Mr. | Benjamin | Kwakye Danso | University of Science and Technology of China | China | Computer Science | Metaheuristic algorithms | Best Paper Award |
Dr. | Argyro | Klini | IESL-FORTH | Greece | Physics and Astronomy | Materials Science | Best Researcher Award |
Dr. | Jin-Lu | Huang | Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine | China | Pharmacology, Toxicology and Pharmaceutical Science | Hospital Pharmacy, Clinical pharmacy | Best Scholar Award |
Prof. | Sjaak | Bloem | Nyenrode Business University | Netherlands | Economics, Econometrics and Finance | Health Economics | Best Researcher Award |
Assoc. Prof. Dr. | Danfeng | Zhang | Associate dean of School of Biomedical & Chemical Engineering at Liaoning Institue of Science and Technology | China | Chemistry | •Photocatalysis oxidation/reduction on environmental pollutants by functional materials./ Analysis and detection of organic pollutants and chemical colorants by MSPE-HPLC method. | Best Researcher Award |
Assoc. Prof. Dr. | Yan | Li | Fudan University | China | Chemistry | Computational Chemistry, CADD/AIDD | Best Researcher Award |
Dr. | Sam | Amosa | The National University of Samoa | Samoa | Arts and Humanities | Public Theology | Best Researcher Award |
Prof. Dr. | Wei | Qiu | Tianjin University | China | Physics and Astronomy | semiconductor & aerospace | Best Researcher Award |
Dr. | Şenol | Yağdı | University of Vienna | Austria | Social Sciences | Religious Education | Best Researcher Award |
Prof. | paul | fenton | Sorbonne Université | France | Arts and Humanities | History of Religions | Excellence in Research Award |
Prof. | Daniela | Tarantino | University of Genoa, Department of Political and International Sciences | Italy | Social Sciences | Canon and Ecclesiastical Law, Comparative Law of Religions | Best Researcher Award |
Dr. | S. Azhagu Madhavan | | Saveetha University, Chennai | India | Biochemistry, Genetics and Molecular Biology | Pharmacology, Biomarkers | Best Researcher Award |
Prof. Dr. | Eduardo | Delgado-Orusco | Universidad de Zaragoza | Spain | Arts and Humanities | Proyecto Arquitectónico | Best Researcher Award |
Mr. | lubin | wang | Guilin Institute of Information Technology | China | Computer Science | Computer Vision | Best Researcher Award |
Dr. | Huang | Xiaosan | Nanjing Agricultural university | China | Agricultural and Biological Sciences | Pomology | Best Researcher Award |
Prof. | Jianghong | Zhao | Dear Author, We are pleased to inform you that your recent publication has been provisionally selected for the "Best Researcher Award." Submit your profile via Nomination Link: https://jut.li/RGKJl Regards, Organizing Committee, International Research Excellence Awards-Book of Award. contact@bookofaward.com Reference: To bridge the modality gap between camera images and LiDAR point clouds in autonomous driving systems—a critical challenge exacerbated by current fusion methods’ inability to effectively integrate cross-modal features—we propose the Cross-Modal Fusion (CMF) framework. This attention-driven architecture enables hierarchical multi-sensor data fusion, achieving state-of-the-art performance in semantic segmentation tasks.The CMF framework first projects point clouds onto the camera coordinates through the use of perspective projection to provide spatio-depth information for RGB images. Then, a two-stream feature extraction network is proposed to extract features from the two modalities separately, and multilevel fusion of the two modalities is realized by a residual fusion module (RCF) with cross-modal attention. Finally, we design a perceptual alignment loss that integrates cross-entropy with feature matching terms, effectively minimizing the semantic discrepancy between camera and LiDAR representations during fusion. The experimental results based on the SemanticKITTI and nuScenes benchmark datasets demonstrate that the CMF method achieves mean intersection over union (mIoU) scores of 64.2% and 79.3%, respectively, outperforming existing state-of-the-art methods in regard to accuracy and exhibiting enhanced robustness in regard to complex scenarios. The results of the ablation studies further validate that enhancing the feature interaction and fusion capabilities in semantic segmentation models through cross-modal attention and perceptually guided cross-entropy loss (Pgce) is effective in regard to improving segmentation accuracy and robustness. https://www.mdpi.com/1424-8220/25/8/2474 | China | Engineering | Surveying and Mapping Science and Technology | Best Researcher Award |
Dr. | Fabio | Matiussi | Imaging Institute of Southern Switzerland | Switzerland | Computer Science | Artificial intelligence | Innovative Research Award |
Prof. Dr. | Qudong | Wang | Shanghai Jiao Tong University | China | Materials Science | Materials Processing Engineering | Best Researcher Award |
Prof. | kun | yang | nanjing university of aeronautics and astronautics | China | Engineering | nuclear engineering | Best Researcher Award |
Ms. | Yeeshtdevisingh | Hosanee | University of Technology | Mauritius | Computer Science | Software and Artificial Intelligence | Women Research Award |