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Computer Vision
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ILMU TEKNIK
TEKNIK ELEKTRO DAN INFORMATIKA
Teknik Informatika
IFB-301-CV
Pertemuan (14)- Image Classification Supervised & Unsupervised Learning
Source File K-Means
Source File K-Means
Click <a href="https://lmsspada.kemdikbud.go.id/pluginfile.php/724028/mod_resource/content/1/KMeans.ipynb" >KMeans.ipynb</a> link to view the file.
Silahkan teman-teman Cvisioner dapat menggunakan ini sebagai bahan untuk mem-praktekan K-Means
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◄ Modul Pemrograman K-means
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Deskripsi Matakuliah dan Peta Kompetensi
CPL, CPMK dan SUb-CPMK
Bahan Kajian (Materi Ajar Mata Kuliah)
Skema Perkuliahan dan Rencana Asesmen
RPS IFB-301 Computer Vision
Dosen Pengampu dan Pengajar
Referensi Matakuliah
Simulasi Operasi Computer Vision
Pixel Spot Detection
Pixel TalkBot
Link Zoom Kelas IFB-301 AA
Link Zoom Kelas IFB-301 BB
Pengumuman
List Collaborative Project Learning from industry
Trello-Monitoring Project Akhir
Handout Introduction of Computer Vision
Video Introduction of Computer Vision
Diskusi-Implementasi Computer Vision
Forum Introduction Computer Vision
Infografis Fundamental Step of Digital Image Processing
Handout Pengenalan Proses Konvolusi
Handout Cara Kerja Konvolusi
Video Cara kerja Konvolusi
Handout Jenis Kernel Konvolusi Citra
Video Jenis Kernel Konvolusi
Case study-Image Enhancement kelas AA
Case study-Image Enhancement Kelas BB
Solusi dan Penjelasan Quiz
Video HistogramEqualization
Handout Histogram Equalization
Handout Image Interpolation
Video Image Interpolation
Case: Histogram Equalization
Case: Histogram Equalization AA
Modul Pemrograman Image Enhancement
Video Tutorial Pemrograman Image Enhancement
Challenge Programming
Evaluasi Image Enhancement
Warming-up
Infografis Fundamental Step of Digital Image Processing
Handout Canny Edge Detection
Video Canny Edge Detection
Modul Canny Edge Detection
Video Tutorial Canny Edge Detection
Handout Otsu's Thresholding
Video Otsu's Thresholding
Modul Otsu Thresholding
Video Tutorial Otsu's Thresholding
Case-based: Image Segmentation
Forum Diskusi Contour Segmentation
warming-up AA
warming-up BB
Handout Watershed Algorithm
Video Watershed Segmentation
Video Tutorial Algoritma Watershed
Modul Algoritma Watershed
Problem-based Learning: Identifikasi dan Pemisahan Wadah Medis dalam Gambar untuk Pengisian Cairan (Kasus dari DUDI)
Evaluation Image Segmentation
Collecting Image Dataset
Handout Color Feature Extraction
Video Color-based Feature Extraction
Video Tutorial Color Histogram
Color Histogram || Challenge Programming
List Collaborative Project Learning from industry
Handout Chain COde
Video Penjelasan Chain Code
Handout Histogram Orientation of Gradient
Video HOG
Modul Histogram Orientation Gradient (HOG)
Video Tutorial Histogram Orientation Gradient (HOG)
Forum Feature Extraction
UTS IFB-301 Computer Vision
Solusi Ujian Tengah Semester
Rincian Nilai Rencana Tugas Mahasiswa
Handout Local Binary Pattern (LBP)
Video Local Binary Pattern (LBP)
Modul Local Binary Pattern (LBP) dan SIFT (Scale Invariant Feature Transform)
Video Tutorial LBP dan SIFT Descriptor
Warming-up | Local Binary Pattern
Forum Diskusi Feature Extraction
Evaluasi Feature Extraction
Warming up
Topik Pembahasan Image Stitching
Modul Image Stitching
Forum Image Stitching
Evaluasi Image Stitching
Warming-up
Modul dan Video Optical Flow | Video Analysis & Motion Tracking
Video Tutorial Video Tracking Optical Flow
Modul Pembelajaran Pemrograman Optical Flow
Case-study Pemrograman Optical Flow
Forum Optical Flow
Evaluasi Video Analysis & Motion Tracking
Infografis Convolutional Neural Network (CNN)
Animation of Convolutional Neural Network Process
Video Penjelasan CNN
Video Tutorial Pemrograman CNN
File Python CNN
Modul Pembelajaran Pemrograman CNN
Case-Study Deep Learning
Evaluasi Convolutional Neural Network
Infografis Support Vector Machine (SVM)
Handout Support Vector Machine (SVM)
Video Penjelasan Image Classification Supervised & Unsupervised Learning
Handout Support Vector Machine
Video Tutorial SVM
File Python SVM
Infografis K-Nearest Neighbor (KNN)
Modul Pemrograman K-NN
File Python KNN
Infografis K-Means
Modul Pemrograman K-means
Student Learning Activity at Home
Supervised and Unsupervised Learning
Evaluasi Supervised and Unsupervised Learning
RTM Project Akhir
Aplikasi dan Video Demo
Laporan Akhir
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Course sections
Introduction
Pertemuan 1-Introduction Computer Vision
Pertemuan 2-Tapis Linear Konvolusi | Image Enhancement
Pertemuan 3-Histogram Equalization & Image Interpolation| Image Enhancement
Pertemuan 4-Contour Segmentation | Image Segmentation
Pertemuan 5-Watershed Segmentation| Region-based segmentation
Pertemuan 6-Color Based: Color histograms & color moments|Feature Extraction
Pertemuan 7-Chain Code and HOG| Shape and OerientationFeature descriptor
Pertemuan 8-Ujian Tengah Semester (UTS)
Pertemuan 9-Local Binary Pattern | Texture-based feature descriptor
Pertemuan 10-Image Stitching
Pertemuan 11- Optical Flow | Video Analysis & Motion Tracking
Pertemuan (12-13)-Convolutional Neural Network (CNN) | Deep Learning Image Classification & Detection
Pertemuan (14)- Image Classification Supervised & Unsupervised Learning
Project Akhir Computer Vision
Pertemuan 16-UJIAN AKHIR SEMESTER