Results 141 to 150 of about 79,319 (254)

Improved Mask R-CNN Multi-Target Detection and Segmentation for Autonomous Driving in Complex Scenes. [PDF]

Sensors (Basel), 2023
Fang S, Zhang B, Hu J.
europepmc   +1 more source

Redefining Optimal Coverage Path Planning for FLS‐Equipped AUVs With Deep Reinforcement Learning

Journal of Field Robotics, EarlyView.
ABSTRACT Autonomous Underwater Vehicles (AUVs) have emerged as indispensable tools for a variety of subsea tasks, from habitat monitoring and seabed mapping to infrastructure inspection and mine countermeasures. A fundamental challenge in this field is Coverage Path Planning (CPP), the problem of ensuring complete and efficient area coverage.
Lorenzo Cecchi, Alberto Topini, Alessandro Bucci, Alessandro Ridolfi   +3 more
wiley   +1 more source

A Mask R-CNN-Based Approach for Brain Aneurysm Detection and Segmentation from TOF-MRA Data. [PDF]

Brain Sci
Aykaç E, Göksungur G, Albayrak GS, Yüksel ME.   +3 more
europepmc   +1 more source

Marker-less tracking system for multiple mice using Mask R-CNN. [PDF]

Front Behav Neurosci, 2022
Sakamoto N, Kakeno H, Ozaki N, Miyazaki Y, Kobayashi K, Murata T.   +5 more
europepmc   +1 more source

Wall‐to‐wall Amazon forest height mapping with Planet NICFI, Aerial LiDAR, and a U‐Net regression model

Remote Sensing in Ecology and Conservation, EarlyView.
Tree canopy height is a key indicator of forest biomass and structure, yet accurate mapping across the Amazon remains challenging. Here, we generated a canopy height map of the Amazon forest at ~4.8 m resolution using Planet NICFI imagery and a deep learning U‐Net model trained with airborne LiDAR data.
Fabien H. Wagner, Ricardo Dalagnol, Griffin Carter, Mayumi C. M. Hirye, Shivraj Gill, Le Bienfaiteur Sagang Takougoum, Samuel Favrichon, Michael Keller, Jean P. H. B. Ometto, Lorena Alves, Cynthia Creze, Stephanie P. George‐Chacon, Shuang Li, Zhihua Liu, Adugna Mullissa, Yan Yang, Erone G. Santos, Sarah R. Worden, Martin Brandt, Philippe Ciais, Stephen C. Hagen, Sassan Saatchi   +21 more
wiley   +1 more source

Improvement of mask R-CNN and deep learning for defect detection and segmentation in electronic products. [PDF]

PLoS One
Guo L, Meng J, Hao W, Kumar Jain D.
europepmc   +1 more source

Improving forest age estimation to understand subtropical forest regrowth dynamics using deep learning image segmentation of time‐series historical aerial photographs

Remote Sensing in Ecology and Conservation, EarlyView.
Accurately estimating forest age is key to understanding how forests recover and evaluating restoration success. We developed a two‐step deep learning approach using historical greyscale aerial photographs to map forest age at fine spatial scales. By combining a pre‐trained model with localized fine‐tuning, our U‐Net + ResNet50 architecture achieved ...
Ying Ki Law, Yi‐Fei Gu, Shuwen Liu, Guangqin Song, Aland H. Y. Chan, Cham Man Tse, Zhonghua Liu, Martha J. Ledger, Billy C. H. Hau, Sawaid Abbas, Jin Wu   +10 more
wiley   +1 more source

Comparison of Mask-R-CNN and Thresholding-Based Segmentation for High-Throughput Phenotyping of Walnut Kernel Color. [PDF]

Plants (Basel)
Lee SH, McDowell S, Leslie C, McCreery K, Earles M, Brown PJ.   +5 more
europepmc   +1 more source

Retracted: Efficient Approach towards Detection and Identification of Copy Move and Image Splicing Forgeries Using Mask R-CNN with MobileNet V1. [PDF]

Comput Intell Neurosci, 2023
Intelligence And Neuroscience C.
europepmc   +1 more source

Time‐series digital camera photos combined with machine learning algorithms can realize accurate observation of flowering phenology

Remote Sensing in Ecology and Conservation, EarlyView.
Intelligent approaches are required to extract valuable phenological information from time‐series digital camera photos. In this research, we employed YOLO‐based object detection and semantic segmentation models to identify flowers and flower pixels, acquire flower count and flower cover data, and extract phenophases such as first, peak, and end ...
Chuangye Song, Yuan Jia, Lin Zhang, Dongxiu Wu   +3 more
wiley   +1 more source