Invitation to submit a paper to the Special Issue “Data, Signal and Image Processing and Applications in Sensors II” — Sensors Journal

February 23rd, 2021 Daniela Lopez de Luise

 

I wish to share some exciting news with you: Sensors received the 2019 Impact Factor of 3.275 and 5-year IF of 3.427. It ranks 15/64 (Q1) in “Instruments & Instrumentation”; 22/86 (Q2) in “Chemistry, Analytical”; 77/266 (Q2) in “Engineering, Electrical & Electronic” of JCR; for more details, please see https://www.mdpi.com/journal/sensors/stats.


I invite you to publish a related work to a Special Issue titled “Data, Signal and Image Processing and Applications in Sensors II”.


For further reading, please follow the link to the Special Issue Website at: https://www.mdpi.com/journal/sensors/special_issues/signal_sensors_II


The submission deadline is 31 August 2021. You may send your manuscript now or up until the deadline. We will process it immediately, and it will be published once it is accepted after the peer review.

If you have any question, please do not hesitate to contact me.

I look forward to hearing from you.

Warm regards,

Manuel Cabral Reis

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CFP: INISTA 2021 IEEE International Conference on INnovations in Intelligent SysTems and Applications

February 23rd, 2021 Daniela Lopez de Luise

We are pleased to inform you that the 2021 IEEE International Conference on INnovations in Intelligent SysTems and Applications (INISTA) will be held in Kocaeli, Turkey on August 25-27, 2021. IEEE INISTA 2021 is organized by the Department of Information Systems Engineering, Kocaeli University in cooperation with Yildiz Technical University, Turkey.

We strongly believe that the situation with COVID-19 virus will be normalized and that we will meet at the end of August in 2021. But, If the pandemic and uncertainties regarding travel restrictions continue, there is a possibility that the conference will be held on a hybrid basis.

IEEE INISTA 2021 conference is technically sponsored by IEEE and IEEE SMC Society on TC on Computational Collective Intelligence. Accepted papers will appear in the conference proceedings, available on IEEE Xplore and submitted to be indexed in the Web of Science Core Collection databases.

Extended versions of the best papers accepted and presented at IEEE INISTA 2021 will be considered for publication in a special issue of internationally recognized journals. The names of the journals will be announced later.

The topics of interest cover the entire spectrum of the multi-disciplinary fields of intelligent systems and related applications from theoretical and practical point of view. In particular, but not exclusively the submissions within the following major areas are relevant and welcome:

v  Artificial Intelligence Algorithms

v  Artificial Neural Networks

v  Autonomous systems

v  Bioinformatics

v  Big Data

v  Cloud Computing

v  Data Mining

v  Data Hiding

v  Deep Learning

v  Distributed Intelligence

v  Ensemble Learning

v  Evolutionary Computation

v  Expert Systems

v  Fuzzy Logic

v  Genetic Algorithms

v  Hardware Implementations for Intelligent Systems

v  Human-Computer Interaction

v  Humanoid Robotics

v  Hybrid Intelligence

v  Intelligent Agents

v  Intelligent Applications in Biomedical Engineering

v  Intelligent Approaches in Robotic and Automation

v  Intelligent Approaches in Signal and Image Processing

v  Intelligent Approaches in System Identification/Modeling

v  Intelligent Behavior

v  Intelligent Control Systems

v  Intelligent Defense/Security Systems

v  Intelligent Healthcare

v  Intelligent Education

v  Intelligent Interaction and Visualization

v  Intelligent Life

v  Information Security

v  Internet of Things, Internet of Everything

v  Machine Learning

v  Memetic Computing

v  Natural Language Processing

v  Neurotechnology and Emergent Intelligence in Nervous Systems

v  Robust Perception in Complex Environments

v  Reinforcement Learning

v  Smart Sensors, Materials, and Environments

v  Smart Wearables

v  Social Media Mining

v  Swarm Intelligence

v  Text Mining

v  Virtual, Augmented and Mixed Reality

v  Other topics related to Intelligent Systems

IMPORTANT DATES

v  Special session proposals:          February 28, 2021

v  Special session notification:        March 15, 2021

v  Paper submission:                         April 16, 2021

v  Paper notification:                          June 01, 2021

v  Camera-Ready Submission:        June 14, 2021

v  Early registration:                           June 14, 2021

KEYNOTE SPEAKERS

Bernard Jim Jansen : Science wants numbers about people: The numbers are likely wrong                                                

Patrick Shen-Pei Wang : Intelligent Pattern Recognition and Applications to Imaging and e-Forensic

Melike Erol-Kantarcı : AI-Enabled Wireless Networks: A Bridge from 5G to 6G              


For more details, please visit the website http://inista.org/

If you have any questions, please do not hesitate to contact us.

Email: inista2021@gmail.com

Hope to see you in INISTA 2021!

IEEE INISTA 2021 Organizing Commitee

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IV 2021 : 3D-DLAD-v3 third workshop on 3D Deep Learning for Autonomous Driving at Intelligent Vehicules 2021

February 23rd, 2021 Daniela Lopez de Luise

 

CALL FOR PAPERS 3D-DLAD-v3 2021

 

3D-DLAD-v3 (third 3D Deep Learning for Autonomous Driving) workshop is the 6th workshop organized as part of DLAD workshop series. It is organized as a part of the flagship automotive conference Intelligent Vehicles https://2021.ieee-iv.org/.

 

Deep Learning has become a de-facto tool in Computer Vision and 3D processing with boosted performance and accuracy for diverse tasks such as object classification, detection, optical flow estimation, motion segmentation, mapping, etc. Lidar sensors are playing an important role in the development of Autonomous Vehicles as they overcome some of the many drawbacks of a camera based system, such as degraded performance under changes in illumination and weather conditions. In addition, Lidar sensors capture a wider field of view, and directly obtain 3D information. This is essential to assure the security of the different agents and obstacles in the scene. It is a computationally challenging task to process more than 100k points per scan in realtime within modern perception pipelines. Following the said motivations, finally to address the growing interest in deep representation learning for lidar point-clouds, in both academic as well as industrial research domains for autonomous driving, we invite submissions to the current workshop to disseminate the latest research.

 

We are soliciting contributions in deep learning on 3D data applied to autonomous driving in (but not limited to) the following topics. Please feel free to contact us if there are any questions.

 

TOPICS : 

Deep Learning for Lidar based clustering, road extraction object detection and/or tracking.

Deep Learning for Radar pointclouds

Deep Learning for TOF sensor-based driver monitoring

New lidar based technologies and sensors.

Deep Learning for Lidar localization, VSLAM, meshing, pointcloud inpainting

Deep Learning for Odometry and Map/HDmaps generation with Lidar cues.

Deep fusion of automotive sensors (Lidar, Camera, Radar).

Design of datasets and active learning methods for pointclouds

Synthetic Lidar sensors & Simulation-to-real transfer learning

Cross-modal feature extraction for Sparse output sensors like Lidar.

Generalization techniques for different Lidar sensors, multi-Lidar setup and point densities.

Lidar based maps, HDmaps, prior maps, occupancy grids

Real-time implementation on embedded platforms (Efficient design & hardware accelerators).

Challenges of deployment in a commercial system (Functional safety & High accuracy).

End to end learning of driving with Lidar information (Single model & modular end-to-end)

Deep learning for dense Lidar point cloud generation from sparse Lidars and other modalities

 

 

 

Location : Nagoya, Japan

Submission : 15th March 2021 (firm deadline, no extension)

Acceptance Notification : 25th April 2021

Workshop Date : 11th July 2021

 

Workshop Organizers:

B Ravi Kiran, Navya, France

Senthil Yogamani, Valeo Vision Systems, Ireland

Victor Vaquero, Research Engineer, IVEX.ai

Patrick Perez, Valeo.AI, France

Bharanidhar Duraisamy, Daimler, Germany

Dan Levi, GM, Israel

Abhinav Valada, University of Freiburg, Germany

Lars Kunze, Oxford University, UK

Markus Enzweiler, Daimler, Germany

Ahmad El Sallab, Valeo AI Research, Egypt

Sumanth Chennupati, Wyze Labs, USA

Stefan Milz, Spleenlab.ai , Germany

Hazem Rashed, Valeo AI Research, Egypt

Jean-Emmanuel Deschaud, MINES ParisTech, France

Kuo-Chin Lien, Appen USA

Naveen Shankar Nagaraja, BMW Group, Munich

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TISR Challenge, PBVS-CVPR 2021

February 23rd, 2021 Daniela Lopez de Luise
2nd. Thermal Image Super Resolution Challenge <TISR Challenge, PBVS-CVPR 2021>

https://pbvs-workshop.github.io/challenge.html

 
in conjunction with the 17th IEEE Workshop on Perception Beyond the Visible Spectrum (PBVS-CVPR 2021)

https://pbvs-workshop.github.io/

June 2021
Virtual

=====================================================

Important Dates

  • Registration open & dataset released: January 18, 2021
  • Evaluation images distributed: March 2, 2021
  • Deadline for challenge & result submitted: March 12, 2021
  • Winner announcement: June 19, 2021

=====================================================

Objective & Scope

The thermal image super-resolution (TISR) problem has become an attractive research topic in recent years, mainly due to the appealing results obtained with recent deep learning-based approaches. In order to define a common benchmark for evaluating the different contributions, the first challenge on TISR has been proposed at the PBVS-2020 workshop. Due to the success of that first challenge, and trying to keep improving the obtained results, this year the second challenge on TISR is proposed in the framework of the PBVS-2021 workshop.

The challenge stated for this year consists in obtaining super-resolution images at x2 and x4 scales from the given images.

Just the mid- and high-resolution images from last year's dataset will be considered. Ground truth images for the x4 scale correspond to the provided high-resolution images; in other words, each team should down-sample the given images by x4 and use these down-sampled images (by adding noise) as inputs to develop their solutions. Regarding the x2 super-resolution solution, it should be developed using as an input the given mid-resolution images acquired with the camera Axis Q2901-E and as an output, the corresponding high-resolution images, of the same scene, but acquired with the FLIR FC-632O camera. In other words, the x2 scale proposed solution should be able to tackle both problems, i.e., generating the super-resolution of the images acquired with the camera Axis Q2901-E camera; as well as mapping images from one domain (Axis Q2901-E camera) to another domain (FLIR FC-632O camera).

https://pbvs-workshop.github.io/challenge.html

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CVPR 2021 New Trends in Image Restoration and Enhancement (NTIRE) workshop and challenges

February 23rd, 2021 Daniela Lopez de Luise
CALL FOR PAPERS  & CALL FOR PARTICIPANTS IN 11 CHALLENGES
NTIRE: 6th New Trends in Image Restoration and Enhancement workshop and challenges on
defocus, deblurring, super-resolution, learning SR space, nonhomogeneous dehazing, image quality assessment, relighting, aerial image classification, enhancement of compressed videos, HDR
In conjunction with CVPR 2021, June 15, Nashville, USA (VIRTUAL).
TOPICS
● Image/video inpainting
● Image/video deblurring
● Image/video denoising
● Image/video upsampling and super-resolution
● Image/video filtering
● Image/video de-hazing, de-raining, de-snowing, etc.
● Demosaicing
● Image/video compression
● Removal of artifacts, shadows, glare and reflections, etc.
● Image/video enhancement: brightening, color adjustment, sharpening, etc.
● Style transfer
● Hyperspectral imaging
● Underwater imaging
● Methods robust to changing weather conditions / adverse outdoor conditions
● Image/video restoration, enhancement, manipulation on constrained settings
● Image/video processing on mobile devices
● Visual domain translation
● Multimodal translation
● Perceptual enhancement
● Perceptual manipulation
● Depth estimation
● Image/video generation and hallucination
● Image/video quality assessment
● Image/video semantic segmentation, depth estimation
● Studies and applications of the above.

SUBMISSION
A paper submission has to be in English, in pdf format, and at most 8 pages (excluding references) in CVPR style.

http://cvpr2021.thecvf.com/node/33

The review process is double blind.
Accepted and presented papers will be published after the conference in the CVPR 2021 Workshops Proceedings.

Author Kit: http://cvpr2021.thecvf.com/sites/default/files/2020-09/cvpr2021AuthorKit_2.zip

WORKSHOP DATES
● Regular Papers Submission Deadline: March 05, 2021
● Challenge Papers Submission Deadline: April 02, 2021

IMAGE CHALLENGES
  1. Defocus Deblurring using Dual-Pixel Images
  2. Depth Guided Relighting (one-to-one and any-to-any)
  3. Perceptual Image Quality Assessment
  4. Deblurring  (low resolution and JPEG artifacts)
  5. Multi-model Aerial View Classification (SAR and EO)
  6. Learning the Super-Resolution Space
  7. Nonhomogeneous Dehazing

VIDEO / MULTI-FRAME CHALLENGES
  1. Enhancement of Compressed Videos (fixed bit-rate and fixed QP)
  2. Super-Resolution (Spatial and Spatio-Temporal)
  3. Burst Super-Resolution (Real and Synthetic)
  4. High Dynamic Range (HDR)
To learn more about the challenges, to participate in the challenges, and to access the data everybody is invited to check the NTIRE 2021 web page:
For those interested in constrained and efficient solutions validated on mobile devices we refer to the CVPR21 Mobile AI Workshop and Challenges:
CHALLENGES DATES

● Release of train data: January 10, 2020
● Competitions end: March 20, 2020

ORGANIZERS

● Radu Timofte, ETH Zurich
● Shuhang Gu, OPPO & University of Sydney
● Kyoung Mu Lee, Seoul National University
● Michael S. Brown, York University

● Andreas Lugmayr, ETH Zurich
● Goutam Bhat, ETH Zurich
● Martin Danelljan, ETH Zurich
● Cosmin Ancuti, Université catholique de Louvain (UCL)
● Codruta O. Ancuti, University Politehnica Timisoara
● Lei Zhang, Alibaba & The Hong Kong Polytechnic University
● Ming-Hsuan Yang, University of California at Merced & Google
● Eli Shechtman, Creative Intelligence Lab at Adobe Research
● Seungjun Nah, Seoul National University, Korea
● Abdullah Abuolaim, York University, Canada
● Eduardo Perez-Pellitero, Huawei Noah's Ark Lab, UK
● Ales Leonardis, Huawei Noah's Ark Lab & University of Birmingham
● Seungjun Nah, Seoul National University
● Sanghyun Son, Seoul National University
● Suyoung Lee, Seoul National University
● Ren Yang, ETH Zurich
● Ruofan Zhou, EPFL
● Majed El Helou, EPFL
● Sabine Süsstrunk, EPFL
● Chao Dong, SIAT
● Jimmy Ren, SenseTime
● Oliver Nina, AF Research Lab
● Bob Lee, Wright Brothers Institute
● Jinjin Gu, University of Sydney
● Luc Van Gool, KU Leuven and ETH Zurich

SPEAKERS (TBA)
SPONSORS (TBA)
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