Results 191 to 200 of about 16,153 (228)

A comparative analysis of YOLOv8 and nnU-Net v2 based pipelines for sex and age estimation from maxillary sinus morphometry on panoramic radiographs. [PDF]

Int J Legal Med
Ocak M, Çatak C, Aksoy S, Orhan K.
europepmc   +1 more source

Integrating skeleton based representations for robust yoga pose classification using deep learning models. [PDF]

Sci Rep
Mohiuddin M, Hossain SMM, Khanam S, Barua P, Barua A, Hossain MDT.   +5 more
europepmc   +1 more source

Automated karyotyping and structural anomaly detection through a hybrid multi-stage deep learning framework integrating chromosome detection, pairwise classification, and autoencoder-based analysis. [PDF]

Sci Rep
Rosas-Alatriste C, Rodríguez-Rodríguez NO, Argüelles-Cruz AJ, Rosas-Cabral A, Yáñez-Márquez C, Alarcón-Paredes A.   +5 more
europepmc   +1 more source

Deep learning based load station inspection for smart manufacturing with limited data. [PDF]

Int J Adv Manuf Technol
Ijaz Y, Coleman S, Kerr D, Siddique N, McAteer C, Baker B, Nguyen K.   +6 more
europepmc   +1 more source

Accelerator-Free Thermal Pose Estimation: Accuracy-Efficiency Trade-Offs on the Raspberry Pi 5. [PDF]

Sensors (Basel)
Vdoviak G, Sledevič T, Matuzevičius D.
europepmc   +1 more source

SPAE-YOLOv8 for Onboard Real-Time Perception: Lightweight Small UAV Detection from Air-to-Air Perspectives. [PDF]

Sensors (Basel)
Zhang R, Fu X.
europepmc   +1 more source

Harris Hawks-tuned severity-aware YOLOv8 instance segmentation framework for vehicle damage assessment. [PDF]

Sci Rep
Dalal S, Sharma YK, Kundu S, Rokade MD, Pradeep M, Choudhary P, Dubale Anamo M, Hashmi A.   +7 more
europepmc   +1 more source

Student Behavior Detection in the Classroom Based on Improved YOLOv8

Sensors, 2023
Accurately detecting student classroom behaviors in classroom videos is beneficial for analyzing students’ classroom performance and consequently enhancing teaching effectiveness.
Guohui Zhou
exaly   +2 more sources

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YOLOv8-LC9: a modified YOLOv8 for weld surface detection

Engineering Research Express
Abstract In order to address the computational resource constraints experienced in weld inspection equipment, this study proposes YOLOv8-LC9, a lightweight real-time detection model. The model is built upon ResNet, integrating depthwise, group, and pointwise convolutions to construct lightweight feature extraction modules (C9 and C3Ghost)
Zhaokai Sun, Zemin Feng, Ming Zhang
openaire   +1 more source