Synapse
⌘+K
Synapse
PulseExploreClubsResearchersJournals
Instagram
HomeClubsExplore
September 10, 2025MALAYSIAN JOURNAL OF COMPUTINGOpen Access

Sports Item Detection Using Mobilenetv2 With Single Shot Detector

View Full Paper
Ask AI
Bookmark
Share

Authors

AYAiman Haziq Ab YazikSKSiti Nur Kamaliah KamarudinYMYuzi Mahmud

Discussion

Loading...

Member takes

Overview

Observational analysis achieved 93% accuracy in detecting sports items, indicating improved tracking efficiency.

Key Points

  • The system achieved a mean average precision of 0.93, demonstrating effective object detection.
  • With a confidence level of 97%, the model minimizes human error within the sports item lending system.
  • Using MobilenetV2 and SSD, experiments were conducted on 960 self-collected images to establish model accuracy.
  • Future work may further enhance performance by increasing training data volume and exploring other detection techniques.

Cite This Study

Yazik et al. (2023) studied this question.

synapsesocial.com/papers/68c1e24854b1d3bfb60ff22bhttps://doi.org/10.24191/mjoc.v8i2.22641
View Full Paper
Ask AI
Bookmark
Share

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Detection of Multiple Objects from Video Frames Through Mobilenet-SSDv22024
  2. 2Object Detection Using CNN2024 · 2 citations
  3. 3Cloud Based Attendance Monitoring System Using MobileNet SSD2024
  4. 4Automated Object Detection and Count Estimation Based on Machine Learning Models2025
  5. 5Real-Time Object Detection Using MobileNet-SSD and OpenCV2025