Nghi Huynh
Entry-Level Data Scientist | Chess Strategist
Machine Learning Stories
2022
Vision beyond classification: Task 2: Image Segmentation
Image segmentation is a computer vision task in which we label specific regions of pixels in an image with their corresponding classes. Since we predict every pixel in the image, this task is commonly referred to as a dense prediction problem, whereas classification is a sparse prediction problem. There are two types of image segmentation: Semantic segmentation and Instance segmentation. In this story, we will explore both types.
Vision beyond classification: Task 1: Object Detection
Object detection is a classification and localization task. Its goal is to locate the presence of objects with bounding boxes and their corresponding classes in an image. In this story, we will explore object detection and some current state-of-the-art deep learning models designed to address it.
Convolutional Neural Networks for Image Recognition
A convolutional neural network (CNN or ConvNet) is a sequence of layers, and each layer of a ConvNet transforms one volume of activations to another through a differentiable function. ConvNets are often used for image classification and other computer vision tasks. In this story, we will explore CNN and how to build it.
An artificial neuron is a building block of artificial neural networks (models). Each artificial neuron represents a simple computation and reflects some neurophysiological observations from a real neuron. However, it does not mean to reproduce their dynamics. So, we often see or hear about the analogy of a real neuron vs an artificial neuron when talking about deep learning and neural networks. But what exactly is the similarity between these two? In this story, we will explore the similarities and differences betwen them.
Cell Instance Segmentation Using Mask R-CNN
Cell instance segmentation: is a Kaggle’s competition hosted by Sartorius- a partner of the life science research and the biopharmaceutical industry. In this competition, our task is to detect and delineate distinct objects of interest in biological images depicting neuronal cell types commonly used in the study of neurological disorders. In this story, we will explore how to apply Mask R-CNN to complete this task.