EE 142: Pattern Recognition and Analysis of Sensor Data

← 2018-19 2019-20 2020-21 →
changes (lax) changes (strict) ▾ 2020-21 → 2020-21 →

Units: 4

Hours: Lecture, 3 hours; discussion, 1 hour

Catalog page 296

Prerequisites: EE 114 or STAT 155 or consent of the instructor

Description: Introduction to pattern recognition for multi-dimensional, multi- modal sensor data such as images, videos, and smart grids. Classification and decision functions, feature extraction, regression, and neural networks. Clustering and dimensionality reduction for unsupervised learning. Dynamic models and tracking. Applications of pattern recognition in computer vision, robotics, smart grids, etc.

Derived Information — The following is not part of the official catalog but is computed from catalog data.
Prerequisite graph not available.
Enrollment History (from UCR Banner, not catalog)
Combined: CS 171 / EE 142
Year F W S Su Total
2025-26 121/150 70/100  47/ 80 14/40 252/370
2024-25 108/150 81/100  79/ 80 11/40 279/370
2023-24 103/107 83/100  80/ 80 266/287
2022-23  64/120 62/100  58/ 63 184/283
2021-22  50/120 74/ 80  37/ 50 161/250
2020-21  34/120 55/ 80  34/ 50 123/250
2019-20  79/ 70 68/ 74 147/144
2018-19  67/ 70 113/140 180/210
2017-18  56/ 60 137/140 193/200
2016-17 117/120 117/120