Engineering AI Agents
BOOK
Foundations
Training Deep Networks
Perception
State Estimation
Large Language Models
Multimodal Reasoning
Planning
Markov Decision Processes
Reinforcement Learning
COURSES
Introduction to AI
AI for Robotics
Deep Learning for Computer Vision
DATA MINING - BEING PORTED
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Perception
Perception
Seeing and understanding the world.
Author
Pantelis Monogioudis
Introduction to Convolutional Neural Networks
CNN Layers
CNN Example Architectures
Using convnets with small datasets
Visualizing what convnets learn
Feature Extraction via Residual Networks
Introduction to Scene Understanding
Object Detection
Object Detection and Semantic Segmentation Metrics
Region-CNN (RCNN) Object Detection
Fast and Faster RCNN Object Detection
Object Detection & Semantic Segmentation Workshop
Mask R-CNN Semantic Segmentation
Mask R-CNN Demo
Mask R-CNN - Inspect Training Data
Mask R-CNN - Inspect Trained Model
Mask R-CNN - Inspect Weights of a Trained Model
Detectron2 Beginner’s Tutorial
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CNN Example Architectures
This is a very high level view of practical structures of CNNs before the advent of more innovative architectures such as ResNets.
CNN Layers
In the convolutional layer the first operation a 3D image with its two spatial dimensions and its third dimension due to the primary colors, typically Red Green and Blue is…
Fast and Faster RCNN Object Detection
Fast-RCNN is the second generation RCNN that aimed to accelerate RCNN. Apart from the complex training of RCNN, its inference involved a forward pass for each of the 2000…
Feature Extraction via Residual Networks
In the figure below we plot the top-5 classification error as a function of depth in CNN architectures. Notice the big jump due to the introduction of the ResNet architecture.
Introduction to Convolutional Neural Networks
(content:cnn-intro)= # Introduction to Convolutional Neural Networks
Introduction to Scene Understanding
In the previous chapters we have treated the perception subsystem mainly from starting the first principles that govern supervised learning to the deep learning…
Mask R-CNN Semantic Segmentation
The semantic segmentation approach described in this section is Mask R-CNN based on this paper paper.
Mask R-CNN
is an extension of Faster R-CNN that adds a mask head to the…
Object Detection
In the introductory section, we have seen examples of what object detection is. In this section we will treat the detection
pipeline
itself, summarized below:
Object Detection & Semantic Segmentation Workshop
Object Detection and Semantic Segmentation Metrics
NOTE: The following example is based on here and its corresponding implementation
Region-CNN (RCNN) Object Detection
We can think about the detection problem as a classification problem of
all possible portions
(windows/masks) of the input image since an object can be located at any…
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