Results 141 to 150 of about 19,743 (267)

Evaluation of Computer‐aided Detection for Identifying Missed Gastric Cancer After Endoscopic Submucosal Dissection

DEN Open, Volume 7, Issue 1, April 2027.
ABSTRACT Objectives Computer‐aided detection (CADe) using deep learning is promising for reducing missed gastric cancers (MGCs) and supporting physicians in double‐checking endoscopic images. We aimed to evaluate the CADe efficacy for MGCs after endoscopic submucosal dissection (ESD).
Tatsunori Minamide, Tomonori Sato, Seiichiro Sakaguchi, Noboru Kawata, Yuki Maeda, Masao Yoshida, Yoichi Yamamoto, Taishi Okumura, Tetsuya Suwa, Hiroshi Ashizawa, Kohei Shigeta, Haruka Nakamura, Akifumi Notsu, Toshio Uraoka, Hiroyuki Ono   +14 more
wiley   +1 more source

PPFS-YOLO: Physics-Prior Frequency-Spatial Fusion for Robust Container Surface Damage Detection. [PDF]

Sensors (Basel)
Liu J, Gao F.
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

YOLO-FLBM: a lightweight and high-performance model for tomato ripeness detection in complex greenhouse environments. [PDF]

Front Plant Sci
Su Y, Zhang P, Li H, Kang F, Zhao P, Wang L.   +5 more
europepmc   +1 more source

Phenotypic scoring of canola blackleg severity using machine learning image analysis

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Canola blackleg is a fungal disease that causes significant yield loss and plant death of infected canola (Brassica napus L., Brassica rapa L., Brassica juncea L.) fields worldwide. One of the most effective methods for controlling blackleg is through the cultivation of resistant varieties.
Qiao Hu, Sarah Anderson, Stuart Gardner, Thomas W. Ernst, Chadwick B. Koscielny, Navratan S. Bahia, Charles G. Johnson Jr, Andrew C. Jarvis, Joseph S. Hynek, Nathan Coles, Igor Falak, David R. Charne, Manuel E. Ruidiaz, Julien Linares, Anastasios Mazis, Daniel J. Stanton   +15 more
wiley   +1 more source

ASW-YOLO: Lightweight Gear Defect Detection with Improved YOLOv8n. [PDF]

Materials (Basel)
Luo Z, Zheng B.
europepmc   +1 more source

High‐throughput phenotyping for the prediction and quantification of flower‐related traits in sugarcane

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Sugarcane (Saccharum spp.), a C4 plant, is a vital renewable biofuel and sugar source for industries worldwide. However, synchronizing flowering between parental lines often poses challenges for breeders, hindering effective crossbreeding efforts.
Paulo H. da Silva Santos, João R. Vieira Manechini, Carlos Augusto Dias Kanthack Jr., Mauro Alexandre Xavier, Samira Domingues Carlin, Dilermando Perecin, Thiago G. Marconi, Leandro G. Marconi, Elisson Antonio da Costa Romanel, Stephen Derek Jackson, Marcos. G. A. Landell, Luciana R. Pinto   +11 more
wiley   +1 more source

TDD-YOLO: A novel model for precise detection of tomato diseases. [PDF]

PLoS One
Chen Z, Bian Z, Li L, Dai C, Ji Z, Ganchev I.   +5 more
europepmc   +1 more source

Deep learning and computer vision for image‐based high‐throughput phenotyping of canning quality traits in dry beans

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Canning color retention is a key quality trait in dry bean (Phaseolus vulgaris L.) breeding, influencing consumer acceptance and commercial value. Public breeding programs maintain canning quality as a selection trait of importance, but existing color evaluation methods such as visual rating are subjective, while instrument colorimetry is ...
Lovepreet Singh, Om Sai Krishna Madhav Lella, Evan M. Wright, Karen Cichy, Valerio Hoyos‐Villegas   +4 more
wiley   +1 more source

KT-YOLO: A multi-convolution kernel collaboration model for dense Hu sheep behavior detection. [PDF]

PLoS One
Zhang S, Chang H, Wu Z, Wu G, Ji R.
europepmc   +1 more source