Bridge : Jurnal Publikasi Sistem Informasi dan Telekomunikasi
metadata only
Penerapan Deep Convolutional Autoencoder dengan Skip Connection Untuk Menghilangkan Derau pada Citra Digital
Digital images often experience noise disturbances that can reduce visual quality and interfere with the image analysis process. One common type of noise is salt and pepper noise, especially in grayscale images, which is characterized by the random appearance of black and white dots. This study appl
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- ExtendingText-Based Duplicate BugDe tection with Image Processing: APipeline Based Approach#427197
- Generation of Synthetic Fingerphotos with GANs#612460
- Generation of Synthetic Fingerphotos with GANs#610983
- A generalization of the maximum likelihood expectation maximization (MLEM) method: Masked-MLEM#491857
- Multimodal sensor data fusion and event recognition in IoT#680865
Record · ID 1003283
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive