Marktechpost

SEPTEMBER 24, 2024

The success of this model reflects a broader shift in computer vision towards machine learning approaches that leverage large datasets and computational power. Previously, researchers doubted that neural networks could solve complex visual tasks without hand-designed systems. by the next-best model.

Convolutional Neural Networks 62

Convolutional Neural Networks Neural Network Computer Vision Deep Learning 62

NYU Center for Data Science

SEPTEMBER 11, 2024

Meet CDS Senior Research Scientist Shirley Ho , a distinguished astrophysicist and machine learning expert who brings a wealth of experience and innovative research to our community. She led the first effort to accelerate astrophysical simulations with deep learning. Ho’s contributions have not gone unnoticed.

Convolutional Neural Networks 74

Convolutional Neural Networks Neural Network Deep Learning Data Science 74

Unite.AI

OCTOBER 10, 2024

A new research paper from Canada has proposed a framework that deliberately introduces JPEG compression into the training scheme of a neural network, and manages to obtain better results – and better resistance to adversarial attacks. Architectures used were EfficientFormer-L1 ; ResNet ; VGG ; MobileNet ; and ShuffleNet.

Neural Network 162

Neural Network Convolutional Neural Networks Deep Learning Machine Learning 162

Viso.ai

FEBRUARY 11, 2024

It brings the development of deep learning models for image classification , object detection , and other computer vision tasks. 2011 – A good ILSVRC image classification error rate is 25%. 2012 – A deep convolutional neural net called AlexNet achieves a 16% error rate. parameters and achieved 84.5%

Convolutional Neural Networks 52

Convolutional Neural Networks Neural Network Computer Vision 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

The traditional machine learning (ML) paradigm involves training models on extensive labeled datasets. 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.

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. What’s Next?

Computer Vision 52

Computer Vision Convolutional Neural Networks Deep Learning Neural Network 52