PaddleOCR: GPU Integration and Troubleshooting
Author(s): Areeb Adnan Khan Originally published on Towards AI. This member-only story is on us. Upgrade to access all of Medium. Source: Hugging Face Demo Optical Character Recognition (OCR) is a game-changer for tasks like text extraction from images, document processing, and …
The Top 10 AI Research Papers of 2024: Key Takeaways and How You Can Apply Them
Author(s): Prashant Kalepu Originally published on Towards AI. The Top 10 AI Research Papers of 2024: Key Takeaways and How You Can Apply Them Photo by Maxim Tolchinskiy on Unsplash As the curtains draw on 2024, it’s time to reflect on the …
Real-Time Object Detection using YoloV7 on Google Colab
Author(s): Adijsad Originally published on Towards AI. Want to test your video using Yolov7 and Google Colab? Learn how to make real-time object detection using your videos in this tutorial This member-only story is on us. Upgrade to access all of Medium. …
![[AI/ML] Spatial Transformer Networks (STN) — Overview, Challenges And Proposed Improvements](https://i0.wp.com/miro.medium.com/v2/resize:fit:700/1*zsztycoAQskDzCeEJISPWQ.png?w=700&resize=700,338&ssl=1 "[AI/ML] Spatial Transformer Networks (STN) — Overview, Challenges And Proposed Improvements")
[AI/ML] Spatial Transformer Networks (STN) — Overview, Challenges And Proposed Improvements
Author(s): Shashwat Gupta Originally published on Towards AI. The modification of dynamic spatial information through spatial transformer networks (STNs) allows models to handle transformations such as scaling and rotation for subsequent tasks. They enhance recognition accuracy by enabling models to focus on …
Faster Knowledge Distillation Using Uncertainty-Aware Mixup
Author(s): Tata Ganesh Originally published on Towards AI. Photo by Jaredd Craig on Unsplash In this article, we will review the paper titled “Computation-Efficient Knowledge Distillation via Uncertainty-Aware Mixup” [1], which aims to reduce the computational cost associated with distilling the knowledge …
Enhance OCR with Llama 3.2-Vision using Ollama
Author(s): Tapan Babbar Originally published on Towards AI. Source: Image by the author. Earlier this month, I dipped my toes into book cover recognition, combining YOLOv10, EasyOCR, and Llama 3 into a seamless workflow. The result? I was confidently extracting titles and …
Building Trustworthy AI: Interpretability in Vision and Linguistic Models
Author(s): Rohan Vij Originally published on Towards AI. Building Trustworthy AI: Interpretability in Vision and Linguistic Models Photo by Arteum.ro on Unsplash | What thoughts lie behind that eye? The rise of large artificial intelligence (AI) models trained using self-supervised deep learning …
OCR with AI and LLM — A New Era of Intelligent Document Processing
Author(s): Tarun Singh Originally published on Towards AI. This member-only story is on us. Upgrade to access all of Medium. What if you could effortlessly extract critical data from complex PDFs or scanned documents with the power of AI? Imagine transforming hours …
Vision Embedding Comparison for Image Similarity Search: EfficientNet vs. ViT vs. VINO vs. CLIP vs. BLIP2
Author(s): Yuki Shizuya Originally published on Towards AI. Photo by gilber franco on Unsplash Recently, I needed to research image similarity search. I wonder if there are any differences among embeddings based on the architecture training methods. However, few blogs compare embeddings …
🤙Sign Language Detection using YOLO11
Author(s): Asad iqbal Originally published on Towards AI. This isn’t just an incremental upgrade. YOLO11 represents a significant leap forward, promising to redefine what’s possible in AI-powered vision This member-only story is on us. Upgrade to access all of Medium. YOLO11 is …
Creating a Panorama using OpenCV
Author(s): Gokulraj Varatharajan Originally published on Towards AI. This member-only story is on us. Upgrade to access all of Medium. What is a Panorama? A panorama is a feature available on most smartphones that stitches together consecutive images to form a single, …
A Comprehensive Guide to Loss Functions🔥: The Backbone of Machine Learning
Author(s): Asad iqbal Originally published on Towards AI. Our detailed guide will help you understand the importance of loss functions in machine learning. It will help you distinguish between loss and cost functions, the different kinds, such as MSE and MAE, and …
Qdrant Plays Mario Kart 64
Author(s): Miguel Otero Pedrido Originally published on Towards AI. An Image Search application using Vector Databases This member-only story is on us. Upgrade to access all of Medium. Source: Image by Ravi Palwe on Unsplash In this article, I’ll introduce you to …
Are Diffusion Models Really Superior to GANs on Image Super Resolution?
Author(s): Valerii Startsev Originally published on Towards AI. Photo by Kasia Derenda on Unsplash Introduction For over half a decade (2014–2020), generative adversarial networks (GANs) dominated generative modeling, including image super-resolution (ISR). The introduced adversarial training framework (involving a competing generator and …
Optical Character Recognition (OCR) with CNN-LSTM Attention Seq2Seq
Author(s): Tan Pengshi Alvin Originally published on Towards AI. Photo by Towfiqu barbhuiya on Unsplash In previous articles, we have covered a lot, and exhaustively, on Convolutional Neural Networks (CNNs) and their various Deep Learning tasks. CNNs are particularly good at learning …
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