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***Research Paper/Project Update*** Excited to share our recent work accepted at ECCV 2024 spearheaded by Abrar Majeedi 😁 🎉. Do checkout this work that he plans to present in Milan. One line description about project: How to assess the performance of a diver (or actions of a surgeon) and score it? How certain can we be about the model's predicted score and can we have a step-wise feedback to trust the model's predictions? Fun coincidence: One of the datasets we evaluated is related to Olympics Diving and the timing of this paper with 2024 Paris Olympics felt nice 😎 #MachineLearning #AI #ComputerVision #SportsResearch #ECCV

"YALTAi introduces a game-changing approach to layout analysis in OCR and similar tasks. By leveraging object detection instead of pixel classification, it significantly enhances segmentation efficiency. The incorporation of YOLOv5 into Kraken 4.1's pipeline yields remarkable performance gains, particularly on smaller datasets. This innovation marks a pivotal shift in document digitization, promising superior extraction accuracy and noise reduction. #AI #MachineLearning #ComputerVision #YALTAi #KrakenEngine"

Exploring EfficientAD: Accurate Visual Anomaly Detection at Millisecond-Level Latencies: A Brief Overview via #TowardsAI → https://bit.ly/3wvbkgS

Exploring EfficientAD: Accurate Visual Anomaly Detection at Millisecond-Level Latencies: A Brief Overview via #TowardsAI → https://bit.ly/3wvbkgS

𝐄𝐱𝐜𝐢𝐭𝐢𝐧𝐠 𝐍𝐞𝐰𝐬 𝐢𝐧 𝐎𝐛𝐣𝐞𝐜𝐭 𝐃𝐞𝐭𝐞𝐜𝐭𝐢𝐨𝐧: 𝐘𝐎𝐋𝐎-𝐖𝐨𝐫𝐥𝐝 Thrilled to share an innovative new development in the field of object detection - YOLO-World. Building on the efficiency and practicality established by the You Only Look Once (YOLO) series of detectors, YOLO-World brings an open-vocabulary detection capability to the table. Traditional detectors are limited by predefined and trained object categories. However, YOLO-World moves beyond these confines by incorporating vision-language modeling and pre-training on large-scale datasets: this manifests as consistent, exceptional performance in detecting an expansive range of objects in a zero-shot manner while maintaining high efficiency. The technological innovation behind this approach is the newly-proposed Re-parameterizable Vision-Language Path Aggregation Network (RepVL-PAN) combined with a region-text contrastive loss. These facilitate a more profound interaction between visual and linguistic information. The results speak for themselves: on the challenging LVIS dataset, YOLO-World achieves a 35.4 average precision (AP) at an impressive 52.0 frames per second (FPS) on V100. This achievement outperforms many state-of-the-art methods in terms of both speed and accuracy. More interestingly, the fine-tuned YOLO-World shows remarkable performance on several downstream tasks. This includes object detection and open-vocabulary instance segmentation, highlighting broad applications and potential for this technology. 🔗 https://lnkd.in/gzYp_b2w YOLO-World is a serious game-changer, introducing flexibility and scalability to object detection that was previously unattainable. Stay tuned for more developments in this space! #AI #ObjectDetection #MachineLearning #yolo #computervision #datascience #artificialintelligence #innovation #technology #visionmodeling #YOLO-World

How to Improve Graphs to Empower Your Machine-Learning Model’s Performance #AI #AIio #BigData #ML #NLU #Futureofwork http://ow.ly/6K7e30sCzOa

How to Improve Graphs to Empower Your Machine-Learning Model’s Performance #AI #AIio #BigData #ML #NLU #Futureofwork http://ow.ly/6K7e30sCzOa

🚀 Excited to share insights on Neural Network Activation Functions! 🧠✨ Understanding activation functions is crucial in the world of neural networks. They determine how neurons process data, influencing the network's ability to learn and make predictions. In my latest article on Medium, I break down four key activation functions - Threshold, Sigmoid, Rectifier (ReLU), and Hyperbolic Tangent. Each has its unique strengths and applications, playing a vital role in shaping the behavior of neural networks. 🔍 Dive into the world of activation functions and discover how they impact the performance of your neural networks. Whether you're a seasoned data scientist or just starting your AI journey, there's something valuable for everyone. 📖 Read the full article here: https://lnkd.in/gfFPcHM2 Let's empower our neural networks for better data processing! 💡🤖 #NeuralNetworks #ActivationFunctions #AI #MachineLearning #datascience

Question: Some researchers have argued that the quality of the text to generated images does not improve significantly after 20 inference steps, which means that the model does not benefit from further refinement or feedback. Does this also apply to text to text chat, where the model has to generate natural and engaging responses to user inputs? Is there a limit to how much a larger model can improve the performance of text to text chat, and is it worth the cost of training and deploying such a model? #ai #promptengineering #aichallenges https://lnkd.in/euxf7_pZ

🚀 Exciting news in the world of computer vision! Introducing PACE (Pose Annotations in Cluttered Environments), a groundbreaking benchmark designed to advance pose estimation methods in cluttered scenarios. With 54,945 frames, 257,673 annotations, and 300 videos, PACE covers 576 objects from 44 categories, offering a real-world challenge for state-of-the-art algorithms. This innovative benchmark aims to stimulate further advancements in the field of computer vision. Check out the details and access the code and data at https://ift.tt/dm82OpK. #ComputerVision #AI #MachineLearning #DataScience #Innovation #Technology #ResearchOpportunities