Results 81 to 90 of about 18,850,036 (270)

Rethinking RGB-D Salient Object Detection: Models, Data Sets, and Large-Scale Benchmarks [PDF]

, 2020
The use of RGB-D information for salient object detection has been extensively explored in recent years. However, relatively few efforts have been put towards modeling salient object detection in real-world human activity scenes with RGBD.
Cheng, Ming-Ming, Lin, Zheng, Zhu, Menglong, Zhao, Jia-Xing, Liu, Yun, Zhang, Zhao, Hou, Qibin, Fan, Deng-Ping   +7 more
core   +1 more source

People Counting and Positioning Using Low‐Resolution Infrared Images for FeFET‐Based In‐Memory Computing

Advanced Electronic Materials, EarlyView.
In this work, low‐resolution infrared imaging is combined with a 28 nm FeFET IMC architecture to enable compact, energy‐efficient edge inference. MLC FeFET devices are experimentally characterized, and controlled multi‐level current accumulation is validated at crossbar array level.
Alptekin Vardar, Li Zhang, Alexander Rehmer, Marc Lupp, Subhashree Baskaran, Osama Abdelaal, Franz Müller, Nandakishor Yadav, Bing Li, Thomas Kämpfe   +9 more
wiley   +1 more source

A multiple‐attention refinement network for RGB‐D salient object detection

IET Image Processing
Most existing RGB‐D salient object detection (SOD) algorithms, when using depth information for cross‐modal fusion, result in significant information redundancy due to issues with low‐quality depth information, ambiguity, and difficulty in discriminating
Zijian Jiang, Ling Yu, Junru Li, Fanglin Niu   +3 more
doaj   +1 more source

Decoupling Thermodynamic and Kinetic Moisture Instability Reveals a Critical Humidity Threshold for Sodium Thiophosphate Solid Electrolyte

Advanced Energy Materials, EarlyView.
A quantitative exposure‐heat treatment framework identifies a critical humidity threshold (15%RH) and heat treatment temperature (80°C) that governs the recoverability of air‐exposed Na3PS4, revealing the decoupled thermodynamic and kinetic contributions to its moisture stability.
Boling Liu, Jingjing Liu, Ahmad Mandouh, Brenna Richardson, Cheng Xu, Soo Yeon Lim, Wenhui Zhu, Md. Monir Hossain, Ruigang Wang, Wei Lai, Chengcheng Fang   +10 more
wiley   +1 more source

Cell Segmentation Beyond 2D—A Review of the State‐of‐the‐Art

Advanced Intelligent Discovery, EarlyView.
Cell segmentation underpins many biological image analysis tasks, yet most deep learning methods remain limited to 2D despite the inherently 3D nature of cellular processes. This review surveys segmentation approaches beyond 2D, comparing 2.5D and fully 3D methods, analyzing 31 models and 32 volumetric datasets, and introducing a unified reference ...
Fabian Schmeisser, Haseeb Muhammad, Junaid Younas, Gillian Lovell, Bianca Migliori, Andreas Dengel, Sheraz Ahmed   +6 more
wiley   +1 more source

S³Net: Self-Supervised Self-Ensembling Network for Semi-Supervised RGB-D Salient Object Detection

, 2023
RGB-D salient object detection aims to detect visually distinctive objects or regions from a pair of the RGB image and the depth image. State-of-the-art RGB-D saliency detectors are mainly based on convolutional neural networks but almost suffer from an ...
Zhu, Lei, Yang, Xin, Wang, Xiaoqiang, Li, Ping, Chen, C. L.Philip, Wang, Weiming, Zhang, Qing, Schonlieb, Carola Bibiane   +7 more
core   +1 more source

AI‐BioMech: Deep Learning Prediction of Mechanical Behavior in Aperiodic Biological Cellular Materials

Advanced Intelligent Discovery, EarlyView.
AI‐BioMech is a deep learning framework that predicts the mechanical behavior of biological cellular materials directly from 2D images. By replacing traditional finite element analysis with semantic segmentation, it identifies stress and strain distributions with 99% accuracy, offering a high‐speed, scalable alternative for analyzing complex, aperiodic
Haleema Sadia, Marcelo A. Dias, Parvez Alam   +2 more
wiley   +1 more source

Saliency-Guided Detection of Unknown Objects in RGB-D Indoor Scenes

Sensors, 2015
This paper studies the problem of detecting unknown objects within indoor environments in an active and natural manner. The visual saliency scheme utilizing both color and depth cues is proposed to arouse the interests of the machine system for detecting
Jiatong Bao, Yunyi Jia, Yu Cheng, Ning Xi   +3 more
doaj   +1 more source

ViDSOD-100: A New Dataset and a Baseline Model for RGB-D Video Salient Object Detection [PDF]

With the rapid development of depth sensor, more and more RGB-D videos could be obtained. Identifying the foreground in RGB-D videos is a fundamental and important task.
Zhu, Lei, Fu, Huazhu, Wang, Liansheng, Lin, Junhao, Shen, Jiaxing, Zhang, Qing   +5 more
core   +1 more source

From Data to Discovery: Machine Learning–Enabled Intelligent Characterization of Two‐Dimensional Materials

Advanced Intelligent Discovery, EarlyView.
Machine learning serves as a central engine for the intelligent characterization of two‐dimensional materials by integrating multimodal techniques, including optical microscopy, spectroscopy, electron microscopy, and scanning probe microscopy (SPM). This unified framework enables automated, high‐throughput, and quantitative extraction of structural ...
Zhi‐Long Cao, Jia‐Xu Yan
wiley   +1 more source