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

DECEMBER 18, 2023

YOLO’s architecture was a significant revolution in the real-time object detection space, surpassing its predecessor – the Region-based Convolutional Neural Network (R-CNN). The backbone is a pre-trained Convolutional Neural Network (CNN) that extracts low, medium, and high-level feature maps from an input image.

Computer Vision 52

Computer Vision Convolutional Neural Networks Neural Network Algorithm 52

Viso.ai

NOVEMBER 27, 2024

Multiple machine-learning algorithms are used for object detection, one of which is convolutional neural networks (CNNs). YOLOv1 The Original Before introducing YOLO object detection, researchers used convolutional neural network (CNN) based approaches like R-CNN and Fast R-CNN.

Explainability 52

Explainability Convolutional Neural Networks Neural Network Computer Vision 52

Viso.ai

OCTOBER 15, 2024

In the field of real-time object identification, YOLOv11 architecture is an advancement over its predecessor, the Region-based Convolutional Neural Network (R-CNN). Using an entire image as input, this single-pass approach with a single neural network predicts bounding boxes and class probabilities. Redmon, et al.

Computer Vision 52

Computer Vision Convolutional Neural Networks Neural Network Python 52

Viso.ai

FEBRUARY 27, 2024

Farhadi, signifying a step forward in the real-time object detection space, outperforming its predecessor – the Region-based Convolutional Neural Network (R-CNN). It is a single-pass algorithm having only one neural network to predict bounding boxes and class probabilities using a full image as input. Divvala, R.

Neural Network 52

Neural Network Computer Vision Convolutional Neural Networks Python 52

Lexalytics

APRIL 5, 2021

Around this time (early 2016), our management team realized that to maintain relevance as a company, we would need to be able to incorporate even more ML into our product. The CNN was a 6-layer neural net with 132 convolution kernels and (don’t laugh!) 90,575 trainable parameters, placing it in the small-feature regime.

Neural Network 52

Neural Network Convolutional Neural Networks Natural Language Processing BERT 52

Explosion

NOVEMBER 21, 2019

In 2016 we trained a sense2vec model on the 2015 portion of the Reddit comments corpus, leading to a useful library and one of our most popular demos. sense2vec reloaded: the updated library sense2vec is a Python package to load and query vectors of words and multi-word phrases based on part-of-speech tags and entity labels.

NLP 52

NLP Convolutional Neural Networks Neural Network Natural Language Processing 52