Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and ...

By Atharva Agrawal Growing up in the Tiger Capital of India, Nagpur, a city surrounded by some of the country’s most eminent wildlife sanctuaries, including Pen ...

We will create a Deep Neural Network python from scratch. We are not going to use Tensorflow or any built-in model to write the code, but it's entirely from scratch in python. We will code Deep Neural ...

Introduction: Recent advances in artificial intelligence have transformed the way we analyze complex environmental data. However, high-dimensionality, spatiotemporal variability, and heterogeneous ...

Real-time object detection is a critical capability in computer vision, enabling systems to identify and localize objects instantly in dynamic environments. Recent advances leverage optimized ...

when i run the python train.py --logtostderr --train_dir=training/ --pipeline_config_path=training/faster_rcnn_inception_v2_pets.config..... (tf) D:\Anaconda\envs\tf ...

Abstract: Recently, on-device object detection has gained significant attention as it enables real-time visual data processing without the need for a connection to a remote server. However, deploying ...

When compiling Object Detection with Tensorflow model (as described here), it gives different compilation errors each time (I guess because of threaded compile). Also, debug and release builds give ...

Abstract: Object detection forms an important area of research where the efforts are still being put forth to improve the accuracy of detection. Several approaches have been made which also include ...