13th International Conference on Signal and Image Processing (SIGL 2026)

Name: 13th International Conference on Signal and Image Processing (SIGL 2026)
Start: 2026-05-16T10:00:00+02:00
End: 2026-05-17T18:00:00+02:00
Location: Zürich

Schedule

Sat, 16 May, 2026 at 10:00 am to Sun, 17 May, 2026 at 06:00 pm

UTC+02:00

Location

Zürich | Zurich, ZH

13th International Conference on Signal and Image Processing (SIGL 2026)

May 16 ~ 17, 2026, Zurich, Switzerland

https://cosit2026.org/sigl/index

Scope & Topics

13th International Conference on Signal and Image Processing (SIGL 2026) serves as a premier forum for researchers, practitioners, and industry experts to present and discuss the latest advances in signal, image, video, audio, and multimodal processing. As the field continues to evolve rapidly driven by breakthroughs in machine learning, computational imaging, large scale sensing, and intelligent systems SIGL 2026 aims to highlight innovative methodologies, emerging applications, and foundational theories that are shaping the future of signal and image processing. SIGL 2026 welcomes original contributions that address both fundamental challenges and real world problems across a broad spectrum of domains, including computer vision, speech and audio processing, biomedical engineering, remote sensing, wireless communication, robotics, and immersive technologies. The conference encourages interdisciplinary work that bridges traditional signal processing with modern AI driven approaches, as well as research that advances robustness, efficiency, interpretability, and scalability in complex environments.

Topics of interest include, but are not limited to, the following:

Signal, image, video, audio, and multimodal processing algorithms
Deep learning methods for signal, image, and video analysis
Foundation models for visual, audio, and multimodal signals
Self supervised, weakly supervised, and unsupervised learning for signal and image data
Generative models for images, video, audio, and multimodal signals (GANs, diffusion, autoregressive models)
Efficient and lightweight models for on device signal and image processing
Federated, distributed, and continual learning applied to signal and image data
Robust, interpretable, and trustworthy AI for signal, image, and audio processing
Image understanding, recognition, detection, and segmentation
3D vision, depth estimation, and scene reconstruction from visual signals
Vision–language models and multimodal reasoning involving image, video, or audio inputs
Medical and biomedical image processing and analysis
Remote sensing and satellite image processing
Hyperspectral, multispectral, and low light imaging techniques
Image enhancement, restoration, denoising, and super resolution
Computational imaging and computational photography
Video analysis, action recognition, and event understanding
Video generation, editing, compression, and quality assessment
Speech and audio signal processing (recognition, synthesis, enhancement)
Speaker identification, diarization, and verification
Acoustic scene analysis, spatial audio, and beamforming
Music signal processing and audio generation
Signal processing for AR/VR/XR and immersive environments
Communication signal processing for wireless, mobile, and sensor systems (focused on signal algorithms, not networking protocols)
Radar, sonar, lidar, and other active sensing signal processing
Localization, tracking, and multi sensor fusion using signal level methods
Biomedical and physiological signal processing (EEG, ECG, EMG, BCI)
Wearable and mobile health signal analytics
Environmental, geophysical, and scientific signal processing
Security and privacy techniques for signal, image, and audio data
Adversarial attacks and defenses targeting signal, image, video, or audio models
Media forensics, deepfake detection, and content authenticity analysis
Watermarking, steganography, and signal based content protection
Sparse representations, compressed sensing, and optimization for signal and image processing
Graph signal processing and geometric deep learning
Statistical and probabilistic methods for signal and image analysis
Hardware acceleration and real time systems for signal, image, and audio processing
Neuromorphic computing for signal and image applications
Edge, cloud, and distributed processing specifically for signal, image, video, or audio workloads
Applications of signal and image processing in robotics, autonomous systems, intelligent transportation, and smart environments
Industrial inspection and manufacturing quality control using signal or image analysis
Cultural heritage preservation using signal and image processing techniques

Paper Submission

Authors are invited to submit papers through the conference Submission System by April 11, 2026 .

Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this conference. The proceedings of the conference will be published by Computer Science Conference Proceedings in Computer Science & Information Technology (CS & IT) series (Confirmed).

Selected papers from SIGL 2026, after further revisions, will be published in the special issues of the following journals