ARGUS: Vision-Centric Reasoning with Grounded Chain-of-Thought
Author(s): Yash Thube Originally published on Towards AI. Existing Multimodal LLMs, primarily driven by advancements in large language models (LLMs), often underperform when accurate visual perception and understanding of specific regions-of-interest (RoIs) are crucial for successful reasoning. Argus tackles this by proposing …
From Pixels to Understanding: A Better Way for AI to See
Author(s): Kaushik Rajan Originally published on Towards AI. How a new “denoising” technique is making on-device computer vision faster, smarter, and ready for your next app. Computer vision on mobile devices is a quiet miracle. It powers the face-unlock on your phone, …
“Building Vision Transformers from Scratch: A Comprehensive Guide”
Author(s): Ajay Kumar mahto Originally published on Towards AI. Building Vision Transformers from Scratch: A Comprehensive Guide A Vision Transformer (ViT) is a deep learning model architecture that applies the Transformer framework, originally designed for natural language processing (NLP), to computer vision …
From Pixels to Understanding: A Better Way for AI to See
Author(s): Kaushik Rajan Originally published on Towards AI. How a new “denoising” technique is making on-device computer vision faster, smarter, and ready for your next app. Computer vision on mobile devices is a quiet miracle. It powers the face-unlock on your phone, …
“Building Vision Transformers from Scratch: A Comprehensive Guide”
Author(s): Ajay Kumar mahto Originally published on Towards AI. Building Vision Transformers from Scratch: A Comprehensive Guide A Vision Transformer (ViT) is a deep learning model architecture that applies the Transformer framework, originally designed for natural language processing (NLP), to computer vision …
Harness DINOv2 Embeddings for Accurate Image Classification
Author(s): Lihi Gur Arie, PhD Originally published on Towards AI. If you don’t have a paid Medium account, you can read for free here. Introduction Training a high-performing image classifier typically requires large amounts of labeled data. But what if you could …
BLIP-2 : How Transformers Learn to ‘See’ and Understand Images
Author(s): Arnavbhatt Originally published on Towards AI. This is a step-by-step walkthrough of how an image moves through BLIP-2: from raw pixels → frozen Vision Transformer (ViT) → Q-Former → final query representations that get fed into a language model. You’ll understand …
DINOv3: Why Vision Foundation Models Deserve The Same Excitement as LLMs
Author(s): Qaisar Tanvir | AVP – AI/ML Architecture and MLOps Originally published on Towards AI. Header Image Every day the feed hypes the next big LLM. That makes sense — language unlocked new product workflows. But the release of DINOv3 is a …
Autonomous Horizons: How AI is Steering the Next Generation of Transportation
Author(s): Yuval Mehta Originally published on Towards AI. Photo by Gabriele Malaspina on Unsplash Artificial intelligence (AI) has advanced from a theoretical concept to a revolutionary force in a variety of industries, with the automobile sector at the vanguard. AI is transforming …
Improved PyTorch Models in Minutes with Perforated Backpropagation — Step-by-Step Guide
Author(s): Dr. Rorry Brenner Originally published on Towards AI. Perforated Backpropagation is an optimization technique which leverages a new type of artificial neuron, bringing a long overdue update to the current model based on 1943 neuroscience. The new neuron instantiates the concept …
Exploring MobileCLIP: A lightweight solution for Zero-Shot Image Classification
Author(s): Antonio Guerra Originally published on Towards AI. Exploring MobileCLIP: A lightweight solution for Zero-Shot Image Classification An example of a Zero-Shot Image Classification Model identifying a cat in an image with class probabilities for “cat”, “dog”, and “bird” (source: https://huggingface.co/tasks/zero-shot-image-classification) Introduction …
NN#11 — Neural Networks Decoded: Concepts Over Code
Author(s): RSD Studio.ai Originally published on Towards AI. Limitations of ANNs: Move to Convolutional Neural Networks This member-only story is on us. Upgrade to access all of Medium. The journey from traditional neural networks to convolutional architectures wasn’t just a technical evolution …
Built a Computer Vision-Powered App Using Gemini in Under 15 Minutes — No Training Required
Author(s): Areeb Adnan Khan Originally published on Towards AI. This member-only story is on us. Upgrade to access all of Medium. Machine Learning Algorithm Illustration: Source Getty Images Computer Vision is booming, and with the rise of multi modal AI models, it’s …
Important Computer Vision Papers for the Week from 27/01 to 01/02
Author(s): Youssef Hosni Originally published on Towards AI. Stay Updated with Recent Computer Vision Research This member-only story is on us. Upgrade to access all of Medium. Every week, researchers from top research labs, companies, and universities publish exciting breakthroughs in diffusion …
Creating Beyond the Frame: A Practical Guide to Image Outpainting with Stable Diffusion
Author(s): Vincent Liu Originally published on Towards AI. This member-only story is on us. Upgrade to access all of Medium. Figure 1. Example of image outpainting. Source: Photo by Jon Tyson on Unsplash, modified by author. In a world where artificial intelligence …
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