
本地的,有指導的實時計算機視覺培訓課程通過互動式討論和實踐計算機視覺基礎知識演示,參與者逐步完成簡單的計算機視覺應用程序的創建。計算機視覺培訓可作為“現場實況培訓”或“遠程實時培訓”。現場實地培訓可在當地客戶所在地進行台灣或者在NobleProg公司的培訓中心台灣 。遠程實時培訓通過交互式遠程桌面進行。 NobleProg您當地的培訓提供商。
Machine Translated
客戶評論
我真的很喜歡親自動手的方法。
Kevin De Cuyper
課程: Computer Vision with OpenCV
Machine Translated
輕鬆使用VideoCapture功能從筆記本電腦相機中獲取視頻圖像..
HP Printing and Computing Solutions, Sociedad Limitada Unipe
課程: Computer Vision with OpenCV
Machine Translated
我很享受培訓師提供的關於如何使用這些工具的建議。這是從互聯網無法獲得的東西,非常有用..
HP Printing and Computing Solutions, Sociedad Limitada Unipe
課程: Computer Vision with OpenCV
Machine Translated
我很享受培訓師提供的關於如何使用這些工具的建議。這是從互聯網無法獲得的東西,非常有用..
HP Printing and Computing Solutions, Sociedad Limitada Unipe
課程: Computer Vision with OpenCV
Machine Translated
這很容易理解。
HP Printing and Computing Solutions, Sociedad Limitada Unipe
課程: Computer Vision with OpenCV
Machine Translated
培訓師非常了解,並且非常開放地反饋我們所涵蓋的內容和主題。我從培訓中收穫了很多,感覺我現在對圖像操作和一些技術有好把握,為圖像分類問題建立良好的訓練集。
Anthea King - WesCEF
課程: Computer Vision with Python
Machine Translated
Computer Vision子類別
Computer Vision課程大綱
聽眾
本課程面向尋求使用SimpleCV開發計算機視覺應用的工程師和開發人員。
本課程以MNIST為例,探討了Caffe作為圖像識別的深度學習框架的應用
聽眾
本課程適合有興趣使用Caffe作為框架的Deep Learning研究人員和工程師。
完成本課程後,代表們將能夠:
- 了解Caffe的結構和部署機制
- 執行安裝/生產環境/架構任務和配置
- 評估代碼質量,執行調試,監控
- 實施高級生產,如培訓模型,實施圖層和日誌記錄
Some of Marvin's video applications include filtering, augmented reality, object tracking and motion detection.
In this instructor-led, live course participants will learn the principles of image and video analysis and utilize the Marvin Framework and its image processing algorithms to construct their own application.
Format of the Course
- The basic principles of image analysis, video analysis and the Marvin Framework are first introduced. Students are given project-based tasks which allow them to practice the concepts learned. By the end of the class, participants will have developed their own application using the Marvin Framework and libraries.
在這一由講師引導的現場培訓中,學員將使用Python逐步創建簡單的計算機視覺應用程序,並從中習得計算機視覺的基礎知識。
在本次培訓結束後,學員將能夠:
- 了解計算機視覺的基礎知識
- 使用Python來實現計算機視覺任務
- 使用Python構建自己的計算機視覺應用程序
受衆
- 對計算機視覺感興趣的Python程序員
課程形式
- 部分講座、部分討論、練習和大量實操
Keras是一種用於快速開發和實驗的高級神經網絡API。它運行在TensorFlow , CNTK或Theano CNTK 。
這種以講師為主導的現場培訓(現場或遠程)是針對希望使用深度學習技術構建自動駕駛汽車的開發人員。
在培訓結束時,參與者將能夠:
- 使用計算機視覺技術識別車道。
- 使用Keras構建和訓練卷積神經網絡。
- 訓練深度學習模型以區分交通標誌。
- 模擬完全自動駕駛的汽車。
課程格式
- 互動講座和討論。
- 大量的練習和練習。
- 在實時實驗室環境中親自實施。
課程自定義選項
- 要申請本課程的定制培訓,請聯繫我們安排。
By the end of this training, participants will be able to:
- Install and configure the necessary development environment, software and libraries to begin developing.
- Build, train, and deploy deep learning models to analyze live video feeds.
- Identify, track, segment and predict different objects within video frames.
- Optimize object detection and tracking models.
- Deploy an intelligent video analytics (IVA) application.
By the end of this training, participants will be able to:
- Install and configure the necessary tools and libraries required in object detection using YOLO.
- Customize Python command-line applications that operate based on YOLO pre-trained models.
- Implement the framework of pre-trained YOLO models for various computer vision projects.
- Convert existing datasets for object detection into YOLO format.
- Understand the fundamental concepts of the YOLO algorithm for computer vision and/or deep learning.
課程格式
- 本課程介紹了模式匹配領域中使用的方法,技術和算法,因為它適用於Machine Vision 。
Audience
This course is directed at engineers and architects seeking to utilize OpenCV for computer vision projects
By the end of this training, participants will be able to:
- View, load, and classify images and videos using OpenCV 4.
- Implement deep learning in OpenCV 4 with TensorFlow and Keras.
- Run deep learning models and generate impactful reports from images and videos.
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