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Intelligent and Advanced Signal Processing Techniques for Data Fusion in Machine Learning Based Remote Sensing Applications

Data fusion has become a popular multidisciplinary approach that combines data from multiple sources to improve the global potential value and interpretation performance and produce a high-quality final representation of the data. Fusion techniques are useful for various applications like object detection, recognition, identification and classification, object tracking, change detection, decision making, etc. And a remarkable improvement over conventional probabilistic data fusion techniques is coming out of machine learning (ML) techniques, which include strong computing and predicting abilities. Despite the fast development, data fusion approaches remain challenging for remote sensing applications due to various requirements, landscape complexity, temporal, spatial, and spectral variations, etc. within the input dataset.

This special issue focuses on intelligent and advanced signal processing techniques to overcome the DF challenges in ML-based remote sensing applications. Indeed, advanced signal processing solutions can be researched to meet DF challenges for RS applications especially when ML techniques are applied. Both theoretical and experimental studies are welcome, particularly papers with good technical insights on the intelligent and advanced signal processing techniques for RS applications.

Lead Guest Editor: 
Silvia Liberata Ullo, University of Sannio, Benevento, Italy

Guest Editors:
Parameshachari B.D. (Bidare Divakarachari), Nitte Meenakshi Institute of Technology, Bangalore, Karnataka, India
Issaak Parcharidis, Harokopio University, Athens, Greece


  1. Fruits significantly impact everyday living, i.e., Citrus fruits. Numerous fruits have a solid nutritious value and are packed with multivitamins and trace components. Citrus fruits are delicate and susceptibl...

    Authors: Poonam Dhiman, Poongodi Manoharan, Umesh Kumar Lilhore, Roobaea Alroobaea, Amandeep Kaur, Celestine Iwendi, Majed Alsafyani, Abdullah M. Baqasah and Kaamran Raahemifar
    Citation: EURASIP Journal on Advances in Signal Processing 2023 2023:72
  2. As the number of passengers at border entry points such as airports and rail stations increases, so does the demand for seamless, secure, and fast biometric technologies for verification purposes. Although fin...

    Authors: Bilal Hassan, Hafiz Husnain Raza Sherazi, Mubashir Ali and Ali K. Bashir
    Citation: EURASIP Journal on Advances in Signal Processing 2023 2023:65
  3. Object detection is one of the essential tasks in computer vision, with most detection methods relying on a limited number of sizes for anchor boxes. However, the boundaries of particular composite objects, su...

    Authors: Shenshen Fu, Yifan He, Xiaofeng Du and Yi Zhu
    Citation: EURASIP Journal on Advances in Signal Processing 2023 2023:53
  4. The fusion of synthetic aperture radar (SAR) and optical satellite data is widely used for deep learning based scene classification. Counter-intuitively such neural networks are still sensitive to changes in s...

    Authors: Jakob Gawlikowski, Sudipan Saha, Julia Niebling and Xiao Xiang Zhu
    Citation: EURASIP Journal on Advances in Signal Processing 2023 2023:47
  5. Aiming at the problem of poor effect of object detection with visible images under low light conditions, the decision-level fusion detection method of visible and infrared images is studied. Taking YOLOX as th...

    Authors: Zuhui Hu, Yaguang Jing and Guoqing Wu
    Citation: EURASIP Journal on Advances in Signal Processing 2023 2023:38
  6. Satellite Image classification provides information about land use land cover (LULC) and this is required in many applications such as Urban planning and environmental monitoring. Recently, deep learning techn...

    Authors: V. N. Vinaykumar, J. Ananda Babu and Jaroslav Frnda
    Citation: EURASIP Journal on Advances in Signal Processing 2023 2023:13
  7. Hyperspectral images have a special attribute with both spectral and spatial information, which is of great significance for the evaluation of the stealth performance of camouflaged targets. Aiming at the prob...

    Authors: Zhenxin He, Yuanying Gan, Shixin Ma, Chuntong Liu and Zhongye Liu
    Citation: EURASIP Journal on Advances in Signal Processing 2023 2023:11