Detection. Two-stage Approach In this story, G-RMI for person keypoint detection or human pose estimation, by Google Inc., is reviewed. G-RMI, Google Research, and Machine Intelligence …
Beginners Guide to Convolutional Neural Network from Scratch — Kuzushiji-MNIST
Author(s): Satsawat Natakarnkitkul Originally published on Towards AI. Machine Learning Figure 1: Convolutional Neural Network (Source: https://en.wikipedia.org/wiki/Convolutional_neural_network) In the previous post, which you can check it out here, I have demonstrated various dimensional reduction techniques on Kuzushiji-MNIST (KMNIST) data set. In this …
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