Machine learning in computer vision: a review
INTRODUCTION: Due to the advancement in the field of Artificial Intelligence (AI), the ability
to tackle entire problems of machine intelligence. Nowadays, Machine learning (ML) is …
to tackle entire problems of machine intelligence. Nowadays, Machine learning (ML) is …
Digital image noise estimation using DWT coefficients
Noise type and strength estimation are important in many image processing applications like
denoising, compression, video tracking, etc. There are many existing methods for estimation …
denoising, compression, video tracking, etc. There are many existing methods for estimation …
Faster as well as early measurements from big data predictive analytics model
Data processing in large scale system and analyses is the key problems of today's
Distributed Systems in real-time and close to real time. These systems should be able, while …
Distributed Systems in real-time and close to real time. These systems should be able, while …
Efficient noise-level estimation based on principal image texture
P Jiang, Q Wang, J Wu - … on Circuits and Systems for Video …, 2019 - ieeexplore.ieee.org
Blind noise-level estimation (NLE) is a fundamental issue in digital image processing. This
paper provides a noise-level estimator for additive white Gaussian noise and multiplicative …
paper provides a noise-level estimator for additive white Gaussian noise and multiplicative …
Detection of pixels corrupted by impulse noise using random point patterns
R Kosarevych, O Lutsyk, B Rusyn - The Visual Computer, 2022 - Springer
This paper presents a novel method for the detection of binary-and random-valued
impulsive noise in contaminated images. The noise detector has been developed to classify …
impulsive noise in contaminated images. The noise detector has been developed to classify …
Gaussian noise level estimation for color image denoising
X Guo, F Liu, X Tian - JOSA A, 2021 - opg.optica.org
Noise level is an important parameter in many visual applications, especially in image
denoising. How to accurately estimate the noise level from a noisy image is a challenging …
denoising. How to accurately estimate the noise level from a noisy image is a challenging …
Noise-aware deep learning algorithm for one-stage multispectral pedestrian detection
Multispectral pedestrian detection has gained momentum in the research literature with its
wide range of applications in car safety, video surveillance, and robotics. We introduce a …
wide range of applications in car safety, video surveillance, and robotics. We introduce a …
Suspicious Activity Detection Using Deep Learning Approach
K Barsagade, S Tabhane, V Satpute… - 2023 1st International …, 2023 - ieeexplore.ieee.org
Video Surveillance plays a pivotal position in today's global. The technologies have superior
an excessive amount of when synthetic intelligence., gadget learning, and deep learning are …
an excessive amount of when synthetic intelligence., gadget learning, and deep learning are …
Classifying Human Activities using CNN and ConvLSTM in Video Sequences
R Gera, KR Ambati, P Chakole… - … on Paradigm Shifts …, 2023 - ieeexplore.ieee.org
Video surveillance plays an important role to analyze any anomaly activity in the given
premises. However, cameras can only capture the video information but cannot determine …
premises. However, cameras can only capture the video information but cannot determine …
Fusion network for blur discrimination
Y Tian, M Luo, L Zhou - Journal of Electronic Imaging, 2021 - spiedigitallibrary.org
Blurry image discrimination is a challenging and critical problem in computer vision. It is
useful for image restoration, object recognition, and other image applications. In previous …
useful for image restoration, object recognition, and other image applications. In previous …