In the article, we will go through the paper Attention U-Net: Learning Where to Look for the Pancreas. It was written by Ozan Oktay et. al in the year 2018 at the MIDL (Medical Imaging with Deep Learning) conference. The Attention UNET introduces a novel Attention Gate that enables the UNET architecture to focus on…
Logistic Regression is a popular machine-learning algorithm that is used for classification tasks. In this tutorial, we will learn how to implement Logistic Regression in TensorFlow 2.0 using the tf.keras.Model API. We will also learn how to split our data into training, validation, and testing sets in order to train and evaluate our model. Related…
In today’s tutorial, we will be looking at the DeepLabV3+ (ResNet50) architecture implementation in TensorFlow using Keras high-level API. Within this architecture, ResNet50 would be used as the encoder, which is pre-trained on the ImageNet classification dataset. We will begin with the overall architectural understanding of the DeepLabV3+ and ResNet50. Furthermore, we will understand the…
Image segmentation is an important area of computer vision that involves dividing an image into multiple segments, each of which corresponds to a different object. Background removal is one of the crucial applications of image segmentation that involves separating foreground objects from the background. This can be useful in various domains, such as video and…
Bounding boxes play a critical role in the object detection process, a fundamental task in computer vision. Object detection entails the identification and precise localization of objects within an image. These bounding boxes serve to define the position of an object within the image, allowing for the creation of a box that encapsulates it. What…
File transfer has been one of many tasks in socket programming. In this article, we will discuss how to transfer large files using TCP sockets in Python. TCP (Transmission Control Protocol) is a reliable and efficient data transmission protocol commonly used for file transfers over the internet. With Python’s in-built socket library, it is easy…
MultiResUNET is an architecture developed by Nabil Ibtehaz et al. for the purpose of multimodal biomedical image segmentation at the Bangladesh University of Engineering and Technology. It is an improvement over the existing UNET architecture as it outperforms U-Net on the five biomedical datasets. The high performance of MultiResUNET is due to the introduction of…
Intersection over Union (IoU) is a popular evaluation metric used in the field of computer vision and object detection. It is used to calculate the overlap between two bounding boxes and is used to evaluate the accuracy of object detection algorithms. IoU is a value between 0 and 1 that represents the overlap between the…
In recent years, advances in machine learning and deep learning techniques have revolutionized the field of computer vision. With the help of these techniques, we can now detect and identify objects in real time with remarkable accuracy. One of the most popular tasks in computer vision is human face detection, which plays a crucial role…
![[Paper Summary] Class-Aware Adversarial Transformers for Medical Image Segmentation](https://idiotdeveloper.com/wp-content/uploads/2023/02/castformer-architecture-250x250.webp)
Transformer-based models have shown remarkable progress in the field of medical image segmentation. However, the existing methods still suffer from limitations such as loss of information and inaccurate segmentation label maps. In this article, we will discuss a new type of adversarial transformer, the Class-Aware Adversarial Transformer (CASTformer), which overcomes these limitations and provides better…
Nikhil Kumar Tomar
AI Researcher and a part-time blogger and YouTuber. Most of my research is focused medical imaging.
