• 9 min read
What is Contrastive Learning? A guide.
Contrastive learning focuses on comparing data points to improve model performance across various tasks.
Blog
Petru Potrimba
Machine Learning Engineer @ Google
Latest Posts by Petru Potrimba
• 8 min read
What is Dimensionality Reduction? A Guide.
Explore the core techniques of dimensionality reduction and examine applications.
• 7 min read
What is 4M? Apple's Massively Multimodal Masked Modeling
4M: Massively Multimodal Masked Modeling, released by Apple in 2024, is a leap forward in the field of multimodal machine learning. This model, building upon the growing capabilities of large language models, addresses critical challenges in vision models which have traditionally been highly specialized and limited to a single modality
• 7 min read
What is YOLOv10? An Architecture Deep Dive.
Learn about the main architectural components of YOLOv10 that contribute to the model's state-of-the-art speed and accuracy.
• 6 min read
What is New in YOLOv9? An Architecture Deep Dive.
Learn what YOLOv9 is and what architectural features allow YOLOv9 to achieve strong performance on object detection and segmentation tasks.
• 7 min read
What is Semantic Segmentation?
In this guide, learn what semantic segmentation is, how it works, and what model architectures are commonly used for semantic segmentation.
• 5 min read
What is YOLOv3? An Introductory Guide.
Learn what YOLOv3 is and the notable architectural eatures of this model.
• 10 min read
What is Visual Question Answering (VQA)?
Learn what Visual Question Answering (VQA) is, how it works, and explore models commonly used for VQA.
• 4 min read
What is ResNet-50?
Learn what ResNet-50 is, how it works, and how ResNet models of various levels perform on uimage classification.
• 8 min read
What is Few-Shot Learning?
In this blog post, we discuss what few-shot learning is, architectural approaches for implementing few-shot learning, and specific implementations of few-shot learning techniques.
• 7 min read
What is Optical Character Recognition (OCR)?
Learn what Optical Character Recognition is, what problems can be solved with OCR, and explore the approaches used by OCR algorithms to identify characters.
• 6 min read
What is Keypoint Detection?
In this guide, we discuss what keypoint detection is, common architectures used for keypoint detection, and the high-level steps to build a keypoint detection model.
• 6 min read
What is DETR (Detection Transformers)?
In this guide, we discuss what DETR is, how it works, the strengths and disadvantages of DETR, and how DETR performs.
• 6 min read
What is R-CNN?
In this guide, you will learn what R-CNN is, how it works, the advantages and disadvantages of the R-CNN architecture, and how R-CNN performs.
• 7 min read
What is Mask2Former? The Ultimate Guide.
In this guide, we discuss what Mask2Former is, how the model works, and how Mask2Former performs on various computer vision tasks.
• 6 min read
What is EfficientNet? The Ultimate Guide.
In this guide, we discuss what EfficientNet is, how it works, and how the compound scaling method is used in the model.
• 7 min read
What is Mask R-CNN? The Ultimate Guide.
In this guide, we discuss what Mask R-CNN is, how it works, where the model performs well, and what limitations exist with the model.
• 6 min read
What is OneFormer? A Deep Dive.
In this guide, we discuss what OneFormer is, how it works, and the performance of OneFormer benchmarked against three datasets.
• 9 min read
What is Hyperparameter Tuning? A Deep Dive.
This guide explores what hyperparameter tuning is, common hyperparameters in computer vision, methods of tuning hyperparameters, and more.
• 6 min read
What is DETIC? A Deep Dive.
In this guide, we discuss what Detic is, how it works, notable characteristics of Detic, and the limitations associated with the model.
• 15 min read
What is Dataset Distillation? A Deep Dive.
In this guide, we discuss what dataset distillation is, the methods through which a dataset can be distilled, and the applications of distilled datasets in computer vision.
• 13 min read
What is Knowledge Distillation? A Deep Dive.
In this guide, we discuss what knowledge distillation is, how it works, why knowledge distillation is useful, and the different methods of distilling knowledge from one model to another.
• 12 min read
Multimodal Models and Computer Vision: A Deep Dive
In this post, we discuss what multimodals are, how they work, and their impact on solving computer vision problems.
• 16 min read
What is a Convolutional Neural Network?
In this guide, we discuss what a Convolutional Neural Network (CNN) is, how they work, and discuss various different applications of CNNs in computer vision models.
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