LostNet: A smart way for lost and find
Meihua Zhou, Ivan Fung, Li Yang, Nan Wan, Keke Di, Tingting Wang

TL;DR
LostNet is an image matching system that efficiently identifies lost items by comparing owner-provided images with new photos, achieving high accuracy and practical usability on standard laptops.
Contribution
The paper introduces LostNet, a novel photo matching network combining MobileNetv2 with CBAM Attention for effective lost item identification.
Findings
Achieved 96.8% testing accuracy.
Operates efficiently on a regular laptop.
Uses only 3.5 million training parameters.
Abstract
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 areas. While services like Find My iPhone can easily identify lost electronic devices, more valuable objects cannot be tracked in an intelligent manner, making it impossible for administrators to reclaim a large number of lost and found items in a timely manner. 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 will primarily design a photo matching network by combining the fine-tuning method of MobileNetv2 with CBAM Attention and using the Internet framework to develop an online lost and found image identification system. Our…
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Taxonomy
TopicsAdvanced Neural Network Applications · Advanced Image and Video Retrieval Techniques · Video Surveillance and Tracking Methods
MethodsDepthwise Convolution · Dense Connections · Max Pooling · *Communicated@Fast*How Do I Communicate to Expedia? · Pointwise Convolution · Depthwise Separable Convolution · Sigmoid Activation · Batch Normalization · How do i ask a question at Expedia?*AskExpertService · Communication--Guide||How Do I Communicate to Expedia?
