Aims & Scope
FEATURE: Nusantara Journal of Computer Vision publishes high-quality, original research that advances the theory and practice of how machines perceive and understand visual data, with particular encouragement for work addressing challenges and datasets from Indonesia and Southeast Asia.
Aims
- Disseminate rigorous, reproducible research in computer vision and image analysis.
- Bridge fundamental advances and real-world deployment in health, agriculture, environment, transportation, industry and culture.
- Foster an open, international community of researchers from the Global South.
Scope
- Feature Extraction & Representation LearningDescriptors, self-supervised, contrastive and foundation-model representations.
- Recognition, Detection & TrackingImage classification, object detection, re-identification, multi-object tracking.
- Segmentation & Scene UnderstandingSemantic, instance, panoptic segmentation and scene graphs.
- 3D Vision, SLAM & RoboticsDepth, reconstruction, neural rendering, visual odometry, robot perception.
- Video AnalysisAction recognition, temporal localisation, video anomaly detection.
- Medical & Biomedical ImagingCAD, radiology, histopathology, ophthalmology, microscopy.
- Remote Sensing & Earth ObservationSatellite/UAV imagery, land cover, agriculture, disaster monitoring.
- Generative & Multimodal VisionDiffusion models, vision-language models, restoration and synthesis.
- Efficient & Edge VisionCompression, quantisation, embedded and IoT vision systems.
- Trustworthy VisionRobustness, explainability, fairness, privacy and security of vision models.
- Vision for Culture & SocietyHeritage digitisation, Aksara Nusantara OCR, sign language, assistive technology.
- Datasets & BenchmarksNew datasets, annotation protocols and benchmark studies.
Article Types
- Original Research Articles — 6,000–9,000 words.
- Review / Survey Articles — systematic or critical reviews, up to 12,000 words.
- Dataset & Benchmark Papers — describing new public datasets with baselines.
- Short Communications — novel preliminary results, up to 4,000 words.