On-device research index

arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,695 papers · 148 categories

Trend · papers per month

count % of corpus

5 results for “YOLOv8”

Automated Pollen Recognition in Optical and Holographic Microscopy Imagescs.CV

Study improves pollen detection in optical and holographic images using deep learning.

problem Improving pollen detection accuracy in holographic microscopy images.

method Used YOLOv8s for detection and MobileNetV3L for classification, addressing performance gaps through dataset expansion and automated labeling.

result Significant improvement in detection and classification performance on holographic images.

pollen recognition deep learning YOLOv8s MobileNetV3L holographic microscopy

2025-12-09abs ↗pdf ↗

Realism in Action: Anomaly-Aware Diagnosis of Brain Tumors from Medical Images Using YOLOv8 and DeiTeess.IV

Framework detects brain tumors robustly from MRI images.

problem Low clinical incidence of brain tumor cases makes diagnosis challenging.

method YOLOv8n for detection, DeiT for classification, PTP metric for evaluation.

result F1-score of 0.92 achieved with reduced computational resources.

brain tumors medical images YOLOv8 DeiT anomaly detection

2024-01-06abs ↗pdf ↗

AI-Augmented Pollen Recognition in Optical and Holographic Microscopy for Veterinary Imagingcs.CV

AI enhances pollen recognition in veterinary imaging using holographic microscopy.

problem Challenges in recognizing pollen in holographic images due to speckle noise and artifacts.

method Training YOLOv8s and MobileNetV3L on dual-modality dataset, employing WGAN-SN for synthetic data augmentation.

result GAN-based augmentation improves object detection and classification in holographic images, closing the performance gap.

AI Pollen Recognition Holographic Microscopy Veterinary Imaging GAN

2025-12-13abs ↗pdf ↗

RCS-YOLO: A Fast and High-Accuracy Object Detector for Brain Tumor Detectioncs.CV

RCS-YOLO improves brain tumor detection speed and accuracy.

problem Efficiently detecting brain tumors with high accuracy and speed.

method Proposes RCS-YOLO, a fast and accurate brain tumor detector using YOLO with Reparameterized Convolution and channel Shuffle.

result RCS-YOLO outperforms other YOLO versions in speed and accuracy on brain tumor detection.

brain tumor detection YOLO object detection fast detection high accuracy

2023-07-31abs ↗pdf ↗

TinyBayes: Closed-Form Bayesian Inference via Jacobi Prior for Real-Time Image Classification on Edge Devicescs.CV

TinyBayes detects crop diseases from images on edge devices with high accuracy and minimal resources.

problem Automated disease detection for cocoa crops in resource-constrained settings.

method Combines YOLOv8-Nano for lesion localisation, MobileNetV3-Small for feature extraction, and Jacobi prior for Bayesian classification.

result Achieves 78.7% accuracy on Amini Cocoa Contamination Challenge dataset with 9.5 MB model size and 150 ms inference time.

TinyBayes Cocoa Swollen Shoot Virus Disease anthracnose edge devices closed-form Bayesian inference

2026-05-07abs ↗pdf ↗