BSc: Introduction To Computer Vision - Revision history

N.zlatanov: /* Course activities and grading breakdown */

2023-08-28T06:29:20Z

Course activities and grading breakdown

← Older revision		Revision as of 06:29, 28 August 2023
Line 89:		Line 89:
	! Activity Type !! Percentage of the overall course grade		! Activity Type !! Percentage of the overall course grade
	\|-		\|-
−	\| Weekly Labs \|\| 55	+	\| Weekly Labs \|\| 50
	\|-		\|-
	\| Weekly Quizzes \|\| 10		\| Weekly Quizzes \|\| 10
Line 95:		Line 95:
	\| Midterm Exam \|\| 15		\| Midterm Exam \|\| 15
	\|-		\|-
−	\| Final Exam \|\| 20	+	\| Final Exam \|\| 25
	\|}		\|}

N.zlatanov: /* Activities and Teaching Methods */

2023-08-28T06:28:23Z

Activities and Teaching Methods

← Older revision		Revision as of 06:28, 28 August 2023
Line 113:		Line 113:

	= Teaching Methodology: Methods, techniques, & activities =		= Teaching Methodology: Methods, techniques, & activities =
−
−	== Activities and Teaching Methods ==
−	{\| class="wikitable"
−	\|+ Activities within each section
−	\|-
−	! Learning Activities !! Section 1 !! Section 2 !! Section 3 !! Section 4
−	\|-
−	\| Development of individual parts of software product code \|\| 1 \|\| 1 \|\| 1 \|\| 1
−	\|-
−	\| Homework and group projects \|\| 1 \|\| 1 \|\| 1 \|\| 1
−	\|-
−	\| Midterm evaluation \|\| 1 \|\| 1 \|\| 1 \|\| 1
−	\|-
−	\| Testing (written or computer based) \|\| 1 \|\| 1 \|\| 1 \|\| 1
−	\|-
−	\| Discussions \|\| 1 \|\| 1 \|\| 1 \|\| 1
−	\|}

N.zlatanov: /* Formative Assessment and Course Activities */

2023-08-28T06:27:56Z

Formative Assessment and Course Activities

@@ Line 129: / Line 129: @@
 |-
 | Discussions || 1 || 1 || 1 || 1
 |}

N.zlatanov: /* Course grading range */

2023-08-28T06:27:14Z

Course grading range

← Older revision		Revision as of 06:27, 28 August 2023
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	\| A. Excellent \|\| 91-100 \|\| -		\| A. Excellent \|\| 91-100 \|\| -
	\|-		\|-
−	\| B. Good \|\| 75-90 \|\| -	+	\| B. Good \|\| 78-90 \|\| -
	\|-		\|-
−	\| C. Satisfactory \|\| 60-74 \|\| -	+	\| C. Satisfactory \|\| 60-77 \|\| -
	\|-		\|-
	\| D. Poor \|\| 0-59 \|\| -		\| D. Poor \|\| 0-59 \|\| -

N.zlatanov: /* Course activities and grading breakdown */

2023-08-28T06:26:29Z

Course activities and grading breakdown

← Older revision		Revision as of 06:26, 28 August 2023
Line 89:		Line 89:
	! Activity Type !! Percentage of the overall course grade		! Activity Type !! Percentage of the overall course grade
	\|-		\|-
−	\| ~~Labs/seminar~~ ~~classes~~ \|\| 55	+	\| Weekly Labs \|\| 55
	\|-		\|-
	\| Weekly Quizzes \|\| 10		\| Weekly Quizzes \|\| 10

N.zlatanov: /* Course activities and grading breakdown */

2023-08-28T06:26:14Z

Course activities and grading breakdown

← Older revision		Revision as of 06:26, 28 August 2023
Line 89:		Line 89:
	! Activity Type !! Percentage of the overall course grade		! Activity Type !! Percentage of the overall course grade
	\|-		\|-
−	\| Labs/seminar classes \|\| 20	+	\| Labs/seminar classes \|\| 55
	\|-		\|-
		+	\| Weekly Quizzes \|\| 10
−	\| Interim performance assessment \|\| 50
	\|-		\|-
−	\| ~~Exams~~ \|\| 30	+	\| Midterm Exam \|\| 15
		+	\|-
		+	\| Final Exam \|\| 20
	\|}		\|}

N.zlatanov: /* Course grading range */

2023-08-28T06:24:56Z

Course grading range

← Older revision		Revision as of 06:24, 28 August 2023
Line 74:		Line 74:
	! Grade !! Range !! Description of performance		! Grade !! Range !! Description of performance
	\|-		\|-
−	\| A. Excellent \|\| 90-100 \|\| -	+	\| A. Excellent \|\| 91-100 \|\| -
	\|-		\|-
−	\| B. Good \|\| 75-89 \|\| -	+	\| B. Good \|\| 75-90 \|\| -
	\|-		\|-
	\| C. Satisfactory \|\| 60-74 \|\| -		\| C. Satisfactory \|\| 60-74 \|\| -

N.zlatanov: /* What is the main purpose of this course? */

2023-08-28T06:24:22Z

What is the main purpose of this course?

← Older revision		Revision as of 06:24, 28 August 2023
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	=== What is the main purpose of this course? ===		=== What is the main purpose of this course? ===
−	This course provides an ~~intensive~~ ~~treatment~~ of ~~a cross-section~~ of ~~the~~ ~~key~~ ~~elements~~ of ~~computer~~ ~~vision~~, with an emphasis on implementing ~~them~~ in ~~modern~~ ~~programming~~ ~~environments,~~ and using them to solve real-world problems. The course will begin with the ~~fundamentals of image processing and~~ image ~~filtering~~, but will quickly ~~build~~ to ~~cover~~ ~~more~~ ~~advanced~~ ~~topics~~, ~~including~~ image segmentation, object detection and recognition~~, face detection, content-based image retrieval, artificial neural networks, convolutional neural networks, generative adversarial networks and much more~~. A key focus of the course is on providing students with not only theory but also hands-on practice of building their computer vision applications.	+	This course provides an introductory but detailed treatment of computer vision techniques using machine learning, with an emphasis on implementing the computer vision algorithms from the scratch and using them to solve real-world problems. The course will begin with the image representation, but will quickly transition to computer vision techniques using machine learning, finishing with image segmentation and object detection and recognition. A key focus of the course is on providing students with not only theory but also hands-on practice of building their computer vision applications.

	=== ILOs defined at three levels ===		=== ILOs defined at three levels ===

N.zlatanov: /* Course Topics */

2023-08-28T06:21:09Z

Course Topics

@@ Line 22: / Line 22: @@
 ! Section !! Topics within the section
 |-
-| Image Acquisition and Basic Image Processing ||
+| Representation of images and videos ||
-# Computer vision in action
+# Computer representation
 |-
-| Image Filtering and Binary Vision ||
+| Image Classification ||
 |-
 |-
 |}
 == Intended Learning Outcomes (ILOs) ==

N.zlatanov: /* Short Description */

2023-08-28T06:15:55Z

Short Description

← Older revision		Revision as of 06:15, 28 August 2023
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	== Short Description ==		== Short Description ==
−	This course covers the following concepts: Computer vision ~~techniques;~~ ~~Classical and deep~~ learning models.	+	This course covers the following concepts: Computer vision using machine learning models.

	== Prerequisites ==		== Prerequisites ==