Wireless Image Retrieval At The Edge
2020 Β· Mikolaj Jankowski, Deniz Gunduz, Krystian Mikolajczyk
Abstract
We study the image retrieval problem at the wireless edge, where an edge device captures an image, which is then used to retrieve similar images from an edge server. These can be images of the same person or a vehicle taken from other cameras at different times and locations. Our goal is to maximize the accuracy of the retrieval task under power and bandwidth constraints over the wireless link. Due to the stringent delay constraint of the underlying application, sending the whole image at a sufficient quality is not possible. We propose two alternative schemes based on digital and analog communications, respectively. In the digital approach, we first propose a deep neural network (DNN) aided retrieval-oriented image compression scheme, whose output bit sequence is transmitted over the channel using conventional channel codes. In the analog joint source and channel coding (JSCC) approach, the feature vectors are directly mapped into channel symbols. We evaluate both schemes on image bas
Authors
(none)
Tags
Stats
Related papers
- Compression Of Deep Neural Networks For Image Instance Retrieval (2017)8.82
- Adapnet: Adaptive Noise-based Network For Low-quality Image Retrieval (2024)0.00
- Compressible And Searchable: Ai-native Multi-modal Retrieval System With Learned Image Compression (2024)0.00
- Pruning Convolutional Neural Networks For Image Instance Retrieval (2017)0.00
- REJEPA: A Novel Joint-embedding Predictive Architecture For Efficient Remote Sensing Image Retrieval (2025)2.26
- Tasks Integrated Networks: Joint Detection And Retrieval For Image Search (2020)11.08
- AMES: Asymmetric And Memory-efficient Similarity Estimation For Instance-level Retrieval (2024)9.70
- Matrix Factorization-based Clustering Of Image Features For Bandwidth-constrained Information Retrieval (2016)0.00