Results 81 to 90 of about 15,951 (227)
Електроніка та інформаційні технологіїBackground. In the context of significant contamination of Ukraine's territory with explosive ordnance (EO) resulting from the Russian Federation's aggression and over 11 years of ongoing hostilities, coupled with limited resources for detection and ...
Volodymyr Hrabovskyi +1 more
doaj +1 more source
New Phytologist, EarlyView.A model of the C‐repeat binding factor–salicylic acid (CBF–SA) module in plant wound healing. Summary Repairing damaged tissues is essential for the survival of all organisms. In plants, tissue injury rapidly triggers defense and repair programs. However, the molecular mechanisms linking early injury cues to the later stage of wound repair remain ...
Joseph Michael Balem +8 more
wiley +1 more source
Promet (Zagreb)With the improvement of deep learning technology, traditional obstacle avoidance approaches for blind people can no longer meet practical needs. In response to the problems of poor adaptability to multiple scenarios and low obstacle avoidance rates in ...
Yan ZHUANG
doaj +1 more source
Periodontology 2000, EarlyView.Abstract Background Artificial intelligence (AI) is increasingly gaining attention in the field of periodontology and implant dentistry. Currently developed models can support diagnosis, treatment planning, and maintenance monitoring. However, most of the available literature is based on retrospective and often single‐modality data sets.
Aminollah Khormali +2 more
wiley +1 more source
Wheat Seed Detection and Counting Method Based on Improved YOLOv8 Model
SensorsWheat seed detection has important applications in calculating thousand-grain weight and crop breeding. In order to solve the problems of seed accumulation, adhesion, and occlusion that can lead to low counting accuracy, while ensuring fast detection ...
Na Ma +4 more
doaj +1 more source
Artificial intelligence‐powered plant phenomics: Progress, challenges, and opportunities
The Plant Phenome Journal, Volume 9, Issue 1, December 2026.Abstract Artificial intelligence (AI), a key driver of the Fourth Industrial Revolution, is being rapidly integrated into plant phenomics to automate sensing, accelerate data analysis, and support decision‐making in phenomic prediction and genomic selection.
Xu Wang +12 more
wiley +1 more source
The Plant Phenome Journal, Volume 9, Issue 1, December 2026.Abstract An agronomic trait such as stand count is important for cultivar development and crop management practices. Manually counting the number of plants is time consuming, labor‐intensive, and prone to error. The use of unoccupied aerial systems (UAS)‐collected red, green, blue (RGB) imagery in conjunction with advanced deep learning and image ...
Aliasghar Bazrafkan +1 more
wiley +1 more source
MDD-YOLOv8: A Multi-Scale Object Detection Model Based on YOLOv8 for Synthetic Aperture Radar Images
The targets in Synthetic Aperture Radar (SAR) images are often tiny, irregular, and difficult to detect against complex backgrounds, leading to a high probability of missed or incorrect detections by object detection algorithms. To address this issue and
Huaixin Chen +3 more
core +1 more source
A Comparison of YOLOv8 Series Performance in Student Facial Expressions Detection on Online Learning
JOIN: Jurnal Online InformatikaStudent engagement in online learning is an important factor that can affect learning outcomes. One indicator of engagement is facial expression.
Dewi Tresnawati +2 more
doaj +1 more source
Automatic measurement of rice tiller angle from unmanned aerial vehicle images
The Plant Phenome Journal, Volume 9, Issue 1, December 2026.Abstract Rice (Oryza sativa L.) tiller angle is an important trait that influences plant architecture, canopy light interception, and yield potential. In this study, we proposed a deep learning‐based pipeline for automated measurement of rice tiller angle and plant base width using unmanned aerial vehicle (UAV) imagery.
Tan‐Hanh Pham +10 more
wiley +1 more source