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

John Snow Labs

MAY 23, 2023

The first VQA dataset was DAQUAR, released in 2014. VQA frameworks combine two Deep Learning architectures to deliver the final answer: Convolutional Neural Networks (CNN) for image recognition and Recurrent Neural Network (RNN) (and its special variant Long Short Term Memory networks or LSTM) for NLP processing.

Natural Language Processing 40

Natural Language Processing Deep Learning NLP Convolutional Neural Networks 40

deepsense.ai

MAY 7, 2023

We also explained the building blocks of Stable Diffusion and highlighted why its release last year was such a groundbreaking achievement. Source: [ 2 ] In the previous post, we explained the importance of Stable Diffusion [ 3 ]. 2022 [link] Going deeper with convolutions , Szegedy et al. But don’t worry!

Neural Network 52

Neural Network Convolutional Neural Networks Explainability Deep Learning 52

Mlearning.ai

JUNE 8, 2023

Vector Embeddings for Developers: The Basics | Pinecone Used geometry concept to explain what is vector, and how raw data is transformed to embedding using embedding model. Pinecone Used a picture of phrase vector to explain vector embedding. What are Vector Embeddings? using its Spectrogram ).

Machine Learning 52

Machine Learning BERT Neural Network OpenAI 52

Marek Rei

NOVEMBER 12, 2019

Evaluations on CoNLL 2014 and JFLEG show a considerable improvement over previous best results of neural models, making this work comparable to state-of-the art on error correction. link] Constructing a system for NLI that explains its decisions by pointing to the most relevant parts of the input. Cambridge, Amazon. NAACL 2019.

Machine Learning 52

Machine Learning NLP Neural Network BERT 52

Heartbeat

APRIL 18, 2023

The VGG model The VGG ( Visual Geometry Group ) model is a deep convolutional neural network architecture for image recognition tasks. It was introduced in 2014 by a group of researchers (A. Zisserman and K. Simonyan) from the University of Oxford. Sometimes simple solutions offer the best results.

Convolutional Neural Networks 52

Convolutional Neural Networks Deep Learning Neural Network Machine Learning 52

ML Review

MAY 3, 2018

22] On a high level in the architecture, the frames extracted from a video sequence are processed in small sets within a Convolutional Neural Network (CNN), [23] while an LSTM-variant runs on the CNN output sequentially to generate output characters. An Intuitive Explanation of Convolutional Neural Networks.

Neural Network 52

Neural Network Computer Vision Deep Learning Convolutional Neural Networks 52