Lost your password?
Don't have an account? Sign Up
0 student
Training Date :6 6-9 July 2021                                                         

สำคัญ!!! กรุณารอการยืนยันเปิดการอบรมจากเจ้าหน้าที่ก่อนการชำระค่าลงทะเบียน

Time : 24 ชั่วโมง
Days :  4 วัน
Duration : 09:00 – 16:00 น.
Fee : ราคาปกติ 20,330 THB   6,955 THB
ราคารวมภาษีมูลค่าเพิ่มร้อยละ 7 และได้รับการยกเว้นไม่ต้องหักภาษี ณ ที่จ่าย ร้อยละ3


Language : ไทย
Instructor : อ.ทัพนันทน์ เอี่ยวพานทอง, ผู้อำนวยการศูนย์ระบบอัจฉริยะ มหาวิทยาลัยอัสสัมชัญ
Who Should Attend : โปรแกรมเมอร์ที่อยากพัฒนาความรู้ด้าน AI หรือผู้ที่สนใจอยากพัฒนาทักษะ AI ไม่จำกัดเพศและอายุ
PREREQUISITE Pass “STEP 3 : Math & Statistics for Data Science” course or Have basic knowledge in Deep Learning
Description         A training workshop on the design and implementation of computer vision applications for object detection and recognition, using modern deep learning tools and technologies. Topics include an introduction to object detection and recognition, using R-CNN and the inception models, SSD architecture and MobileNet, and approaches for training deep learning models for object classification.
Course Syllabus
  • Lesson 1 Introduction to Object Detection & Recognition
    (6 hours)
    1.1. Overview of object detection tasks & pipelines
    1.2. Object detection using YOLO
    1.3. Overview of object recognition
    1.4. Example: Face recognition using FaceNet
  • Lesson 2 R-CNN & the Inception Models
    (6 hours)
    2.1. Understanding R-CNN family of algorithms
    2.2. Object detection using R-CNN & pre-trained models
    2.3. Understanding Inception models
    2.4. Training an Inception model for object recognition
  • Lesson 3 SSD Architecture & MobileNet Models
    (6 hours)
    3.1. Overview of SSD architecture
    3.2. Object detection using SSD: OpenCV’s Caffe Model example
    3.3. Understanding MobileNet models
    3.4. Training MobileNet for object recognition
  • Lesson 4 Object Classification
    (6 hours)
    4.1. Overview of object classification problems
    4.2. Importance of feature extraction: feature embeddings
    4.3. Training a deep learning model for feature extraction
    4.4. Pipelining object detection & classification for real-world applications
Payment Condition : Payment can be made by:

1. Cash or Credit Card or Bank Cheque payable to “Software Park Thailand #2” (a post-dated cheque is not accepted) on the first day of the service or within the last day of the service.
2. Account transfer and send the proof of the payment (the deposit slip) via fax or email to fax no. 02-583-2884 or email ttd@swpark.or.th

2.1 Siam Commercial Bank, Chaengwattana Branch
Saving Account Number: 324-2-56262-0
Account Name: Software Park Thailand#2

2.2 Krungsri Bank, Chaengwattana (Software Park) Branch
Saving Account Number: 329-1-34850-3
Account Name: Software Park Thailand#2


  • Withholding tax (3%) is exempt.
  • Should you need to withdraw, you must send the notice of the withdrawal in writing no later than 7 working days before the commencement date. The cancellation less than 7 days will be subject to a fine of 40% of the fee.
  • Software Park Thailand reserves the rights to cancel courses due to unforeseen circumstances.
Contact Person : For more information, contact our course coordinator on:

Ms. Merinya Punsoun (Paeng)

Tel: +66-2583-9992 Ext. 1443

Fax: +66-2583-2884

Email: Merinya.pun@nstda.or.th , cc jirawan@swpark.or.th

You are encouraged to use the course schedule as a guide to plan your training. The schedule is accessible at www.swpark.or.th for more information.

0.00 average based on 0 ratings

5 Star
4 Star
3 Star
2 Star
1 Star
20,330 ฿ 6,955 ฿

Course Features

  • Lectures 0
  • Quizzes 0
  • Students 0
  • Assessments Yes