Word2Vec: A Study of Embeddings in NLP

Faster Django Queries With Materialized Views

Introduction to the Bag-of-Words (BoW) Model

Semantic vs. Instance vs. Panoptic Segmentation

Introduction to Natural Language Processing (NLP)

Extending image with new pixels using OpenCV

The main goal of this post is to show how to work with the NumPy array for OpenCV images. I will use a simple case to present how to extend the image with new pixels.

PyCharm 2022.1.3 Is Out!

Training the YOLOv5 Object Detector on a Custom Dataset

Enhanced Super-Resolution Generative Adversarial Networks (ESRGAN)

Super-Resolution Generative Adversarial Networks (SRGAN)

PyCharm 2022.1.2

Attending to Channels Using Keras and TensorFlow

Spatial Transformer Networks Using TensorFlow

PyCharm 2022.2 EAP is open!

Achieving Optimal Speed and Accuracy in Object Detection (YOLOv4)

Table of Contents Achieving Optimal Speed and Accuracy in Object Detection (YOLOv4)

PyCharm 2022.1.1 Is Now Available

An Incremental Improvement with Darknet-53 and Multi-Scale Predictions (YOLOv3)

Mean Average Precision (mAP) Using the COCO Evaluator

Hypothesis GraphQL

Generate arbitrary queries matching your GraphQL schema, and use them to verify your backend implementation.

A Better, Faster, and Stronger Object Detector (YOLOv2)

Detection frameworks have become increasingly fast and accurate, as seen in our last post on YOLOv1; however, most detection methods are still constrained to a small set of objects like 20 classes in PASCAL VOC and 80 classes in Microsoft COCO.