Covers various state-of-the-art techniques, methodologies, and applications in the field of 3D computer vision

Comparing and Analyzing 3D Object Detection Methods: Transformer-Based vs. Convolutional-Based Approaches

We recently received reviewer comments and are in the process of revising the paper for publication.

Transformer Neural Networks, Convolutional Neural Networks (CNN)

MMlab engines, MMDet3D, MMCV

Ground Segmentation for point cloud data

Kitti Dataset

Random Forest Algorithm using python for real-time transaction classification tasks

our paper has been published in 7th International Conference on Industrial and Systems Engineering

Various deep learning frameworks (e.g., TensorFlow, PyTorch)

implement and test YOLOv3

Engineered a custom bootloader in C for NXP ARM microcontrollers, enabling remote updates through network connectivity

Implemented a secure and efficient update mechanism using UDP packets for seamless transmission of new code to devices

Integrated C# components for sending update signals and transmitting code over the network

Accelerating robot processes with navigation and obstacle crash avoidance by ARMFPGA+Arduino board

Orchestrated the integration of Arduino and FPGA to create a cohesive control system for the robot

Offloaded computationally heavy processes to the FPGA, optimizing the robot's overall performance

Microcontroller: Arduino, C

FPGA: VHDL