University of Udine, Italy Months Research Fellow Position – Object Tracking in First-Person and Third-Person Videos

Dear colleagues,
We are seeking one highly motivated researcher for a fully funded research fellowship position (Italian Assegno di Ricerca – Post-Doc Equivalent) on topics related to Object Tracking in Egocentric Vision.
 
The candidate will join the Machine Learning and Perception Lab (MLP Lab), at the University of Udine, Italy under the supervision of Prof. Christian Micheloni and Dr. Matteo Dunnhofer.
 
The position is in topics related to a recently funded PRIN project: EXTRA-EYE, with specific focus on developing object tracking algorithms for first-person egocentric and third-person videos. More details are in the following:
 
Position – Design and Development of Object Tracking Algorithms for localisation across First-Person and Third-Person Views
Position: Research Fellow (post-doc equivalent)
Location: University of Udine, Udine, Italy
Application Deadline: May 28, 2024 at 2:00 pm (Italian time)
Duration: 14 Months
Research Topics: Tracking objects in first-person view is notoriously challenging, and EXTRA-EYE aims to pioneer a solution. Our approach involves integrating state-of-the-art deep learning architectures for third-person-view (TPV) tracking with first-person-view (FPV) specific cues, such as the position of the user's hands. The project will establish correspondences between scenes captured in the FPV and TPV streams, creating a holistic, robust, and efficient tracking approach capable of real-time tracking across multiple dynamic and static cameras. 
Link to the project’s website: https://sites.google.com/view/extraeye/home
  
Admission Criteria
To participate in the call, a master’s degree in computer science or computer science engineering is required. A PhD is not required, but strongly recommended. Previous background in Computer Vision and Deep Learning is also strongly recommended.
 
About the Laboratory
The MLP research group mainly focuses on the development of research in Computer Vision and Deep Learning for Object Tracking and Re-Identification, and Distributed Camera Systems. The group has 6+ members.
 
The MLP group has a track record of previous publications in prestigious venues (CVPR, ICCV, ECCV, TPAMI, IJCV, …) and several research projects on both fundamental and application-oriented research, in collaboration with several industrial and academic partners. 
 
The group aims to provide its members a friendly environment with strong supervision, in which individuals can grow and let their full potential flourish. We regularly organize group meetings and gatherings outside the lab to keep the team motivated and encourage a good work culture.
  
 
Please feel free to share this opportunity with anyone who might be interested. We appreciate your assistance in reaching out to potential candidates.
 
Christian Micheloni, University of Udine
Matteo Dunnhofer, University of Udine

CFP – Big Visual Data Analytics (BVDA) Workshop at ICIP, 27-30 October 2024, Abu Dhabi, UAE

CALL FOR PAPERS

 

Big Visual Data Analytics (BVDA) Workshop at ICIP 2024

 

IEEE International Conference on Image Processing, 27-30 October 2024, Abu Dhabi, UAE

 

We invite researchers and practitioners working on various aspects of big visual data analytics to submit their work to the Big Visual Data Analytics (BVDA) Workshop, organized in conjunction with the IEEE International Conference on Image Processing (ICIP) 2024. The ever-increasing visual data availability leads to repositories or streams characterized by big data volumes, velocity (acquisition and processing speed), variety (e.g., RGB or RGB-D or hyperspectral images) and complexity (e.g., video data and point clouds). Their processing necessitates novel and advanced visual analysis methods, in order to unlock their potential across diverse domains.

The BVDA Workshop aims to explore this rapidly evolving field encompassing cutting-edge methods, emerging applications, and significant challenges in extracting meaning and value from large-scale visual datasets. From high-throughput biomedical imaging and autonomous driving sensors to satellite imagery and social media platforms, visual data has permeated nearly every aspect of our lives. Analyzing this data effectively requires efficient tools that go beyond traditional methods, leveraging advancements in machine learning, computer vision and data science. Exciting new developments in these fields are already paving the way for fully and semi-automated visual data analysis workflows at an unprecedented scale. This workshop will provide a platform for researchers and practitioners to discuss recent breakthroughs and challenges in big visual data analytics, explore novel applications across diverse domains (e.g., environment monitoring, natural disaster management,  robotics, urban planning, healthcare, etc.), as well as for fostering interdisciplinary collaborations between computer vision, data science, machine learning, and domain experts. Its ultimate goal is to help identify promising research directions and pave the way for future innovations.

The BVDA Workshop delves deeper into specific aspects of big visual data, complementing the broader ICIP themes. Thus it can generate new research interest and collaborations within the main conference community, while attracting researchers and practitioners specifically interested in big visual data analytics. Its interdisciplinary nature, its focus on cutting-edge areas (e.g., large Vision-Language Models, distributed deep neural architectures, fast generative models, etc.) and its synergies with neighboring fields (e.g., privacy-preserving analytics, real-time visual analytics, ethical considerations, etc.) broaden the discussion.

 

Topics of interest include (non-exhaustively) the following ones:

·         Scalable algorithms and architectures for big visual data processing and analysis.

·         High-performance computing, distributed and parallel processing, efficient data storage and retrieval for big visual data analysis.

·         Deep learning architectures for large-scale visual content understanding, search & retrieval: Convolutional Neural Networks (CNNs), Transformers, Self-Supervised Learning, etc.

·         Big visual data summarization.

·         Decentralized/distributed DNN architectures for big visual data analysis.

·         Cloud/edge computing architectures for big visual data analysis.

·         Multimodal big visual data analysis.

·         Large Vision-Language Models/Foundation Models.

·         Fast generative models for visual data: Synthesizing realistic images/videos, data augmentation, in-painting and manipulation.

·         Fast Interpretability and eXplainability (XAI) of visual analytics models: Understanding and communicating model decisions, trust and bias in AI systems.

·         Privacy-preserving analytics in the context of big visual data: Secure data processing, differential privacy, federated learning.

·         Visual analytics for real-time applications: Efficient analysis of visual streaming data, edge/fog computing.

·         Visual analytics for specialized domains: Remote sensing, natural disaster management, medical imaging, social media analysis, etc.

·         Ethical considerations in big visual data analytics: Data ownership, fairness, accountability, societal impact.

 

The regular ICIP paper template/style must be used for submission. All accepted contributions will be published in IEEE Xplore. The paper submission deadline is May 9, 2024.

 

For further details and submission instructions visit: https://icarus.csd.auth.gr/cfp-bvda-icip24-workshop/

 

 

Organizers

 

Prof. Ioannis Pitas: Chair of the International AI Doctoral Academy (AIDA), Director of the Artificial Intelligence and Information analysis (AIIA) Lab,

Aristotle University of Thessaloniki, Greece.

 

Prof. Massimo Villari: University of Messina, Italy.

 

Dr. Ioannis Mademlis: Postdoctoral researcher at the Harokopio University of Athens.

 

Data challenge launched by EU-MSCA-GREENEDGE

Dear colleagues,

it is my pleasure to announce the opening of the GREENEDGE contest.
It features three possible research lines:

1) Cybersecurity: “Cyber Threats Detection through Network Energy Consumption Analysis” 
2) Image Classification: “Energy Aware Image Classification”  
3) Internet of Things: “Energy Efficient IoT Networks”.

The lines deal with topics related to the GREENEDGE core mission, i.e., to devise energy-efficient tools for computing in networks.

BS, MS level and PhD students are invited to participate in the challenge.

The submitted projects will undergo an evaluation by a team of scientists from the GREENEDGE consortium.
The winners will be invited to participate in the final GREENEDGE workshop where they will present their work and will receive a prize.
The final workshop will be co-located with SofCom2024 international conference and will take place end of September 2024 in Croatia (detailed instructions will follow in a second stage). 
 
Subscription deadline: May 15, 2024. ⏰
 
More details are available in the GREENEDGE website: https://greenedge-itn.eu/contest/

For any question, please do not hesitate to contact me.

Best regards,

IEEE BHI 2024 – “Deep Medicine and AI for Health”

IEEE BHI 2024: Deep Medicine and AI for Health

 

https://bhi.embs.org/2024/

 

The IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI), sponsored by the IEEE Engineering in Medicine and Biology Society (IEEE EMBS), is EMBS’s primary technical conference on informatics and computing in healthcare and life sciences. BHI 2024 will take place in Houston, Texas,  from November 10-13, 2024. It will provide a unique forum to showcase basic and translational research on big data analytics and machine learning that address challenges in the acquisition, transmission, processing, security, visualization, and interpretation of vast volumes of multi-modal biomedical data, as well as related social, behavioral, environmental, and geographical data. It will also demonstrate the deployment of BHI informatics solutions that integrate key technologies including artificial intelligence, machine learning, mHealth, e-Health, human-computer interface, telemedicine, bioinformatics, sensors, imaging, and public health monitoring, to achieve patient-centric and outcome-driven effective health care.

 

Important Information

·        Inception of 8-page papers in IEEE Journal of Biomedical and Health Informatics format: 8-page J-BHI format papers will be evaluated by JBHI (IF: 7.7) EiC and accepted papers will be published in JBHI Special Issue.

·        Opportunities for regular conference papers and 1-page abstracts

·        Open Access: BHI 2024 proudly features Open-Access publishing for accepted regular papers.

·        Accepted regular conference papers for publishing in IEEE Xplore

·        Open Double-Blind Review for high quality: BHI 2024 will use openreview for establishing open review processes.

·        Best paper awards for recognizing innovative and excellence research

·        Continuing Medicine Education (CME) credits for clinicians

·        Travel Awards: for undergraduate and graduate students from US Institutions are available through a National Science Foundation (NSF) grant.

·        Data competition and awards for students

·        Student resume database and career fair

 The topical areas of interest include but are not limited to the following:

·        Intelligent reality and metaverse

·        AI for combating long COVID

·        AI-based clinical decision support systems

·        Large Language Models for biomedical and clinical research

·        Biomedical Generative AI

·        AI for biomarker discovery and drug design

·        Digital radiology and pathology

·        Single-cell and spatial omics

·        Cancer genomics and immunotherapy

·        Digital health

·        Biomedical digital twins

 

Important Dates

Paper Submission (JBHI & Reg. Conf. papers)

June 13, 2024

1st Round of Paper Review Notifications

August 1, 2024

2nd Round Paper Review Submission

August 29, 2024

2nd Round Review sent to JBHI EiC for Selection

September 12, 2024

Final Paper Acceptance Notification

September 26, 2024

Final Camera Ready Paper

October 10, 2024

1-page Abstract Submission

September 13, 2024

1-page Abstract Acceptance Notification

September 27, 2024

 

 

ICIP2024 – 1st LVLM Workshop – Call for Papers

 

l  Call for Papers:

ICIP 2024 1st Workshop on Integrating Image Processing with Large-Scale Language/Vision Models for Advanced Visual Understanding

ü  The 31st International Conference on Image Processing (ICIP 2024)

ü  27-30 October 2024, Abu Dhabi, United Arab Emirates

 

l  Abstract:

This workshop aims to bridge the gap between conventional image processing techniques and the latest advancements in large-scale models (LLM and LVLM). In recent years, the integration of large-scale models into image processing tasks has shown significant promise in improving visual object understanding and image classification. This workshop will provide a platform for researchers and practitioners to explore the synergies between conventional image processing methods and cutting-edge large language model and large vision language models, fostering innovation and collaboration in the field.

This workshop is designed for researchers, academics, and industry professionals working in the fields of image processing, computer vision, multimedia processing and natural language processing. Participants should have a basic understanding of image processing concepts and an interest in exploring innovative approaches for visual understanding.

 

l  Workshop Topics (include, but not limited to):

ü  Cross-Modal Fusion

ü  Object Detection and Recognition with Large-scale models

ü  Image Classification and Annotation

ü  Multimodal Sensor Fusion

ü  Semantic Segmentation with Large-scale Models

ü  Cross-Domain Visual Understanding

ü  Visual Question Answering (VQA) Systems

ü  Text-Image Linking and Alignment

 

l  Important Dates:

ü  Paper Submission Deadline:         May 9, 2024

ü  Paper Acceptance Notification:      June 6, 2024

ü  Final Submission Deadline:           June 19, 2024

ü  Author Registration Deadline:       July 11, 2024

 

l  Paper Submission:

Submission instructions, templates and the “no show” policy are detailed in https://2024.ieeeicip.org/.

All accepted papers will be published in IEEE Xplore.

Conference papers can be submitted electronically through the workshop submission website: https://cmsworkshops.com/ICIP2024/papers/submission.asp?Type=WS&ID=8

For further information on our workshop and the paper submission process, please visit the workshop website: https://carai.kaist.ac.kr/lvlm

 

l  Workshop Organizers:

ü  Yong Man Ro, Korea Advanced Institute of Science & Technology (KAIST) (ymro@kaist.ac.kr)

ü  Hak Gu Kim, Chung-Ang University (hakgukim@cau.ac.kr)

ü  Nikolaos (Nikos) Boulgouris, Brunel University London (nikolaos.boulgouris@brunel.ac.uk)

 

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