Deep learning based object detection for resource constrained devices: Systematic review, future trends and challenges ahead
Deep learning models are widely being employed for object detection due to their high
performance. However, the majority of applications that require object detection are …
performance. However, the majority of applications that require object detection are …
Lightweight image super-resolution based on stepwise feedback mechanism and multi-feature maps fusion
X Yao, H Chen, Y Li, J Sun, J Wei - Multimedia Systems, 2024 - Springer
In recent years, deep learning has made remarkable breakthroughs in single-image super-
resolution (SISR). However, the improvements often come with the increased network size …
resolution (SISR). However, the improvements often come with the increased network size …
ASFESRN: bridging the gap in real-time corn leaf disease detection with image super-resolution
PV Yeswanth, S Deivalakshmi - Multimedia Systems, 2024 - Springer
Plant diseases pose a significant threat to agricultural productivity, emphasizing the
essential need for early detection and diagnosis. While recent deep learning approaches …
essential need for early detection and diagnosis. While recent deep learning approaches …
SBDet: A Symmetry-Breaking Object Detector via Relaxed Rotation-Equivariance
Introducing Group Equivariant Convolution (GConv) empowers models to explore
symmetries hidden in visual data, improving their performance. However, in real-world …
symmetries hidden in visual data, improving their performance. However, in real-world …
Special issue on deep learning for emerging big multimedia super-resolution
The main goal of the super-resolution (SR) is to restore a visually pleasing high-resolution
image using a low-resolution image of video sequence. The higher resolution image is …
image using a low-resolution image of video sequence. The higher resolution image is …
Iterative dual regression network for blind image super-resolution
C Lei, S Yang, X Yang, B Yan, G Jeon - Signal, Image and Video …, 2023 - Springer
Previous single-image super-resolution methods assume that the blur kernel is known (eg,
bicubic) when degrading from high-resolution (HR) images to low-resolution (LR) images …
bicubic) when degrading from high-resolution (HR) images to low-resolution (LR) images …
Super-Resolution Based on Generative Adversarial Network for HRTEM Images
F Mao, X Guan, R Wang, W Yue - International Journal of Pattern …, 2021 - World Scientific
As an important tool to study the microstructure and properties of materials, High Resolution
Transmission Electron Microscope (HRTEM) images can obtain the lattice fringe image …
Transmission Electron Microscope (HRTEM) images can obtain the lattice fringe image …