Vehicle Re-identification via Spatio-temporal Multi-instance Learning

Xiang, Yang; Li, Chunjie; Zeng, Quan; Xiu, Pan; Yang, Jing; Xu, Hongke

doi:10.1007/978-981-19-6135-9_36

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Video Classification1

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2023

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“…MIL can be utilized for tasks like activity recognition or identifying anomalies in video surveillance [61][62][63]. Bags represent video clips or sequences, while instances are specific time frames inside such videos.…”

Section: Video Classificationmentioning

confidence: 99%

A Comprehensive Review on Multiple Instance Learning

Fatima,

Ali,

Kim

2023

Electronics

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Multiple-instance learning has become popular over recent years due to its use in some special scenarios. It is basically a type of weakly supervised learning where the learning dataset contains bags of instances instead of a single feature vector. Each bag is associated with a single label. This type of learning is flexible and a natural fit for multiple real-world problems. MIL has been employed to deal with a number of challenges, including object detection and identification tasks, content-based image retrieval, and computer-aided diagnosis. Medical image analysis and drug activity prediction have been the main uses of MIL in biomedical research. Many Algorithms based on MIL have been put forth over the years. In this paper, we will discuss MIL, the background of MIL and its application in multiple domains, some MIL-based methods, challenges, and lastly, the conclusions and prospects.

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Section: Video Classificationmentioning

confidence: 99%