ECE4076
Computer vision
基本信息
| 学分 | 6 credit points |
|---|---|
| 开课学期 | First semester |
| 校区 | Malaysia |
| 考核构成 | Lab assessments — 32% Final assessment — 60% Quizzes — 8% |
开课安排1 条
| 教学期 | 授课方式 | 状态 |
|---|---|---|
| First semester | Teaching activities are on-campus (ON-CAMPUS) | 开课 |
以上为该校区在官方资料中登记的全部开课安排，不是汇总。同一门课可能在多个 教学期开课，也可能不同教学期的授课方式不同。
课程简介
This unit aims to develop an understanding of methods for extracting useful information (eg 3-D structure; object size, motion, shape, location and identity, etc) from images. It will allow you to understand how to construct computer vision systems for robotics, surveillance, medical imaging, and related application areas.
以上为 Monash Handbook 的官方原文，版权属 Monash University，此处按本站要求转载并标注出处： 官方页面 ↗
学习成果6 条
官方原文（Learning outcomes），版权属 Monash University。
- ULO1 Interpret and apply mathematical optimisation, linear algebra, and supervised and unsupervised learning to computer vision problems.
- ULO2 Simulate cameras using projective and multi-view geometry to design model-based vision systems and algorithms that extract 3D and rotational information from images, alongside methods for image registration and stitching.
- ULO3 Differentiate between elements of the human visual system and computer vision pipelines, and reflect on the consequences for the design of algorithms for scene understanding.
- ULO4 Generate and document implementations of low, mid and high-level vision processes such as filtering and structure from motion, image segmentation and clustering, and model fitting and tracking.
- ULO5 Design ethical machine learning solutions to problems in computer vision, such as image classification, 3D reconstruction and pose estimation, object detection and semantic segmentation, by critically appraising information and publications.
- ULO6 Demonstrate the development, training and deployment of computer vision algorithms using a high-level programming language.
教学方式与预期工作量
教学方式
Peer assisted learning - Active participation in the Slack discussion forums (Clayton-only) and the practical sessions (Clayton and Malaysia).
Enquiry-based learning - Active participation in laboratories.
Problem-based learning - Active participation in the practicals.
Active learning - Participation and problem-solving in the laboratories and practical sessions.
预期工作量
The minimum total expected workload to achieve the learning outcomes for this unit is 144 hours per semester typically comprising a mixture of 3-6 hours of scheduled learning activities and 6-9 hours of independent study per week. Scheduled activities may include a combination of teacher-directed learning, peer-directed learning and online engagement. Independent study may include associated readings, assessment and preparation for scheduled activities.
官方原文，版权属 Monash University。
先修 / 同修要求
以下先修关系按官方来源的结构化先修字段解析，原始记号：ENG1005 AND (ECE2071 OR ECE2191)
先修链路
按官方先修字段的原始分组展开，AND / OR 的区别保留着—— 「A 或 B」和「A 与 B」在选课时是两回事。每门课点进去可以继续往下看。
互斥课程1 门
这些课和本课内容重叠，不能同时算进同一个学位（官方目录的 Prohibition 字段）。选了其中一门，另一门通常只能算选修学分甚至完全不计—— 这跟先修不同，先修是"没修过就不能选"，互斥是"修了也不能两门都算"。
原始记号：ECE5176
数据来源
- 数据来源
- 官方网页
handbook.monash.edu ↗ - 抓取时间
- 2026-09-13
- 可信度
- 程序抓取，未人工核实
查看官方完整描述 ↗ — 事实性字段（代码、学分、教学期、授课方式、考核权重、先修/同修/互斥关系）与 课程简介、学习成果、教学方式、预期工作量均取自官方 Handbook； 正文版权属 Monash University，此处转载并逐处标注出处。
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