A comprehensive survey on impulse and Gaussian denoising filters for digital images

M Mafi, H Martin, M Cabrerizo, J Andrian, A Barreto… - Signal Processing, 2019 - Elsevier
This review article provides a comprehensive survey on state-of-the-art impulse and
Gaussian denoising filters applied to images and summarizes the progress that has been …

Computer-aided diagnosis of liver lesions using CT images: A systematic review

PV Nayantara, S Kamath, KN Manjunath… - Computers in Biology …, 2020 - Elsevier
Background Medical image processing has a strong footprint in radio diagnosis for the
detection of diseases from the images. Several computer-aided systems were researched in …

LLNet: A deep autoencoder approach to natural low-light image enhancement

KG Lore, A Akintayo, S Sarkar - Pattern Recognition, 2017 - Elsevier
In surveillance, monitoring and tactical reconnaissance, gathering visual information from a
dynamic environment and accurately processing such data are essential to making informed …

Efficient federated learning with spike neural networks for traffic sign recognition

K **e, Z Zhang, B Li, J Kang, D Niyato… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
With the gradual popularization of self-driving, it is becoming increasingly important for
vehicles to smartly make the right driving decisions and autonomously obey traffic rules by …

Image denoising: The deep learning revolution and beyond—a survey paper

M Elad, B Kawar, G Vaksman - SIAM Journal on Imaging Sciences, 2023 - SIAM
Image denoising—removal of additive white Gaussian noise from an image—is one of the
oldest and most studied problems in image processing. Extensive work over several …

An unsupervised-learning-based approach for automated defect inspection on textured surfaces

S Mei, H Yang, Z Yin - IEEE transactions on instrumentation …, 2018 - ieeexplore.ieee.org
Automated defect inspection has long been a challenging task especially in industrial
applications, where collecting and labeling large amounts of defective samples are usually …

A novel MP-LSTM method for ship trajectory prediction based on AIS data

D Gao, Y Zhu, J Zhang, Y He, K Yan, B Yan - Ocean Engineering, 2021 - Elsevier
The accurate prediction of ship trajectory has great significance in maritime transportation.
Among all the prediction methods, multi-step prediction has received increasing attention …

Insect detection and classification based on an improved convolutional neural network

D **a, P Chen, B Wang, J Zhang, C **e - Sensors, 2018 - mdpi.com
Regarding the growth of crops, one of the important factors affecting crop yield is insect
disasters. Since most insect species are extremely similar, insect detection on field crops …

Different applied median filter in salt and pepper noise

U Erkan, L Gökrem, S Enginoğlu - Computers & Electrical Engineering, 2018 - Elsevier
In this paper, we proposed a new method, Different Applied Median Filter (DAMF), to remove
salt and pepper (SAP) noise at all densities. We then explained some basic notions of it …

Generating pit-free canopy height models from airborne lidar

A Khosravipour, AK Skidmore… - … & Remote Sensing, 2014 - ingentaconnect.com
Canopy height models (CHMs) derived from lidar data have been applied to extract forest
inventory parameters. However, variations in modeled height cause data pits, which form a …