多目标跟踪方法研究（深度学习算法与实验评估）
在交通场景的多目标追踪研究中，基于深度学习完成算法设计、代码实现与实验评估，以支持模型在复杂干扰条件下的性能提升。该经历以计算机视觉任务为核心，侧重对检测与跟踪效果的验证与度量，而非传统人工标注流程。主要产出包括论文撰写与投递，并完成实验对比以支撑研究结论。• 对多目标追踪场景中的漏检与ID切换问题进行分析与改进 • 进行实验设置、结果分析与性能优化 • 支撑学术论文数据与结论整理 • 参与代码实现与评估验证闭环
2023 - Present
For employersInvite to Job
Hire this AI Trainer
Sign in or create an account to invite AI Trainers to your job.
Key Skills
Software
Other
Top Subject Matter
Computer Vision / Multi-object Tracking
Robotics / Embedded Systems / Sensor Data Acquisition
Top Data Types
Video
Image
Computer Code ProgrammingTop Task Types
Bounding Box
Classification
Object Detection
Computer Programming/Coding
SegmentationFreelancer Overview
多目标跟踪方法研究（深度学习算法与实验评估）. Brings 3+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include PyTorch and Other. Education includes Master of Science, Changsha University of Science and Technology (2023) and Bachelor of Science, Hunan City University (2021). AI-training focus includes data types such as Computer Code and Programming and labeling workflows including Evaluation, Rating, and Data Collection.
Labeling Experience
Education
H
Hunan City University
Bachelor of Science, Internet of Things Engineering
Bachelor of Science
2017 - 2021
C
Changsha University of Science and Technology
Master of Science, Computer Technology
Master of Science
2023
Work History
R
RoboMaster
Robotics Embedded System Engineer (Competition)
Changsha
2021 - 2021