Advances in Underwater Surveillance: Technologies, Challenges and Future Directions (AUSTech 2025) Flyer

Organisers: Dr. Badri N Subudhi (IIT Jammu), Prof. Arijit Sur (IIT Guwahati), Dr. Deepak K Rout (IIIT Bhubaneswar), Meghna Kapoor (IIT Jammu)

Abstract: Underwater communication has advanced significantly, enabling data exchange between submerged vehicles, sensors, and surface stations. Challenges such as signal attenuation and scattering affect both optical and acoustic data quality. This workshop will explore recent developments in underwater vision, sensor fusion, AI-based analytics, and communication technologies. Topics include deep learning for image enhancement, generative models for data augmentation, autonomous underwater vehicles, and acoustic communication protocols. The workshop aims to connect researchers and industry experts to drive innovation in underwater surveillance.

3rd workshop on High-throughput Vision based Phenotyping (HTVP’25)

Organisers: Prof. Brejesh Lall (IIT Delhi), Dr. Prerana Mukherjee (JNU), Prof. Deepak Mishra (IIST Thiruvananthapuram), Dr. Vinay Kaushik (IIIT Sonepat), Dr. Manoj Sharma (Bennett University), Dr. Jit Mukherjee (BIT Mesra Ranchi), Dr. Swati Bhugra (IIT Delhi)

Abstract: The application of methodologies to measure specific organism’s (e.g. plant, insect etc.) traits (morphology, growth etc.) related to its structure and function is termed as phenotyping. With the emergence of low-cost and high-resolution multi-modal cameras, acquisition of 2D and 3D data permits high-throughput micro and macro analysis. This is a rapidly growing field at the interface of biology and computer vision (CV) termed- High-throughput Vision based Phenotyping. Unlike class objects e.g. car, table, chair etc. present in common datasets such as ImageNet; MSCOCO; PASCAL VOC and the SUN dataset, organisms are self changing systems with traits exhibiting variability. This poses novel challenges such as, tracking deformable objects e.g. microbes in microscopy imagery, multi-label segmentation of self-similar objects e.g. leave segmentation in plants, fish segmentation, 3D reconstruction in the presence of overlapping surfaces e.g. plant 3D structure reconstruction etc. In addition, the images acquired in natural conditions such as agricultural fields, greenhouses, forests, marine ecosystems introduce further complexity. Topics of interest include, but are not limited to: Farmland pattern classification, detection, and segmentation from agricultural/phenotyping imagery; Resources and dataset benchmarks for agricultural imagery based pattern analysis; Data fusion of multi/hyper-spectral image data and multi-modal data sources; Self, semi, and weakly supervised methods for agricultural/phenotyping imagery; Vision Language Modelling VLMs for agricultural/phenotyping imagery; Transfer learning and domain adaptation; Generative AI for plant/animal/microorganisms phenotyping; 3D modeling and segmentation, UAV based field phenotyping; Efficient data sampling methods and learning with limited training data or in presence of noisy, sparse, and imbalanced annotations; Computer vision applications which promote the study or adoption of sustainable agriculture .

AI-Driven Biometrics for Forensic Intelligence: Trends, Challenges, and Applications Flyer

Organisers: Dr. Ritesh Vyas (Pandit Deendayal Energy University Gandhinagar), Dr. Santosh Satapathy (Pandit Deendayal Energy University Gandhinagar), Dr. Siddharth Dabhade (National Forensic Science University Gandhinagar)

Abstract: This workshop aims to bring together researchers, practitioners, and policymakers to explore emerging trends in AI-based biometric systems tailored for forensic applications. With an increasing demand for reliable identification in law enforcement and national security, the integration of deep learning, multimodal sensing, and explainable AI has become critical for modern forensic workflows. The workshop will focus on real-world challenges such as degraded input data, spoofing and adversarial attacks, privacy concerns, and the need for interpretability in high-stakes decision-making environments. Discussions will include both theoretical advances and practical deployments of biometric systems in forensic scenarios. This focused workshop will serve as a platform to foster interdisciplinary discussions and collaborations, promote the development of explainable, ethical, and robust biometric systems, and highlight the critical role of AI in forensic intelligence.

All the papers accepted in workshop will be published by Scopus Indexed – Springer in Communications in Computer and Information Science series (CCIS).

All papers must be submitted using the CMT link