Fast YOLOv8 Dog Segmentation Tutorial for Video & Images Understanding YOLOv8 Segmentation for Real Projects

Real-Time Instance Segmentation using YOLOv8 and OpenCV

Reading on Medium: medium.com/image-segmen...

Detailed written explanation and source code: eranfeit.net/fast-yolov8-...
Deep-dive video walkthrough: youtu.be/eaHpGjFSFYE

Eran Feit

#EranFeitTutorial #ImageSegmentation #YoloV8

YOLOv8 Segmentation Tutorial for Multi-Class Football Effortless YOLOv8 Segmentation Tutorial for Multi-Class Football

Football Image segmentation using Yolov8

Reading on Medium: medium.com/@feitgemel/y...
Detailed written explanation and source code: eranfeit.net/yolov8-segme...
Deep-dive video walkthrough: youtu.be/iXaq4OXNwSs

Eran Feit

#EranFeitTutorial #ImageSegmentation #YoloV8

How to Build a Flood Detection Model in 5 Steps Using YOLOv8 How YOLOv8 Flood Segmentation Helps You Map Real Floods

For anyone studying computer vision and semantic segmentation for environmental monitoring.

Detailed written explanation and source code: eranfeit.net/yolov8-segme...

Deep-dive video walkthrough: youtu.be/diZj_nPVLkE

Eran Feit

#ImageSegmentation #YoloV8

Aquatic Waste Sorting and Classification Using Image Processing and Detection System Using YOLOV8 Model and Django - Premier Science Aquatic waste detection, YOLOv8 object detection, Underwater image processing, Real-time waste sorting, Django-based web interface.

doi.org/10.70389/PJS...

#aquaticwastesorting #imageprocessing #YOLOV8 #django

License plate recognition methodology in complex scenarios based on CSCM-YOLOv8 and CSM-LPRNet.
Cao, Lixian et al.
Paper
Details
#LPR #YOLOv8 #LicensePlateRecognition

Low-cost Portable Detector — Nile Red staining + YOLOv8 deep learning on Raspberry Pi with a digital microscope, 385 nm UV, and an optical filter. Rapid in-field counts & classification.
#AI #YOLOv8 #RaspberryPi #OpenHardware

YOLOv8 Outperforms Mask R-CNN for Orchard Instance Segmentation

YOLOv8 achieved 0.93 precision on early‑season fruitlet images, processing each frame in 7.8 ms, outperforming Mask R‑CNN’s 0.85 precision and slower inference. Read more: getnews.me/yolov8-outperforms-mask-... #yolov8 #maskrcnn #agriculture

Deep Learning Detects Microscopic Vehicle Dents with High Precision

A new YOLOv8‑based system can automatically locate microscopic dents on cars in real‑time inspection, with the YOLOv8m‑t42 model achieving 0.86 precision and 0.84 recall. Read more: getnews.me/deep-learning-detects-mi... #deeplearning #yolov8

Tiny Object Detection in Aerial Images with YOLOv8 and MoonNet

Researchers upgraded YOLOv8 with higher resolution, SE and CBAM attention, building MoonNet which outperformed on a tiny aerial object benchmark. Code released on GitHub. Read more: getnews.me/tiny-object-detection-in... #yolov8 #moonnet #tinyobjects

Entrenando a la IA #yolov8 con ayuda de la IA #gemini. Curiosamente las peores clasificaciones son de los animales mirando de frente.

Vi‑SAFE Framework Boosts Real‑Time Violence Detection in Surveillance

Vi‑SAFE merges a lightweight YOLOv8 detector with a Temporal Segment Network, reaching 0.88 accuracy on the RWF‑2000 dataset (vs. 0.77 for TSN alone). Read more: getnews.me/vi-safe-framework-boosts... #visafe #yolov8

YOLOv8 Compression Enables Real‑Time Aerial Detection on Edge Devices

A three‑stage compression pipeline cut YOLOv8m parameters from 25.85 M to 6.85 M (≈73 % drop) while AP50 stays at 47.9 % and inference speed rises from 26 FPS to 45 FPS. Read more: getnews.me/yolov8-compression-enabl... #yolov8 #edgeai

Ultimate YOLOv8 Research Tutorial: Master Custom Object Detection in 10 Steps Are you struggling to adapt existing object detection models for your specific research needs? This comprehensive YOLOv8 research tutorial will transform you from a beginner into an expert capable of customizing state-of-the-art computer vision models for any research application. Computer vision research demands precision, flexibility, and cutting-edge techniques. YOLOv8 represents the pinnacle of object detection technology, but its true power lies in customization.

YOLOv8 research tutorial: Discover 10 powerful steps to customize YOLOv8 for your research. Boost your AI projects today! #YOLOv8 #ObjectDetection #Research #AI #DeepLearning

Radxa Launches M.2 AI Accelerator with Axera AX8850 and 24 TOPS NPU The Radxa AICore AX-M1 is an M.2 M Key AI acceleration module designed for edge computing systems that require high-throughput neural processing. Built around the Axera AX8850 system-on-chip, the module combines an octa-core Cortex-A55 processor with a 24 TOPS INT8-capable NPU and an 8K-capable video processing unit, delivering AI processing capabilities in a compact footprint. According […]

Radxa Launches M.2 AI Accelerator with Axera AX8850 and 24 TOPS NPU The Radxa AICore AX-M1 is an M.2 M Key AI acceleration module designed for edge computing systems that require high-throughput neural processing. Built around the Axera AX8850 system-on-chip, the module combines an octa-core Cortex-A55 processor with a 24 TOPS INT8-capable NPU and an 8K-capable video processing unit, delivering AI processing capabilities in a compact footprint. According […]

Radxa Launches M.2 AI Accelerator with Axera AX8850 and 24 TOPS NPU The Radxa AICore AX-M1 is an M.2 M Key AI acceleration module designed for edge computing systems that require high-throughput neural processing. Built around the Axera AX8850 system-on-chip, the module combines an octa-core Cortex-A55 processor with a 24 TOPS INT8-capable NPU and an 8K-capable video processing unit, delivering AI processing capabilities in a compact footprint. According […]

Mi nuevo modelo entrenado con #yolov8. Con este ya distingue bien un mirlo de una grajilla 🥳 #ia

📢 Classification of oil palm tree conditions from #UAV imagery using the #YOLO object detector by Aakash Thapa, Teerayut Horanont et al.
👉Article link: doi.org/10.1080/2096...
💌 #Oilpalmtree #deeplearning #YOLOv8 #YOLO #objectdetection #precisionagriculture #remotesensing

« L’IA les a tous battus » : en combat aérien, l’intelligence artificielle surpasse les pilotes chinois avec une précision terrifiante - TechGuru Les avancées technologiques dans le domaine de l'intelligence artificielle (IA) ont atteint un nouveau sommet avec le développement par des chercheurs chinois d'un système capable de surpasser les pil...

« L’#IA les a tous battus » : des chercheurs chinois développent une IA capable de surpasser les pilotes humains dans des combats aériens simulés, avec une précision redoutable.
techguru.fr/2025/05/24/l...
#IA #Aérien #Chine #Technologie #Défense #YOLOv8

#yolov8

SciTech Chronicles. . . . . . . . .April 3rd, 2025 Vol II No 3 470 links Curated A man that flees from his fear may find that he has taken a short cut to meet it. NASA Finds Asteroid 2024 YR4...

SciTech Chronicles. . . . . . . . .April 3rd, 2025

bit.ly/stc040325

#NIRCam #NIRCam #infrared #size #air-low #turbulence #simulation #hypersonic #fermentation #microgravity #radiation #Miso #AI #threats #YOLOv8 #DeepSORT #capabilities #AtmoSense #acoustic #electromagnetic

🚨 New #MEE paper! We used #YOLOv8 & smartphone 📷 from Norway’s #NFI to estimate blueberry 🍇& lingonberry 🍒 cover. First step in our #NFI_AI series, showing it's not just about spotting species but quantifying them too!

Huge kudos to Pauline Müller for a ✨MSc thesis!

see 👇 for resources

#AI4Nature

Snap, Scan, and Know: AI Turns Meal Photos into Instant Nutrition Facts NYU Tandon researchers have developed an AI-powered food recognition system that accurately estimates calories and macronutrients from meal photos, eliminating the need for manual food tracking.

Snap, Scan, and Know: AI Turns Meal Photos into Instant Nutrition Facts 🍔📸🤖 www.azoai.com/news/2025031... #AI #Nutrition #HealthTech #FoodTracking #MachineLearning #YOLOv8 #DeepLearning #Wellness #TechInnovation #SmartEating

Snap, Scan, and Know: AI Turns Meal Photos into Instant Nutrition Facts NYU Tandon researchers have developed an AI-powered food recognition system that accurately estimates calories and macronutrients from meal photos, eliminating the need for manual food tracking.

Snap, Scan, and Know: AI Turns Meal Photos into Instant Nutrition Facts 🍔📸🤖 www.azoai.com/news/2025031... #AI #Nutrition #HealthTech #FoodTracking #MachineLearning #YOLOv8 #DeepLearning #Wellness #TechInnovation #SmartEating

Deep Learning-Driven Detection of Polymer Nanoparticles in TEM Images

#AI is not just about detecting cats and dogs! 🚀

In our project, we use #YOLOv8 to detect #polymer #nanoparticles in #TEM images and measure their size in less than a second.

doi.org/10.5281/zeno...

Original post on medium.com

How I Built an AI Fish Doctor with a Raspberry Pi (And How You Can Too) From heartbreak to breakt...

medium.com/@aaghashm/how-i-built-an...

#ai #yolov8 #raspberry-pi #machine-learning […]

Static laser #weeding system based on improved #YOLOv8 and image fusion | doi.org/10.4081/jae.... | www.scopus.com/sourceid/211... | #laser #openaccess #science #AcademicSky #agroengineering #agronomy 🧪🦋 #China

Playing with YOLOv8 and noticed a weird issue: when running inference in two processes simultaneously, the speed drops by 50% despite having plenty of RAM, GPU memory, and available cores. Has anyone encountered this? Any idea where the bottleneck or contention might be? #YOLOv8 #AI #Multithreading

A self-trained model that detects fish species with YOLOv8 🚀👇

📌 I used about 250 labeled images for each fish species

📌 I used the Labelimg repository to tag fish images. It was pretty fast

📌 100 epochs was enough for my model

#ArtificialIntelligence #ObjectDetection #ComputerVision #YOLOv8