PyImageSearch

NOVEMBER 13, 2023

You’ll typically find IoU and mAP used to evaluate the performance of HOG + Linear SVM detectors ( Dalal and Triggs, 2005 ), Convolutional Neural Network methods, such as Faster R-CNN ( Girshick et al., 2015 ; Redmon and Farhad, 2016 ), and others. 2015 ), SSD ( Fei-Fei et al., 2015 ; He et al., MobileNets ).

Convolutional Neural Networks 119

Convolutional Neural Networks Neural Network Computer Vision Deep Learning 119

Viso.ai

MAY 7, 2024

However, GoogLeNet demonstrated by using the inception module that depth and width in a neural network could be increased without exploding computations. GooLeNet – source Historical Context The concept of Convolutional Neural Networks ( CNNs ) isn’t new.

Explainability 52

Explainability Neural Network Convolutional Neural Networks Deep Learning 52

Viso.ai

MARCH 11, 2024

YOLO in 2015 became the first significant model capable of object detection with a single pass of the network. The previous approaches relied on Region-based Convolutional Neural Network (RCNN) and sliding window techniques. The post YOLOX Explained: Features, Architecture and Applications appeared first on viso.ai.

Explainability 52

Explainability Convolutional Neural Networks Neural Network Computer Vision 52

Explosion

NOVEMBER 9, 2016

Over the last six months, a powerful new neural network playbook has come together for Natural Language Processing. This post explains the components of this new approach, and shows how they’re put together in two recent systems. 2016) introduce an attention mechanism that takes a single matrix and outputs a single vector.

Deep Learning 52

Deep Learning NLP Convolutional Neural Networks Neural Network 52

ML Review

JUNE 4, 2018

These ideas also move in step with the explainability of results. If language grounding is achieved, then the network tells me how a decision was reached. In image captioning a network is not only required to classify objects, but instead to describe objects (including people and things) and their relations in a given image.

Neural Network 52

Neural Network Convolutional Neural Networks Computer Vision Deep Learning 52

Viso.ai

JULY 17, 2024

Output from Neural Style Transfer – source Neural Style Transfer Explained Neural Style Transfer follows a simple process that involves: Three images, the image from which the style is copied, the content image, and a starting image that is just random noise. Johnson et al. What is Perceptual Loss?

Convolutional Neural Networks 52

Convolutional Neural Networks Neural Network Computer Vision Deep Learning 52

Snorkel AI

MARCH 1, 2023

This can make it challenging for businesses to explain or justify their decisions to customers or regulators. Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks Radford et al. Microsoft Microsoft launched its Language Understanding Intelligent Service in 2016.

BERT 83

BERT Natural Language Processing Large Language Models Neural Network 83