Unlocking Computer Vision with Deep Learning

Apr 20, 2025

0 likes | 4 Vues

Discover how deep learning is unlocking new dimensions in computer vision. From real-time object detection to facial recognition and autonomous vehicles, learn how neural networks are teaching machines to interpret visual data like never before. Explore the tech behind smart vision systems and the future of AI-powered perception.

Share Presentation

Embed Code

Link

scholarsco

Télécharger la présentation

Unlocking Computer Vision with Deep Learning

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

Computer Vision since Deep Learning

Computer Vision since Deep Learning. Larry Strickland. Chief Product Officer lstrickland@dkl.com. What is deep learning?. Well…. …. that is really not well defined. Possible sources Large (Artificial) Neural Networks Multiple Layer Neural Networks Larger data sets (deep pool of data)

557 views • 29 slides

Deep learning

Deep learning. Harrison Littler and Peter Jones Monday 15 th April 2013. Do any of these statements match your experience? . Reflecting on our current practice. Aim of this session:

1.09k views • 17 slides

Deep Learning

Deep Learning. Early Work Why Deep Learning Stacked Auto Encoders Deep Belief Networks. Deep Learning Overview. Train networks with many layers (vs. shallow nets with just a couple of layers) Multiple layers work to build an improved feature space

790 views • 34 slides

Deep Learning

Deep Learning. Why?. Source: Huang et al., Communications ACM 01/2014.

611 views • 39 slides

Computer Vision Machine Learning Features

Computer Vision Machine Learning Features. Presented By Dr. Keith Haynes. Outline. Introduction Appearance-Based Approach Features Classifiers Face Detection Walkthrough Questions. Computer Vision.

1.05k views • 63 slides

Deep Learning

Deep Learning. Bing-Chen Tsai 1/21. outline. Neural networks Graphical model Belief nets Boltzmann machine DBN Reference. Neural networks. Supervised learning The training data consists of input information with their corresponding output information. Unsupervised learning

701 views • 32 slides

Hierarchical Models of Vision: Machine Learning/Computer Vision

Hierarchical Models of Vision: Machine Learning/Computer Vision. Alan Yuille UCLA: Dept. Statistics Joint App. Computer Science, Psychiatry, Psychology Dept . Brain and Cognitive Engineering, Korea University. Structure of Talk.

917 views • 65 slides

Scalable Learning in Computer Vision

Scalable Learning in Computer Vision. Adam Coates Honglak Lee Rajat Raina Andrew Y. Ng Stanford University. Computer Vision is Hard. Introduction. One reason for difficulty: small datasets. Introduction. But the world is complex.

500 views • 29 slides

Deep Learning for Vision

Deep Learning for Vision. Adam Coates Stanford University (Visiting Scholar: Indiana University, Bloomington). What do we want ML to do?. Given image, predict complex high-level patterns:. “Cat”. Object recognition. Detection. Segmentation. [Martin et al., 2001]. How is ML done?.

1.07k views • 78 slides

Deep Learning

Deep Learning. Supervised Learning. Works well if we have right features Domains like computer vision, audio processing, and natural language processing requires feature engineering. Feature Engineering is tough job Manually finding right features does not scale well. What?.

584 views • 23 slides

Deep Learning

Deep Learning. Yann Le Cun The Courant Institute of Mathematical Sciences New York University http://yann.lecun.com. The Challenges of Machine Learning. How can we use learning to progress towards AI? Can we find learning methods that scale?

1.18k views • 69 slides

(Infinitely) Deep Learning in Vision

(Infinitely) Deep Learning in Vision. Max Welling (UCI) collaborators: Ian Porteous (UCI) Evgeniy Bart UCI/Caltech) Pietro Perona (Caltech). Outline. Nonparametric Bayesian Taxonomy models for object categorization Hierarchical representations from networks of HDPs. Motivation.

307 views • 18 slides

Deep learning with multiplicative interactions

Deep learning with multiplicative interactions. Geoffrey Hinton Canadian Institute for Advanced Research & Department of Computer Science University of Toronto. Overview. Background: How to learn a multilayer generative model of unlabeled data using a Restricted Boltzmann Machine

764 views • 60 slides

Deep learning

And Deep Networks for Natural Language Processing. Deep learning. Overview of the Talk. Overview of Deep Learning Justification Properties of Deep Learning Neural Networks 101 Brief History of Deep Learning Implementation Details RBM’s and DBN’s Auto-Encoders Deep Learning for NLP

1.52k views • 78 slides

DEEP Vision

DEEP D river E ducation & E nlightenment P rogram A Non-profit Organization Saving Lives Through Education. DEEP Vision. To create a new generation of road users who are orderly and courteous in using the transportation facilities in an orderly and courteous manner. DEEP Goal.

611 views • 42 slides

Global Deep Learning in Computer Vision Market– Industry Trends and Forecast to 2025

The Global Deep Learning in Computer Vision Market accounted for USD 7.8 billion in 2017 and is projected to grow at a CAGR of 55.7% the forecast period of 2018 to 2025. The upcoming market report contains data for historic years 2016, the base year of calculation is 2017 and the forecast period is 2018 to 2025.

68 views • 5 slides

Deep Learning in Machine Vision Market

52 views • 3 slides

Revolutionizing Healthcare with Computer Vision A Deep Dive into the Future

Computer vision in healthcare is transforming the sector by enabling better diagnostics, personalized treatment, and improved patient outcomes. This article explores the applications of computer vision in healthcare, also artificial intelligence for healthcare management and highlights its potential to revolutionize the industry. For more details, please visit our website: https://www.assertai.com/

149 views • 6 slides

Deep Learning in Machine Vision Market

Deep learning in machine vision market is expected to gain market growth in the forecast period of 2022 to 2029. Data Bridge Market Research analyses that the market is growing with the CAGR of 12.5% in the forecast period of 2022 to 2029 and expected to reach USD 9,262.40 million by 2029.

18 views • 6 slides

Deep Learning with Python- 4achievers

We offer a Deep Learning with Python course at 4Achievers. Learn advanced concepts and practical applications of artificial intelligence and neural networks. You will gain hands-on experience through projects and exercises designed to deepen your knowledge. Python in Deep Learning certification will validate your skills for potential employers, regardless of whether you are a beginner or advanced programmer. Start your career in deep learning with us and take the first step. For more info: https://bit.ly/4ahVyEC Contact No.: 91-8010805667 Address: A-77, sector-2 Near sector-15 Metro station

27 views • 5 slides

Unlocking the Power of Deep Learning with TensorFlow 2.0

Visit us for more courses: http://www.squadcenter.com/itplacements

23 views • 6 slides

More Related