Motivated by surveillance applications with wireless cameras or drones, we consider the problem of image retrieval over a wireless channel. Conventional systems apply lossy compression on query images to reduce the data that must be transmitted over a bandwidth and power limited wireless link. We first note that reconstructing the original image is not needed for retrieval tasks; hence, we introduce a deep neutral network (DNN) based compression scheme targeting the retrieval task. Then, we completely remove the compression step, and propose another DNN-based communication scheme that directly maps the feature vectors to channel inputs. This joint source-channel coding (JSCC) approach not only improves the end-to-end accuracy, but also simplifies and speeds up the encoding operation which is highly beneficial for power and latency constrained IoT applications.
Deep Joint Source-Channel Coding for Wireless Image Retrieval / Jankowski, M.; Gunduz, D.; Mikolajczyk, K.. - 2020-:(2020), pp. 5070-5074. (Intervento presentato al convegno 2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020 tenutosi a esp nel 2020) [10.1109/ICASSP40776.2020.9054078].
Deep Joint Source-Channel Coding for Wireless Image Retrieval
Gunduz D.;
2020
Abstract
Motivated by surveillance applications with wireless cameras or drones, we consider the problem of image retrieval over a wireless channel. Conventional systems apply lossy compression on query images to reduce the data that must be transmitted over a bandwidth and power limited wireless link. We first note that reconstructing the original image is not needed for retrieval tasks; hence, we introduce a deep neutral network (DNN) based compression scheme targeting the retrieval task. Then, we completely remove the compression step, and propose another DNN-based communication scheme that directly maps the feature vectors to channel inputs. This joint source-channel coding (JSCC) approach not only improves the end-to-end accuracy, but also simplifies and speeds up the encoding operation which is highly beneficial for power and latency constrained IoT applications.Pubblicazioni consigliate
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