Results 41 to 50 of about 15,597 (201)

Design and Optimization of Full‐Stokes Hyperspectro‐Polarimetric Encoding Metasurfaces Based on Conditional Multi‐Task Deep Learning

Advanced Science, EarlyView.
A conditional multi‐task deep learning framework is developed for designing and optimizing Full‐Stokes Hyperspectro‐Polarimetric Encoding Metasurfaces (FHPEMs). This framework achieves joint spectro‐polarimetric learning and unified forward–inverse design.
Chenjie Gong, Haodong Shi, Qi Wang, Yingchao Li, Hongyu Sun, Jiayu Wang, Guanlin Li, Jian Zhang, Qiang Fu, Huilin Jiang   +9 more
wiley   +1 more source

CDRSHNET: VARIANCE-GUIDED MULTISCALE AND SELF-ATTENTION FUSION WITH HYBRID LOSS FUNCTION TO RESTORE TRAFFIC-SIGN IMAGES CAPTURED IN ADVERSE CONDITIONS

Jordanian Journal of Computers and Information Technology
This paper proposes a CDRSHNet (CodecDirtyRainyShadowHazeNetwork) architecture with a fusion of self-attention (SA) and variance-guided multiscale attention (VGMA) mechanism to restore traffic sign images captured in challenging weather conditions ...
Milind Vijay Parse, Dhanya Pramod
doaj   +1 more source

Improving Visual Defect Detection and Localization in Industrial Thermal Images Using Autoencoders

Journal of Imaging, 2023
Reliable functionality in anomaly detection in thermal image datasets is crucial for defect detection of industrial products. Nevertheless, achieving reliable functionality is challenging, especially when datasets are image sequences captured during ...
Sasha Behrouzi, Marcel Dix, Fatemeh Karampanah, Omer Ates, Nissy Sasidharan, Swati Chandna, Binh Vu   +6 more
doaj   +1 more source

Deep Generative Adversarial Compression Artifact Removal

, 2017
Compression artifacts arise in images whenever a lossy compression algorithm is applied. These artifacts eliminate details present in the original image, or add noise and small structures; because of these effects they make images less pleasant for the ...
Bertini, Marco, Del Bimbo, Alberto, Galteri, Leonardo, Seidenari, Lorenzo   +3 more
core   +1 more source

Emerging Memory and Device Technologies for Hardware‐Accelerated Model Training and Inference

Advanced Electronic Materials, EarlyView.
This review investigates the suitability of various emerging memory technologies as compute‐in‐memory hardware for artificial intelligence (AI) applications. Distinct requirements for training‐ and inference‐centric computing are discussed, spanning device physics, materials, and system integration.
Yoonho Cho, Dae‐won Kim, Yujin Kim, Jung‐Heum Na, Yuwon Jeong, Dong‐Yeop Lee, Shinhyun Choi   +6 more
wiley   +1 more source

From Microscale to Nanoscale Shadow Electrochemiluminescence Microscopy

Angewandte Chemie, EarlyView.
In this research we report on the label‐free shadow electrochemiluminescence (shadow ECL) microscopy of microscale and nanoscale objects. By systematically investigating various influencing factors—including optical configuration, electrode activity, frame averaging, exposure time, and particle arrangement—we further confirm the nano‐imaging potential ...
Xiaodan Gou, Hanna Manko, Jasmina Vidic, Laurent Cognet, Jun‐Jie Zhu, Neso Sojic   +5 more
wiley   +2 more sources

Noise Impact Analysis in Computer-Generated Holography Based on Dual Metrics Evaluation via Peak Signal-to-Noise Ratio and Structural Similarity Index Measure

Applied Sciences
This study investigates the noise impact on reconstructed images in computer-generated holography (CGH) through theoretical analysis and Matlab 2015b simulations.
Yucheng Li, Yang Zhang, Deyu Jia, Song Gao, Muqun Zhang   +4 more
doaj   +1 more source

Virtual UV Fluorescence Microscopy from Hematoxylin and Eosin Staining of Liver Images Using Deep Learning Convolutional Neural Network

Applied Sciences, 2020
The use of UV (ultraviolet fluorescence) light in microscopy allows improving the quality of images and observation of structures that are not visible in visible spectrum. The disadvantage of this method is the degradation of microstructures in the slide
Dorota Oszutowska-Mazurek, Miroslaw Parafiniuk, Przemyslaw Mazurek   +2 more
doaj   +1 more source

Fractal Texture Enhancement of Simulated Infrared Images Using a CNN-Based Neural Style Transfer Algorithm with a Histogram Matching Technique

Sensors, 2022
Here, we propose a CNN-based infrared image enhancement method to transform pseudo-realistic regions of simulation-based infrared images into real infrared texture. The proposed algorithm consists of the following three steps.
Taeyoung Kim, Hyochoong Bang
doaj   +1 more source

Deep Neural Networks for No-Reference and Full-Reference Image Quality Assessment

, 2017
We present a deep neural network-based approach to image quality assessment (IQA). The network is trained end-to-end and comprises ten convolutional layers and five pooling layers for feature extraction, and two fully connected layers for regression ...
Bosse, Sebastian, Maniry, Dominique, Müller, Klaus-Robert, Samek, Wojciech, Wiegand, Thomas   +4 more
core   +1 more source