SyeedaOthman's Stars
AgungHari/personal-site-agung
This project will always be in development, as it is my personal website and will evolve along with my life journey. This project is built using TypeScript, Next.js, and Tailwind CSS.
SyeedaOthman/Smart-Wheelchair-Control-Based-on-Spatial-Features-of-Hand-Gesture.
Collaborating with I Gusti Ngurah Agung Hari Vijaya Kusuma, this project involves training a CNN model with a dataset of hand movement pose. Real time predicted pose will then used to control wheelchair movement.
SyeedaOthman/Forecasting-USDCHF-in-Forex-with-LSTM
Forecasting USDCHF in Forex with LSTM is a machine learning-based project aimed at predicting the price of the USD/CHF currency pair in Forex using an LSTM (Long Short-Term Memory) model. This project uses historical exchange rate data of USD/CHF, particularly the closing price (Close), to train a model capable of predicting future price movements.
AgungHari/Temp_Kursi_Roda
AgungHari/temp_Pengembangan-Kursi-Roda-Otonom-Berbasis-Yolov8-untuk-Penghindaran-Obstacle
Pendeteksian dengan menggabungkan dua pendekatan Yolo bounding box dan landmark pose, dimana kedua output ini dipetakan dalam grid 10x10 yang menjadi acuan kursi roda dalam menghindar. Perintah dikirim dari NUC ke ESP32 lalu menggerakan motor. Untuk lebih jelas buka Buku-Tugas-Akhir
AgungHari/TempUniversal-ESP-For-Roblox
Universal ESP for Roblox
AgungHari/tmp_elpose
dataset
AgungHari/temp-kirim
AgungHari/el-paper
AgungHari/Paper
Paper Tugas Akhir
AgungHari/Universal-Teleport-for-Roblox
This script is optimized and built for mobile devices. This script is able to teleport the user to the point the user touches on the screen.
AgungHari/nyoba
AgungHari/Proglan-Game-Nazi-Project-Tank
Tugas Mata Kuliah Pemrograman Lanjut (2020) Program permainan yang menggunakan pustaka SFML (Simple and Fast Multimedia Library) untuk grafis dan audio.
AgungHari/Universal-ESP-For-Roblox
This script is optimized and built for mobile devices. This ESP script is capable of distinguishing the distance of targets near the player with color indicators.
AgungHari/Development-of-YOLOV8-based-Autonomous-Wheelchair-for-Obstacle-Avoidance
Detection is performed by combining two approaches: Yolo bounding box and pose landmarks, where both outputs are mapped into a 10x10 grid (made with OpenCV), which serves as a reference for the wheelchair to avoid obstacles. Commands are sent from the NUC to the ESP32, which then moves the motor.
AgungHari/YOLOv8-Based-Human-Tracking-System-for-Autonomous-Wheelchairs
Same as the previous project but for human tracking, requested by Dr. Eko Mulyanto Yuniarno,S.T.,M.T.
AgungHari/Smart-Wheelchair-Control-Based-on-Spatial-Features-of-Hand-Gesture
Collaborating with Rasyeedah binti Mohd Othman, this project involves training a CNN model with a dataset of hand movement pose. Real time predicted pose will then used to control wheelchair movement.
AgungHari/TinyBERT-Enhanced-Chat-System-for-Mobile-Legends
I developed a TinyBERT powered chat moderation system for Mobile Legends. It classifies in-game comments as positive, neutral, or negative, providing real-time feedback to curb toxic behavior with dynamic responses and efficient sentiment analysis, enhancing the gaming experience.
AgungHari/Desktop
AgungHari/Wheelchair-Control-System-Based-on-SIBI-Gesture-with-Smart-Braking-System-using-YOLOv11-and-LSTM
This time the system will use two cameras to implement the control and smart braking features for wheelchairs, the first camera is specifically for detecting obstacles with the YOLOv11 model that has been trained, where if the obstacle is below 1.2 meters it will send a stop command. The second camera is used to control the wheelchair using LSTM.
AgungHari/Wheelchair-Control-System-Using-Invisible-Steering-Gesture-Based-on-LSTM
This project is still under development. It involves controlling the wheelchair with an invisible steering wheel, using hand gestures as if steering. The approach utilizes an LSTM model to send output to the wheelchair, corresponding to the five available classes.
AgungHari/Forecasting-USDCHF-in-Forex-with-LSTM
Forecasting USDCHF in Forex with LSTM is a machine learning-based project aimed at predicting the price of the USD/CHF currency pair in Forex using an LSTM (Long Short-Term Memory) model. This project uses historical exchange rate data of USD/CHF, particularly the closing price (Close), to train a model capable of predicting future price movements.
AgungHari/Development-of-a-Wheelchair-Control-System-Based-on-Face-Gesture-Recognition-with-LSTM
AgungHari/Esp32_tmp
AgungHari/AgungHari
This is my GitHub profile README. I would like to thank those who created open-source workflows,I have copied a lot from you.