Results 261 to 270 of about 757,026 (325)

Smart ROUV advances for enhanced navigation in the Suez Canal. [PDF]

Sci Rep
Oqda K, Ibrahim KM, Mustafa AI, Allam RG, Saad MA, Asl AI, Samie MAA, Ibrahim SAF, Ghanem HY, Habib MM, Metwalliy MA, Marie HS.   +11 more
europepmc   +1 more source

Robustness of high‐throughput prediction of leaf ecophysiological traits using near infrared spectroscopy and poro‐fluorometry

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Water scarcity is a major threat to crop production and quality. Improving drought tolerance through variety selection requires a deeper understanding of plant ecophysiological responses, but large‐scale phenotyping remains a bottleneck. This study assessed the potential of high‐throughput tools (spectroscopy and poro‐fluorometry) to predict ...
Eva Coindre, Romain Boulord, Laurine Chir, Virgilio Freitas, Maxime Ryckewaert, Thomas Laisné, Virginie Bouckenooghe, Maëlle Lis, Llorenç Cabrera‐Bosquet, Agnès Doligez, Thierry Simonneau, Benoît Pallas, Aude Coupel‐Ledru, Vincent Segura   +13 more
wiley   +1 more source

The Multi-Sensor and Multi-Temporal Dataset of Multiple Crops for In-Field Phenotyping and Monitoring. [PDF]

Sci Data
Chong YL, Krämer J, Chakhvashvili E, Marks E, Esser F, Dreier A, Rosu RA, Warstat K, Pude R, Behnke S, Muller O, Rascher U, Kuhlmann H, Stachniss C, Behley J, Klingbeil L.   +15 more
europepmc   +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, Daeun Choi, Damian Adams, Jaehyun Ahn, Kelly Balmant, Raquel Dias, Carlos D. Messina, Rafael Muñoz‐Carpena, Vance M. Whitaker, Haipeng Yu, Ziwen Yu, Chang Zhao, Changying Li   +12 more
wiley   +1 more source

Segment-Based SLAM Registration Optimization Algorithm Combining NDT and PL-ICP. [PDF]

Sensors (Basel)
Zhang Y, Wang X, Lyu X, Zhang L, Song W, Zhang R.   +5 more
europepmc   +1 more source

Immersive Gamified Training Simulations for Visualization of Structural Maintenance With Virtual Reality

Computer Applications in Engineering Education, Volume 34, Issue 2, March 2026.
ABSTRACT Identification of damage and key structural elements is vital to the monitoring and management of civil engineering projects, education, and training. However, practical inspection training is often constrained by cost, safety risk, and limited access to real structures, which reduces opportunities for repeated practice and feedback‐rich ...
Elliott Carter, Joel Friesen Walder, Paul Mensink, Ayan Sadhu   +3 more
wiley   +1 more source

Intelligent path control of autonomous AGVs in flexible manufacturing systems: a reinforcement learning approach. [PDF]

Sci Rep
Umakarthikeyan S, Priyadharshini S.
europepmc   +1 more source

Prioritized Real‐Time UAV‐Based Vessel Detection for Efficient Maritime Search

Journal of Field Robotics, Volume 43, Issue 2, Page 561-577, March 2026.
ABSTRACT Real‐time vessel detection in maritime environments is crucial for diverse applications requiring speed and accuracy. Static camera views often introduce blind spots, compromising detection efficiency. This paper proposes a novel, real‐time UAV‐based system that uses a dynamic camera control strategy to address this limitation.
Lyes Saad Saoud, Zikai Jia, Siyuan Yang, Muhayy Ud Din, Lakmal Seneviratne, Shaoming He, Irfan Hussain   +6 more
wiley   +1 more source

Research on multi-source data fusion and high-precision mapping method for complex landforms based on computer vision. [PDF]

Sci Rep
Yang A.
europepmc   +1 more source

From “Mirror Flower, Water Moon” to Multi‐Task Visual Prospective Representation Learning for Unmanned Aerial Vehicles Indoor Mapless Navigation

Journal of Field Robotics, Volume 43, Issue 2, Page 655-680, March 2026.
ABSTRACT Vision‐based deep learning models have been widely adopted in autonomous agents, such as unmanned aerial vehicles (UAVs), particularly in reactive control policies that serve as a key component of navigation systems. These policies enable agents to respond instantaneously to dynamic environments without relying on pre‐existing maps.
Yingxiu Chang, Yongqiang Cheng, John Murray, Muhammad Khalid, Umar Manzoor   +4 more
wiley   +1 more source