Marktechpost

SEPTEMBER 24, 2024

Further, pre-training on the ImageNet Fall 2011 dataset, followed by fine-tuning, reduced the error to 15.3%. In the ILSVRC-2012 competition, the model reached a top-5 validation error rate of 18.2%, which improved to 16.4% when predictions from five CNNs were averaged.

Convolutional Neural Networks 64

Convolutional Neural Networks Neural Network Computer Vision Deep Learning 64

NYU Center for Data Science

SEPTEMBER 11, 2024

Dr. Ho’s innovative approach has led to several groundbreaking achievements: Her team at Carnegie Mellon University was the first to apply 3D convolutional neural networks in astrophysics. “I look forward to collaborating with fellow researchers and students to explore new frontiers in foundation models for science.”

Convolutional Neural Networks 54

Convolutional Neural Networks Neural Network Deep Learning Data Science 54

Viso.ai

FEBRUARY 11, 2024

2011 – A good ILSVRC image classification error rate is 25%. 2012 – A deep convolutional neural net called AlexNet achieves a 16% error rate. 2015 – Microsoft researchers report that their Convolutional Neural Networks (CNNs) exceed human ability in pure ILSVRC tasks.

Convolutional Neural Networks 52

Convolutional Neural Networks Computer Vision Neural Network Deep Learning 52

Viso.ai

MARCH 12, 2024

Today’s boom in computer vision (CV) started at the beginning of the 21 st century with the breakthrough of deep learning models and convolutional neural networks (CNN). They found that removing any convolutional layer (each containing less than 1% of the model’s parameters) resulted in inferior performance.

Computer Vision 52

Computer Vision Convolutional Neural Networks Neural Network Deep Learning 52

Viso.ai

JANUARY 16, 2024

Matching Networks: The algorithm computes embeddings using a support set, and one-shot learns by classifying the query data sample based on which support set embedding is closest to the query embedding – source. The embedding functions can be convolutional neural networks (CNNs). The CLIP model for ZSL shows 64.3%

Neural Network 52

Neural Network Computer Vision Convolutional Neural Networks Algorithm 52

Viso.ai

MAY 31, 2024

VOC2011 PASCAL VOC challenge took a big step forward in 2011 with VOC2011. Deep Learning Approaches Convolutional Neural Networks (CNNs) : The CNNs including AlexNet , VGGNet , and ResNet helped solve computer vision problems by learning the hierarchal features directly from the Pascal VOC data.

Computer Vision 52

Computer Vision Convolutional Neural Networks Deep Learning Neural Network 52

Lexalytics

APRIL 5, 2021

A paper that exemplifies the Classifier Cage Match era is LeCun et al [ 109 ], which pits support vector machines (SVMs), k-nearest neighbor (KNN) classifiers, and convolution neural networks (CNNs) against each other to recognize images from the NORB database. 90,575 trainable parameters, placing it in the small-feature regime.

Neural Network 52

Neural Network Convolutional Neural Networks Natural Language Processing BERT 52