Prof. Dr. Eng. FITRI UTAMININGRUM, ST., MT.
Program Studi Magister Ilmu Komputer
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The combination of gray level co-occurrence matrix and back propagation neural network for classifying stairs descent and floor
Kursi roda pintar dengan Multi Navigasi
Pentingnya Pelatihan Google Colaboratory Sebagai Upaya Penyelesaian Masalah Komputasi Data yang Besar
Modul Pelatihan Google Colab
Feature Selection of Gray-Level Co-occurrence Matrix Using Genetic Algorithm with Extreme Learning Machine Classification for Early Detection of Pole Roads
PELATIHAN PENGENALAN DAN PENERAPAN TEKNOLOGI ARTIFICIAL INTELLIGENCE UNTUK MENINGKATKAN KOMPETENSI GURU SMK NEGERI 5 KOTA MALANG
ALAT KONTROL DAN PREDIKSI HIDROGEN MENGGUNAKAN MACHINE LEARNING
Melaleuca leaves extract as eco-friendly inhibitor for low carbon steel in sulfuric acid
STUDI KELAYAKAN KONTROL DAN PREDIKSI HIDROGEN MENGGUNAKAN MACHINE LEARNING PADA PROSES KOROSI ALUMINIUM DALAM LINGKUNGAN DENGAN INHIBITOR ORGANIK
The potential of nanocomposite-based coatings for corrosion protection of metals: A review
Deciphering pixel insights: A deep dive into deep learning strategies for enhanced indoor depth estimation
Workshop Pengenalan Sistem Berbasis Kecerdasan Buatan Untuk Peningkatan Hardskill Guru SMK
Swin Transformer Adaptation into YOLOv7 for Road Damage Detection
A convolutional neural network -VGG16 method for corrosion inhibition of 304SS in sulfuric acid solution by timoho leaf extract
Komposisi Bahan Inhibitor Korosi Aluminium 6061 Dari Kulit Alpukat dalam Lingkungan Korosif yang Bersifat Asam
Cellulose Nanofibers of Oil Palm Fronds as a Filler in Nanocomposites Coating for Corrosion Protection of Copper
Accelerating Nameplate Detection for Autonomous Smart Wheelchairs Utilize YOLOv8n-GSM
Enhancing Ergonomic Aspects in Smart Wheelchair Design Through a User-Centered Approach
Diseminasi hasil penelitian di seminar internasional
Tim Dosen FILKOM UB Melakukan Pemasangan CCTV dengan Fitur Deteksi Objek Manusia berbasis AI
Enhancing Smart Wheelchair Navigation through Head Motion Detection: A YOLO-based Approach