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GradCAM and its Implementation in PyTorch
Computer Vision Deep Learning PyTorch

GradCAM and its Implementation in PyTorch

Nikhil Tomar1st March 20251st March 2025
Deep learning models, especially convolutional neural networks (CNNs), often function as black boxes, making it difficult to interpret their decision-making processes. Gradient-weighted Class Activation Mapping (GradCAM) is a powerful technique...
GradCAM with TensorFlow: Interpreting Neural Networks with Class Activation Maps
Blog TensorFlow

GradCAM with TensorFlow: Interpreting Neural Networks with Class Activation Maps

Nikhil Tomar26th February 2025
Deep learning models, particularly convolutional neural networks (CNNs), are widely used for image classification, object detection, and various computer vision tasks. However, these models are often referred to as "black...
[Paper Summary] EMCAD: Efficient Multi-scale Convolutional Attention Decoding for Medical Image Segmentation
Computer Vision Deep Learning

[Paper Summary] EMCAD: Efficient Multi-scale Convolutional Attention Decoding for Medical Image Segmentation

Nikhil Tomar14th September 202414th September 2024
This post will analyze the research paper "EMCAD: Efficient Multi-scale Convolutional Attention Decoding for Medical Image Segmentation." We will discuss the problems with existing medical image segmentation methods and how...
What is Image Captioning?
Computer Vision Deep Learning

What is Image Captioning?

Nikhil Tomar29th August 2024
In recent years, the field of artificial intelligence (AI) has seen remarkable advancements, particularly in how machines can understand and describe visual content. One of the fascinating developments in this...
Read Video Files Using OpenCV Python
OpenCV Python

Read Video Files Using OpenCV Python

Nikhil Tomar25th August 202425th August 2024
Reading and processing video files is a common task in computer vision, and OpenCV makes it easy to work with video data. In this article, we'll go through the process...
Image Masking with OpenCV AddWeighted
Computer Vision OpenCV

Image Masking with OpenCV AddWeighted

Nikhil Tomar13th August 202415th August 2024
Image masking is a powerful technique used in image processing to manipulate specific parts of an image while leaving other areas untouched. This is particularly useful in applications like object...
ResUNet++ Implementation in TensorFlow
Computer Vision Deep Learning TensorFlow

ResUNet++ Implementation in TensorFlow

Nikhil Tomar20th April 202420th April 2024
In this article, we will study the ResUNet++ architecture and implement it using the TensorFlow framework. ResUNet++ is a medical image segmentation architecture built upon the ResUNet architecture. It takes...
UNet 3+ Implementation in TensorFlow
Computer Vision Deep Learning TensorFlow

UNet 3+ Implementation in TensorFlow

Nikhil Tomar11th April 202414th September 2024
In this article, we will implement the UNet 3+ architecture using TensorFlow. UNet 3+ extends the classic UNet and UNet++ architecture incorporating full skip connections. We will delve into each block...
Skip Connection in Image Segmentation: UNet, UNet++ and UNet 3+
Computer Vision Deep Learning

Skip Connection in Image Segmentation: UNet, UNet++ and UNet 3+

Nikhil Tomar7th February 2024
Image segmentation, a fundamental task in computer vision, involves partitioning an image into multiple segments to simplify its representation. One of the critical advancements in image segmentation architectures is the...
[Paper Summary] UNet 3+: A Full-Scale Connected UNET For Medical Image Segmentation
Computer Vision Deep Learning

[Paper Summary] UNet 3+: A Full-Scale Connected UNET For Medical Image Segmentation

Nikhil Tomar5th February 20245th February 2024
In medical image analysis, accurately identifying and outlining organs is vital for clinical applications such as diagnosis and treatment planning. The UNet architecture, a widely favoured choice for these tasks,...

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