Results 201 to 210 of about 15,264 (300)

Double-branch feature fusion transformer for hyperspectral image classification. [PDF]

Sci Rep, 2023
Dang L, Weng L, Hou Y, Zuo X, Liu Y.
europepmc   +1 more source

Artificial Intelligence in the Food Industry: Transforming Safety, Efficiency, and Sustainability From Farm to Fork

eFood, Volume 7, Issue 3, June 2026.
This review synthesizes AI advancements in food systems, leveraging machine learning, computer vision, robotics, and IoT for 96%–100% accurate quality inspection, 30% reduced downtime, and enhanced traceability from farm to fork. It highlights transformative potential in sustainability and SDGs while addressing data, ethical, and scalability challenges
Muhammad Waqar, Mariyam Shahid, Manat Chaijan, Worawan Panpipat, Djilali Benabdelmoumene, Ahmed Mediani, Abdifetah Ibrahim Omar, Sabrin R. M. Ibrahim, Qudrat Ullah, Temesgen Anjulo Ageru   +9 more
wiley   +1 more source

EchoMamba: A new Mamba model for fast and efficient hyperspectral image classification. [PDF]

PLoS One
Zhang Y, Jin X, Zhang X, Wu Y, Tu L.
europepmc   +1 more source

Multi-Scale Superpixel-Guided Structural Profiles for Hyperspectral Image Classification. [PDF]

Sensors (Basel), 2022
Wang N, Zeng X, Duan Y, Deng B, Mo Y, Xie Z, Duan P.   +6 more
europepmc   +1 more source

Application of Artificial Intelligence in Food Science and Nutrition: Challenges and Future Perspectives

eFood, Volume 7, Issue 3, June 2026.
AI application can be very helpful in addressing different issues and shaping novel techniques in food production, food safety and quality, and food intake. AI application in food science, such as the food industry and processing, food safety and packaging, and nutrition.
Yaseen Galali, Pary Hadi, Arkan Mohammed Hassan, Holem Hashm Balaky, Tavga Sulaiman Rashid, Bashdar Abuzed Sadee, Tanya Salam Salih, Hamed Hassanzadeh   +7 more
wiley   +1 more source

Correction: A new band selection approach integrated with physical reflectance autoencoders and albedo recovery for hyperspectral image classification. [PDF]

Sci Rep
Sangeetha V, Agilandeeswari L.
europepmc   +1 more source

Backpropagation Network‐Based Contrastive Learning for Unsupervised Domain Adaptation

Engineering Reports, Volume 8, Issue 6, June 2026.
Unsupervised domain adaptation for contractive learning. ABSTRACT This study introduces a new method for domain adaptation for image classification tasks that aims to improve the model's performance on a target domain after being trained on a source domain.
Yushui Xiao, Yong Huang, Yujie Li
wiley   +1 more source

Spectral-spatial wave and frequency interactive transformer for hyperspectral image classification. [PDF]

Sci Rep
Arshad T, Peng B, Rahman A, Khan R, Khan SU, Alnazi S, Alturki N.   +6 more
europepmc   +1 more source

Laser bathymetry on rough riverbed channels: State‐of‐the‐art and future prospects

Earth Surface Processes and Landforms, Volume 51, Issue 6, June 2026.
This literature review found that topo‐bathymetric LiDAR has been successfully used to capture the structures of rough riverbeds and detect large boulders. While all of the studies that were reviewed used sensors that were operated from fixed‐wing aircraft, few studies have yet tested UAV‐borne sensors on rough riverbeds, despite the potential offered ...
Theresa M. Himmelsbach, Gottfried Mandlburger, Bernhard Gems, Jan Rhomberg‐Kauert, Markus Aufleger   +4 more
wiley   +1 more source

Leveraging potential of limpid attention transformer with dynamic tokenization for hyperspectral image classification. [PDF]

PLoS One
Yadav DP, Kumar D, Jalal AS, Sharma B, Liatsis P.   +4 more
europepmc   +1 more source