Papers with Code 아카이브

WiFi CSI-based Image Reconstruction

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

하위 태스크
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평가표
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보존된 평가 기록
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This project explores an innovative approach to imaging by leveraging WiFi Channel State Information (CSI) to reconstruct visual images of an environment. Unlike conventional cameras, which rely on optical light, this method uses the properties of WiFi signals—such as amplitude, phase, and multipath characteristics—to infer and recreate the spatial structure of objects and scenes.

데이터셋

출처에 같은 태스크 이름으로 연결된 데이터셋입니다. 동명 태스크가 포함될 수 있으므로, 비교할 때는 평가 결과의 조건도 확인하세요.

TDMA CSI 16

This dataset is a collection of paired wireless signal data and corresponding image ground truth specifically designed for underground object sensing and image reconstruction. It utilizes Channel State Information (CSI) and Received Signal Strength Indicator (RSSI) collected from a low-cost WiFi Wireless Sensor Network (WSN) deployed around a soil volume containing underground potato tubers. The data was acquired in a controlled laboratory environment using an automated system that ensures precise alignment between the wireless measurements and the physical location/shape of the target. The primary motivation for creating this dataset was to provide a resource for developing and evaluating non-destructive, low-cost methods for sensing underground biomass, overcoming the limitations of traditional techniques and simpler wireless metrics like RSSI. The dataset contains: - CSI amplitude (52 data subcarriers) and RSSI values from a 16-node ESP32-C3 WiFi mesh network across 14 channels, capturing frequency-dependent and overall signal attenuation for numerous links. For each wireless sample, a 360x360 pixel binary image mask representing the precise 2D cross-section of the underground potato tuber at that orientation, generated via automated camera and image segmentation. The dataset includes data collected from 8 different potato tubers, with measurements taken at 32 distinct rotation angles for each.

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.