Land use and land cover classification with hyperspectral data: A comprehensive review of methods, challenges and future directions
MA Moharram, DM Sundaram - Neurocomputing, 2023 - Elsevier
Recently, many efforts have been concentrated on land use land cover (LULC) classification
due to rapid urbanization, environmental pollution, agriculture drought, frequent floods, and …
due to rapid urbanization, environmental pollution, agriculture drought, frequent floods, and …
Towards label-efficient automatic diagnosis and analysis: a comprehensive survey of advanced deep learning-based weakly-supervised, semi-supervised and self …
Histopathological images contain abundant phenotypic information and pathological
patterns, which are the gold standards for disease diagnosis and essential for the prediction …
patterns, which are the gold standards for disease diagnosis and essential for the prediction …
Neural image compression for gigapixel histopathology image analysis
We propose Neural Image Compression (NIC), a two-step method to build convolutional
neural networks for gigapixel image analysis solely using weak image-level labels. First …
neural networks for gigapixel image analysis solely using weak image-level labels. First …
VIF-Net: An unsupervised framework for infrared and visible image fusion
Visible images provide abundant texture details and environmental information, while
infrared images benefit from night-time visibility and suppression of highly dynamic regions; …
infrared images benefit from night-time visibility and suppression of highly dynamic regions; …
Visual object tracking by hierarchical attention siamese network
Visual tracking addresses the problem of localizing an arbitrary target in video according to
the annotated bounding box. In this article, we present a novel tracking method by …
the annotated bounding box. In this article, we present a novel tracking method by …
Convolutional neural network-based finger-vein recognition using NIR image sensors
HG Hong, MB Lee, KR Park - Sensors, 2017 - mdpi.com
Conventional finger-vein recognition systems perform recognition based on the finger-vein
lines extracted from the input images or image enhancement, and texture feature extraction …
lines extracted from the input images or image enhancement, and texture feature extraction …
Travelgan: Image-to-image translation by transformation vector learning
M Amodio, S Krishnaswamy - … of the ieee/cvf conference on …, 2019 - openaccess.thecvf.com
Interest in image-to-image translation has grown substantially in recent years with the
success of unsupervised models based on the cycle-consistency assumption. The …
success of unsupervised models based on the cycle-consistency assumption. The …
Finger-vein recognition based on deep DenseNet using composite image
JM Song, W Kim, KR Park - Ieee Access, 2019 - ieeexplore.ieee.org
Finger-vein recognition has the advantages of high immutability, as finger veins are located
under the skin, high user convenience, as a non-invasive and contactless capture device, is …
under the skin, high user convenience, as a non-invasive and contactless capture device, is …
Steel surface defect detection based on self-supervised contrastive representation learning with matching metric
Defect detection is crucial in the quality control of industrial applications. Existing supervised
methods are heavily reliant on the large amounts of labeled data. However, labeled data in …
methods are heavily reliant on the large amounts of labeled data. However, labeled data in …