Dissertation/ Thesis
LostNet: A smart way for lost and find
| العنوان: | LostNet: A smart way for lost and find |
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| المؤلفون: | meihua zhou |
| سنة النشر: | 2023 |
| مصطلحات موضوعية: | Artificial intelligence not elsewhere classified, 智慧城市 |
| الوصف: | Due to the enormous population growth of cities in recent years, objects are frequently lost and unclaimed on public transportation, in restaurants, or any other public area. While services like Find My iPhone can easily identify lost electronic devices, more valuable objects cannot be tracked intelligently, making it impossible for administrators to reclaim a large number of lost and found items on time. We present a method that significantly reduces the complexity of searching by comparing previous images of lost and recovered things provided by the owner with photos taken when registered lost and found items are received. In this research, we primarily design a photo matching network by combining the transfer learning method of MobileNetV2 with CBAM（Convolutional Block Attention Module） and using the Internet framework to develop an online lost and found image identification system. Our implementation gets a testing accuracy of 96.8% using only 665.12M GLFOPs and 3.5M training parameters. It can recognize practice images and can be run on a regular laptop. |
| نوع الوثيقة: | thesis |
| اللغة: | unknown |
| Relation: | https://figshare.com/articles/thesis/lostnet/24826740 |
| DOI: | 10.6084/m9.figshare.24826740.v2 |
| الاتاحة: | https://doi.org/10.6084/m9.figshare.24826740.v2 https://figshare.com/articles/thesis/lostnet/24826740 |
| Rights: | CC BY 4.0 |
| رقم الانضمام: | edsbas.AE51D8A4 |
| قاعدة البيانات: | BASE |
| DOI: | 10.6084/m9.figshare.24826740.v2 |
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