Home
About
Search
Portfolio
Books
Subscribe
AI Blog
☰ Menu
🌓 Light|dark mode
Computer Vision: Object Detection
Posted by
Mukesh
Jun 30, 2019
What is the object detection problem?
What is Intersection Over Union?
How do you compare performance of multiple detectors?
What are some of the detectors?
What are sliding window detectors?
What are some challenges with sliding window detectors?
What is a Histogram of Gradients detector?
What is Viola-Jones face detector?
What are attentional cascades in neural networks?
What is region-based convolutional neural network?
Why from R-CNN to Fast R-CNN?
What is Faster R-CNN?
What is Region-based fully-convolutional network?
What is You Only Look Once (YOLO)?
How does 3D Object Detection work?
Read more
Deep Learning With TF 2.0: 04.00- Numerical Computation
Posted by
Mukesh
Jun 23, 2019
04.00 - Numerical Computation
04.01 - Overflow and Underflow
04.02 - Poor Conditioning
04.03 - Gradient-Based Optimization
04.04 - Constrained Optimization
04.05 - Example: Linear Least Squares
Read more
Computer Vision: Face Recognition
Posted by
Mukesh
Jun 16, 2019
What is face recognition?
What is face verification evaluation protocol?
How is face verification solved?
What is a triplet loss training scheme?
What is the re-identification problem?
What are some challenges in person re-identification?
What are some approaches to person re-identification?
What is facial key-point regression?
What are some approaches to key-point regression tasks?
How to build a statistical model of facial shape?
Read more
Computer Vision: Image Retrieval
Posted by
Mukesh
Jun 9, 2019
What is content based image retrieval?
How do you define image similarity?
How do you evaluate a image retrieval method?
Computing semantic image embeddings using convolutional neural networks
What are come of the first content based image retrieval systems?
How does HOG descriptor work?
What is a GIST descriptor?
How can we use convolutional neural networks for image retrieval?
What is a compact neural descriptor?
How does vector quantization for image retrieval work?
Hashing for image quantization
How does Locality Sensitive Hashing works?
What are the strengths and weaknesses of K-means and LSH?
GIST IS for indexing large image collections.
Read more
Deep Learning With TF 2.0: 03.00- Probability and Information Theory
Posted by
Mukesh
Jun 2, 2019
03.00 - Probability and Information Theory
03.01 - Why Probability?
03.02 - Random Variables
03.03 - Probability Distributions
03.04 - Marginal Probability
03.05 - Conditional Probability
03.06 - The Chain Rule of Conditional Probabilities
03.07 - Independence and Conditional Independence
03.08 - Expectation, Variance and Covariance
03.09 - Common Probability Distributions
03.10 - Useful Properties of Common Functions
03.11 - Bayes’ Rule
03.12 - Technical Details of Continuous Variables
03.13 - Information Theory
03.14 - Structured Probabilistic Models
Read more
Previous
1
2
Next
Google Search
Posts Search
Search
Blog Categories
AI (1)
DeepLearningWithTF (4)
ComputerVision (5)
Recent posts
30 Jun 2019
Computer Vision: Object Detection
23 Jun 2019
Deep Learning With TF 2.0: 04.00- Numerical Computation
16 Jun 2019
Computer Vision: Face Recognition
09 Jun 2019
Computer Vision: Image Retrieval
02 Jun 2019
Deep Learning With TF 2.0: 03.00- Probability and Information Theory
Tags
Image Processing (1)
Linear Algebra (1)
CNN (4)
Probability (1)
Optimization (1)
This blog is maintained by
MUKESH
Get in touch with me via:
Get Notified on New Posts.
*
indicates required
Email Address
*
First Name
Last Name