Test Whats new message.
Scheduled Maintenance on Monday 1/13/2025
Single article sales and account management will be unavailable from 5:00 AM - 7:00 PM ET (09:00 - 23:00 UTC). We apologize for the inconvenience.
Showing 1-11 of 11 results
- Sort
Sort By
Results
NTIRE 2024 Image Shadow Removal Challenge Report
Florin-Alexandru Vasluianu;Tim Seizinger;Zhuyun Zhou;Zongwei Wu;Cailian Chen;Radu Timofte;Wei Dong;Han Zhou;Yuqiong Tian;Jun Chen;Xueyang Fu;Xin Lu;Yurui Zhu;Xi Wang;Dong Li;Jie Xiao;Yunpeng Zhang;Zheng-Jun Zha;Zhao Zhang;Suiyi Zhao;Bo Wang;Yan Luo;Yanyan Wei;Zhihao Zhao;Long Sun;Tingting Yang;Jinshan Pan;Jiangxin Dong;Jinhui Tang;Bilel Benjdira;Mohammed Nassif;Anis Koubaa;Ahmed Elhayek;Anas M. Ali;Kyotaro Tokoro;Kento Kawai;Kaname Yokoyama;Takuya Seno;Yuki Kondo;Norimichi Ukita;Chenghua Li;Bo Yang;Zhiqi Wu;Gao Chen;Yihan Yu;Sixiang Chen;Kai Zhang;Tian Ye;Wenbin Zou;Yunlong Lin;Zhaohu Xing;Jinbin Bai;Wenhao Chai;Lei Zhu;Ritik Maheshwari;Rakshank Verma;Rahul Tekchandani;Praful Hambarde;Satya Narayan Tazi;Santosh Kumar Vipparthi;Subrahmanyam Murala;Jaeho Lee;Seongwan Kim;Sharif S M A;Nodirkhuja Khujaev;Roman Tsoy;Fan Gao;Weidan Yan;Wenze Shao;Dengyin Zhang;Bin Chen;Siqi Zhang;Yanxin Qian;Yuanbin Chen;Yuanbo Zhou;Tong Tong;Rongfeng Wei;Ruiqi Sun;Yue Liu;Nikhil Akalwadi;Amogh Joshi;Sampada Malagi;Chaitra Desai;Ramesh Ashok Tabib;Uma Mudenagudi;Ali Murtaza;Uswah Khairuddin;Ahmad ’Athif Mohd Faudzi;Adinath Dukre;Vivek Deshmukh;Shruti S. Phutke;Ashutosh Kulkarni;Santosh Kumar Vipparthi;Anil Gonde;Subrahmanyam Murala;Arun karthik K;Manasa N;Shri Hari Priya;Wei Hao;Xingzhuo Yan;Minghan Fu
2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
Year: 2024 | Conference Paper |
Cited by: Papers (21)
This work reviews the results of the NTIRE 2024 Challenge on Shadow Removal. Building on the last year edition, the current challenge was organized in two tracks, with a track focused on increased fidelity reconstruction, and a separate ranking for high performing perceptual quality solutions. Track 1 (fidelity) had 214 registered participants, with 17 teams submitting in the final phase, while Tr...Show More
NTIRE 2024 Image Shadow Removal Challenge Report
Florin-Alexandru Vasluianu;Tim Seizinger;Zhuyun Zhou;Zongwei Wu;Cailian Chen;Radu Timofte;Wei Dong;Han Zhou;Yuqiong Tian;Jun Chen;Xueyang Fu;Xin Lu;Yurui Zhu;Xi Wang;Dong Li;Jie Xiao;Yunpeng Zhang;Zheng-Jun Zha;Zhao Zhang;Suiyi Zhao;Bo Wang;Yan Luo;Yanyan Wei;Zhihao Zhao;Long Sun;Tingting Yang;Jinshan Pan;Jiangxin Dong;Jinhui Tang;Bilel Benjdira;Mohammed Nassif;Anis Koubaa;Ahmed Elhayek;Anas M. Ali;Kyotaro Tokoro;Kento Kawai;Kaname Yokoyama;Takuya Seno;Yuki Kondo;Norimichi Ukita;Chenghua Li;Bo Yang;Zhiqi Wu;Gao Chen;Yihan Yu;Sixiang Chen;Kai Zhang;Tian Ye;Wenbin Zou;Yunlong Lin;Zhaohu Xing;Jinbin Bai;Wenhao Chai;Lei Zhu;Ritik Maheshwari;Rakshank Verma;Rahul Tekchandani;Praful Hambarde;Satya Narayan Tazi;Santosh Kumar Vipparthi;Subrahmanyam Murala;Jaeho Lee;Seongwan Kim;Sharif S M A;Nodirkhuja Khujaev;Roman Tsoy;Fan Gao;Weidan Yan;Wenze Shao;Dengyin Zhang;Bin Chen;Siqi Zhang;Yanxin Qian;Yuanbin Chen;Yuanbo Zhou;Tong Tong;Rongfeng Wei;Ruiqi Sun;Yue Liu;Nikhil Akalwadi;Amogh Joshi;Sampada Malagi;Chaitra Desai;Ramesh Ashok Tabib;Uma Mudenagudi;Ali Murtaza;Uswah Khairuddin;Ahmad ’Athif Mohd Faudzi;Adinath Dukre;Vivek Deshmukh;Shruti S. Phutke;Ashutosh Kulkarni;Santosh Kumar Vipparthi;Anil Gonde;Subrahmanyam Murala;Arun karthik K;Manasa N;Shri Hari Priya;Wei Hao;Xingzhuo Yan;Minghan Fu
Year: 2024 | Conference Paper |
A Heuristic Route Planning Scheme in Scalable VANET-Oriented Evolving Grid Graph (S-VoEGG)
Clustering is an excellent solution to divide the network into manageable groups to reduce the excessive overhead. However, the number of clusters can lead to MAC contention (in dense clusters) and network disconnection (in sparse clusters) problems. This paper proposes a heuristic and scalable route planning scheme for traffic congestion avoidance and optimal data communications. The contribution...Show More
Streamlined Global and Local Features Combinator (SGLC) for High Resolution Image Dehazing
2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
Year: 2023 | Conference Paper |
Cited by: Papers (6)
Image Dehazing aims to remove atmospheric fog or haze from an image. Although the Dehazing models have evolved a lot in recent years, few have precisely tackled the problem of High-Resolution hazy images. For this kind of image, the model needs to work on a downscaled version of the image or on cropped patches from it. In both cases, the accuracy will drop. This is primarily due to the inherent fa...Show More
NTIRE 2023 HR NonHomogeneous Dehazing Challenge Report
Codruta O. Ancuti;Cosmin Ancuti;Florin-Alexandru Vasluianu;Radu Timofte;Han Zhou;Wei Dong;Yangyi Liu;Jun Chen;Yangyi Liu;Huan Liu;Liangyan Li;Zijun Wu;Jun Chen;Yubo Dong;Yuyan Li;Tian Qiu;Yu He;Yonghong Lu;Yinwei Wu;Zhenxiang Jiang;Songhua Liu;Xingyi Yang;Yongcheng Jing;Bilel Benjdira;Anas M. Ali;Anis Koubaa;Hao-Hsiang Yang;I-Hsiang Chen;Wei-Ting Chen;Zhi-Kai Huang;Yi-Chung Chen;Chia-Hsuan Hsieh;Hua-En Chang;Yuan-Chun Chiang;Sy-Yen Kuo;Yu Guo;Yuan Gao;Ryan Wen Liu;Yuxu Lu;Jingxiang Qu;Shengfeng He;Wenqi Ren;Trung Hoang;Haichuan Zhang;Amirsaeed Yazdani;Vishal Monga;Lehan Yang;Alex Jiahao Wu;Tiancheng Mai;Xiaofeng Cong;Xuemeng Yin;Xuefei Yin;Hazim Emad;Ahmed Abdallah;Yahya Yasser;Dalia Elshahat;Esraa Elbaz;Zhan Li;Wenqing Kuang;Ziwei Luo;Fredrik K. Gustafsson;Zheng Zhao;Jens Sjölund;Thomas B. Schön;Zhao Zhang;Yanyan Wei;Junhu Wang;Suiyi Zhao;Huan Zheng;Jin Guo;Yangfan Sun;Tianli Liu;Dejun Hao;Kui Jiang;Anjali Sarvaiya;Kalpesh Prajapati;Ratnadeep Patra;Pragnesh Barik;Chaitanya Rathod;Kishor Upla;Kiran Raja;Raghavendra Ramachandra;Christoph Busch
2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
Year: 2023 | Conference Paper |
Cited by: Papers (6)
This study assesses the outcomes of the NTIRE 2023 Challenge on Non-Homogeneous Dehazing, wherein novel techniques were proposed and evaluated on new image dataset called HD-NH-HAZE. The HD-NH-HAZE dataset contains 50 high resolution pairs of real-life outdoor images featuring nonhomogeneous hazy images and corresponding haze-free images of the same scene. The nonhomogeneous haze was simulated usi...Show More
NTIRE 2023 HR NonHomogeneous Dehazing Challenge Report
Codruta O. Ancuti;Cosmin Ancuti;Florin-Alexandru Vasluianu;Radu Timofte;Han Zhou;Wei Dong;Yangyi Liu;Jun Chen;Yangyi Liu;Huan Liu;Liangyan Li;Zijun Wu;Jun Chen;Yubo Dong;Yuyan Li;Tian Qiu;Yu He;Yonghong Lu;Yinwei Wu;Zhenxiang Jiang;Songhua Liu;Xingyi Yang;Yongcheng Jing;Bilel Benjdira;Anas M. Ali;Anis Koubaa;Hao-Hsiang Yang;I-Hsiang Chen;Wei-Ting Chen;Zhi-Kai Huang;Yi-Chung Chen;Chia-Hsuan Hsieh;Hua-En Chang;Yuan-Chun Chiang;Sy-Yen Kuo;Yu Guo;Yuan Gao;Ryan Wen Liu;Yuxu Lu;Jingxiang Qu;Shengfeng He;Wenqi Ren;Trung Hoang;Haichuan Zhang;Amirsaeed Yazdani;Vishal Monga;Lehan Yang;Alex Jiahao Wu;Tiancheng Mai;Xiaofeng Cong;Xuemeng Yin;Xuefei Yin;Hazim Emad;Ahmed Abdallah;Yahya Yasser;Dalia Elshahat;Esraa Elbaz;Zhan Li;Wenqing Kuang;Ziwei Luo;Fredrik K. Gustafsson;Zheng Zhao;Jens Sjölund;Thomas B. Schön;Zhao Zhang;Yanyan Wei;Junhu Wang;Suiyi Zhao;Huan Zheng;Jin Guo;Yangfan Sun;Tianli Liu;Dejun Hao;Kui Jiang;Anjali Sarvaiya;Kalpesh Prajapati;Ratnadeep Patra;Pragnesh Barik;Chaitanya Rathod;Kishor Upla;Kiran Raja;Raghavendra Ramachandra;Christoph Busch
Year: 2023 | Conference Paper |
Securing the Classification of COVID-19 in Chest X-ray Images: A Privacy-Preserving Deep Learning Approach
2022 2nd International Conference of Smart Systems and Emerging Technologies (SMARTTECH)
Year: 2022 | Conference Paper |
Cited by: Papers (10)
Deep learning (DL) is being increasingly utilized in healthcare-related fields due to its outstanding efficiency. However, we have to keep the individual health data used by DL models private and secure. Protecting data and preserving the privacy of individuals has become an increasingly prevalent issue. The gap between the DL and privacy communities must be bridged. In this paper, we propose priv...Show More
Deep Neural Network based Secured Control of Flying Vehicle in Urban Environment
Adeel Zaidi;Muhammad Kazim;Lixian Zhang;Ahmad Taher Azar;Anis Koubaa;Bilel Benjdira;Adel Ammar;Mohammad Abdelkader
2022 2nd International Conference of Smart Systems and Emerging Technologies (SMARTTECH)
Year: 2022 | Conference Paper |
Cited by: Papers (3)
Aerial transport for daily inter- and intra-urban passenger mobility has been a human dream for decades ago. Now, the dream is near to be realized after the great technological advances achieved recently. As urban populations' size increases, traffic congestion and air pollution remain major threats to economic growth. However, questions concerning safe and secure autonomous flying vehicles remain...Show More
Parking Analytics Framework using Deep Learning
2022 2nd International Conference of Smart Systems and Emerging Technologies (SMARTTECH)
Year: 2022 | Conference Paper |
Cited by: Papers (4)
With the number of vehicles continuously increasing, parking monitoring and analysis are becoming a substantial feature of modern cities. In this study, we present a methodology to monitor car parking areas and to analyze their occupancy in real-time. The solution is based on a combination between image analysis and deep learning techniques. It incorporates four building blocks put inside a pipeli...Show More
A Hybrid Deep Learning Model for UAVs Detection in Day and Night Dual Visions
Alam Noor;Kai Li;Adel Ammar;Anis Koubaa;Bilel Benjdira;Eduardo Tovar
2021 IEEE Third International Conference on Cognitive Machine Intelligence (CogMI)
Year: 2021 | Conference Paper |
Cited by: Papers (2)
Unmanned Aerial Vehicle (UAV) detection for public safety protection is becoming a critical issue in non-fly zones. There are plenty of attempts of the UAV detection using single stream (day or night vision). In this paper, we propose a new hybrid deep learning model to detect the UAV s in day and night visions with a high detection precision and accurate bounding box localization. The proposed hy...Show More
DriftNet: Aggressive Driving Behaviour Detection using 3D Convolutional Neural Networks
2020 First International Conference of Smart Systems and Emerging Technologies (SMARTTECH)
Year: 2020 | Conference Paper |
Cited by: Papers (6)
Aggressive driving (i.e., car drifting) is a dangerous behavior that puts human safety and life into a significant risk. In this paper, we targeted this issue and proposed DriftNet, a deep learning model to detect aggressive driving behavior automatically from videos. It is built upon a DenseNet 3D backbone. DrifNet has proven the ability to learn both spatial and temporal features related to car ...Show More
Activity Monitoring of Islamic Prayer (Salat) Postures using Deep Learning
Anis Koubaa;Adel Ammar;Bilel Benjdira;Abdullatif Al-Hadid;Belal Kawaf;Saleh Ali Al-Yahri;Abdelrahman Babiker;Koutaiba Assaf;Mohannad Ba Ras
2020 6th Conference on Data Science and Machine Learning Applications (CDMA)
Year: 2020 | Conference Paper |
Cited by: Papers (20)
In the Muslim community, the prayer (i.e. Salat) is the second pillar of Islam, and it is the most essential and fundamental worshiping activity that believers have to perform five times a day. From a gestures' perspective, there are predefined human postures that must be performed in a precise manner. However, for several people, these postures are not correctly performed, due to being new to Sal...Show More
Car Detection using Unmanned Aerial Vehicles: Comparison between Faster R-CNN and YOLOv3
Bilel Benjdira;Taha Khursheed;Anis Koubaa;Adel Ammar;Kais Ouni
2019 1st International Conference on Unmanned Vehicle Systems-Oman (UVS)
Year: 2019 | Conference Paper |
Cited by: Papers (195)
Unmanned Aerial Vehicles are increasingly being used in surveillance and traffic monitoring thanks to their high mobility and ability to cover areas at different altitudes and locations. One of the major challenges is to use aerial images to accurately detect cars and count-them in real-time for traffic monitoring purposes. Several deep learning techniques were recently proposed based on convoluti...Show More
IEEE Account
Purchase Details
Profile Information
Need Help?
- US & Canada: +1 800 678 4333
- Worldwide: +1 732 981 0060
- Contact & Support
- About IEEE Xplore
- Contact Us
- Help
- Accessibility
- Terms of Use
- Nondiscrimination Policy
- Sitemap
- Privacy & Opting Out of Cookies
A not-for-profit organization, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity.
© Copyright 2025 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.