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Computer Vision - 计算机视觉

计算机视觉Computer VisionVision System
MAEG5720 Computer Vision in Practice - Mini-Project2: Panorama
计算机视觉Computer VisionVision System
The field of view of the image is limited by your lens. However, we could solve this issue by combining multiple images together to form a panorama. The aim of this assignment is to automatically stitch the images acquired by a panning camera.
Introduction to Computer Vision (ECSE 415) Assignment 5: Segmentation
计算机视觉Computer VisionVision System
In this section, you will be asked to compute image segmentations by using several basic clustering techniques. Clustering is used to determine the class of each pixel, and the result can be different depending on the feature space. The images for this part are placed under the same dictionary.
CS 6476: Computer Vision - Final Project Overview and Topics List
计算机视觉Computer VisionVision System
For the final project you will apply knowledge that you have learned in class plus additional research to build a computer vision system that achieves near state-of-the-art results in an area you select.
COMP 4102A Computer Vision: Assignment 1: SVD, Edge Detection and Sticks filter
计算机视觉Computer VisionVision System
Write a function that finds edge intensity and orientation in an image. Display the output of your function for one of the given images in the handout
Introduction to Computer Vision (ECSE 415) Assignment 4: Neural Networks
计算机视觉Computer VisionVision System
For this assignment, you are going to train models on the subset derived from the publicly available CIFAR-10 dataset source. The CIFAR-10 dataset consists of 60000 32x32 color images in 10 classes, with 6000 images per class.
Computer vision 2022 Assignment 3: Deep Learning for Perception Tasks
计算机视觉Computer VisionVision System
For this exercise, we will provide a demo code showing how to train a network on a small dataset called FashionMinst. Please go through the following tutorials first. You will get a basic understanding about how to train an image classification network in pytorch. You can change the training scheme and the network structure. Please answer the following questions then. You can orginaze your own text and code cell to show the answer of each questions.
[2022] UNSW - COMP9517 Computer Vision - Lab1 Image Processing
计算机视觉Computer VisionVision System
This lab revisits important concepts covered in the Week 1 and Week 2 lectures and aims to make you familiar with implementing specific algorithms.
[2022] UNSW - COMP9517 Computer Vision - Lab2 SIFT: Scale-Invariant Feature Transform
计算机视觉Computer VisionVision System
A well-known algorithm in computer vision to detect and describe local features in images is the scale-invariant feature transform (SIFT). Its applications include object recognition, mapping and navigation, image stitching, 3D modelling, object tracking, and others.
[2022] COMPSCI 773 Intelligent Vision Systems - Assignment2 Camera Calibration
计算机视觉Computer VisionVision System
This assignment will look at the optical distortion free camera calibration components (step 1 and 2) of the full stereo vision pipeline with other components of the pipeline explored in subsequent assignments.
[2022] UNSW - COMP9517 Computer Vision - Lab4 Image Segmentation
计算机视觉Computer VisionVision System
The goal of image segmentation is to assign a label to each pixel in an image, indicating whether it belongs to an object (and which object) or the background. In this lab the MeanShift clustering algorithm and the Watershed algorithm will be used to solve unsupervised image segmentation.
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