Visual vocabulary advances novel object captioning by breaking free of paired sentence-image training data in vision and language pretraining. Discover how this method helps set new state of the art on the nocaps benchmark and bests CIDEr scores of humans.
Get up to date on one of the most promising Deep Learning technologies there is right now
Tesla's Autopilot system relies on vision rather than LIDAR, which means it can be tricked by messages on billboards and projections created by hackers.
Nvidia tops MLPerf records again, consortium adds benchmarks to measure mobile
With PyTorch and TensorFlow incorporated, the authors hope to gain a wider audience.
Self-Organizing Maps for Dimension Reduction, Data Visualization, and Clustering
Recognition of Oil Storage Tanks in satellite images using the Yolov3 object detection model from scratch using Tensorflow 2.x and…
A brief introduction to CenterNet (Objects as Points), TTFNet and their implementation in TensorFlow 2.2+.
Standard, Recurrent, Convolutional, & Autoencoder Networks
To researchers’ surprise, deep learning vision algorithms often fail at classifying images because they mostly take cues from textures, not shapes.
Less than 50 days after the release YOLOv4, YOLOv5 improves accessibility for realtime object detection. June 29, YOLOv5 has released the first official version of the repository. We wrote a new deep dive on YOLOv5. June 12, 8:08 AM CDT Update: In response to to community…
Deep Dive into DNNs, CNNs, and RNNs Dropout Methods for Regularization, Monte Carlo Uncertainty, and Model Compression
Smooth python codes to augment your image datasets by yourself.
Part one of a three part deep dive into the curve neuron family.
How I Generated New Images from Random Data using DCGAN
Let’s dive deep into the architectural details of all the different EfficientNet Models and find out how they differ from each other.
Webcam background change is not limited to Zoom now, I just did it in the browser with tensorflow.js body-pix model
State of the art modeling with image data augmentation and management
Computer vision is evolving on a daily basis. Popular computer vision techniques such as image classification and object detection have been used extensively to solve a lot of computer vision…
BERT, XLNet, RoBERTa, etc.
A component by component breakdown analysis
We reached out to further members of the AI community for their recommendations of papers which everyone should be reading! All of the cited papers are free to access and cover a range of topics from some incredible minds.
This post collates research on the advancements of Natural Language Processing (NLP) over the years.
An elegant method to group predictions without labeling
We’re releasing an analysis showing that since 2012 the amount of compute needed to train a neural net to the same performance on ImageNet classification has been decreasing by a factor of 2 every 16 months. Compared to 2012, it now takes 44 times less compute to train a neural…
The stores aren’t dead yet
Making the design process faster and more efficient by generating 3D objects from natural language descriptions.
Explore and manipulate the COCO image dataset for Semantic Image Segmentation with PyCoco, Tensorflow Keras Python libraries
Create a data generator and train your model on the COCO image dataset for Semantic Image Segmentation with PyCoco, Tensorflow Keras py
Usage of the new model, with examples and Colab Notebook.
An Overview Of popular python libraries for Natural Language Processing
In this article we’ll serve the Tensorflow Object Detection API with Flask, Dockerize the Application and deploy it on Kubernetes.
Paper: https://arxiv.org/abs/1910.07454 Blog Post: http://www.offconvex.org/2020/04/24/ExpLR1/ "We report experiments that state-of-the-art networks…
The new tools shows the potential of data visualizations for understanding features in a neural network.
Introduction on Stacked Auto-encoder and Technical Walk-through on Model Creation using Pytorch
We review the cost of training large-scale language models, and the drivers of these costs. The intended audience includes engineers and scientists budgeting their model-training experiments, as...
Bringing Neural Architecture into Recommendations
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AI looks well-suited for short-term weather forecasts
New approach to meta-reinforcement learning minimizes the need for costly interactions with the environment.
Extracting topics is a good unsupervised data-mining technique to discover the underlying relationships between texts. There are many…
We’ll show you how to quickly build a Streamlit app to synthesize celebrity faces using GANs, Tensorflow, and st.cache.
It’s theoretically possible to become invisible to cameras. But can it catch on?
Reading between the lines of the latest advancements in GML.
Google published an article “Understanding searches better than ever before” and positioned BERT as one of the most important updates to…
Statistics, Algorithms, Deep Learning, NLP, & Data Organization