alsani-ipe
𝐈𝐧𝐝𝐮𝐬𝐭𝐫𝐢𝐚𝐥 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫 & 𝐀𝐈 𝐄𝐧𝐭𝐡𝐮𝐬𝐢𝐚𝐬𝐭|| Exploring the Boundaries of 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠, 𝐃𝐞𝐞𝐩 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠
https://alsani.me/Dhaka, Bangladesh
Pinned Repositories
alsani-ipe
Brain-Tumor-Classification-with-custom-Neural-Network
Brain Tumors are complex. There are a lot of abnormalities in the sizes and location of the brain tumor(s). This makes it really difficult for complete understanding of the nature of the tumor. Also, a professional Neurosurgeon is required for MRI analysis
Car-Brand-Prediction-s-by-Using-ResNet50-Model
ResNet-50 is a convolutional neural network architecture commonly used in deep learning for various computer vision tasks, such as image classification and object detection. It is part of the ResNet (Residual Network) family of architectures, which was introduced by Kaiming in 2015
Convolutional-Neural-Network-CNN-Implementation-
Welcome to the "Convolutional Neural Network Implementation" repository! 🧠📷 In this repository, we dive deep into the exciting world of Convolutional Neural Networks (CNNs), a powerful class of artificial neural networks designed to excel at tasks like image recognition, object detection, and image classification.
deeptest
Deep learning implementation
Gesture-Detection-using-OpenCV-python
To detect motion with OpenCV and Python, you can use the following steps: Capture the video stream using a camera or a video file. Convert each frame of the video stream to grayscale. Apply a background subtraction algorithm to detect the regions where motion is occurring.
Image-Preprocessing-Image-Transformation-OpenCV
Image preprocessing is a crucial step in image analysis and computer vision tasks. It involves various operations to prepare images for further analysis or feature extraction. OpenCV is a powerful library for image preprocessing in Python.
Image-Similarity-Index-SSIM-analysis-
In image processing, an image similarity index, also known as a similarity measure or similarity metric, is a numerical value that quantifies the degree of similarity or dissimilarity between two or more images.
Understanding-Activation-functions-in-Neural-Networks
Activation functions are functions used in a neural network to compute the weighted sum of inputs and biases, which is in turn used to decide whether a neuron can be activated or not.
X-ray-Image-Classification-using-Transfer-Learning
Our Python project aims to automate the classification of X-ray images by leveraging the capabilities of deep learning. This endeavor has the potential to bring significant benefits to both medical professionals and patients. Our objective is to develop a rapid and precise diagnostic tool for the identification of medical disorders.
alsani-ipe's Repositories
alsani-ipe/Understanding-Activation-functions-in-Neural-Networks
Activation functions are functions used in a neural network to compute the weighted sum of inputs and biases, which is in turn used to decide whether a neuron can be activated or not.
alsani-ipe/Brain-Tumor-Classification-with-custom-Neural-Network
Brain Tumors are complex. There are a lot of abnormalities in the sizes and location of the brain tumor(s). This makes it really difficult for complete understanding of the nature of the tumor. Also, a professional Neurosurgeon is required for MRI analysis
alsani-ipe/alsani-ipe
alsani-ipe/X-ray-Image-Classification-using-Transfer-Learning
Our Python project aims to automate the classification of X-ray images by leveraging the capabilities of deep learning. This endeavor has the potential to bring significant benefits to both medical professionals and patients. Our objective is to develop a rapid and precise diagnostic tool for the identification of medical disorders.
alsani-ipe/Car-Brand-Prediction-s-by-Using-ResNet50-Model
ResNet-50 is a convolutional neural network architecture commonly used in deep learning for various computer vision tasks, such as image classification and object detection. It is part of the ResNet (Residual Network) family of architectures, which was introduced by Kaiming in 2015
alsani-ipe/Convolutional-Neural-Network-CNN-Implementation-
Welcome to the "Convolutional Neural Network Implementation" repository! 🧠📷 In this repository, we dive deep into the exciting world of Convolutional Neural Networks (CNNs), a powerful class of artificial neural networks designed to excel at tasks like image recognition, object detection, and image classification.
alsani-ipe/deeptest
Deep learning implementation
alsani-ipe/Gesture-Detection-using-OpenCV-python
To detect motion with OpenCV and Python, you can use the following steps: Capture the video stream using a camera or a video file. Convert each frame of the video stream to grayscale. Apply a background subtraction algorithm to detect the regions where motion is occurring.
alsani-ipe/Image-Preprocessing-Image-Transformation-OpenCV
Image preprocessing is a crucial step in image analysis and computer vision tasks. It involves various operations to prepare images for further analysis or feature extraction. OpenCV is a powerful library for image preprocessing in Python.
alsani-ipe/Image-Similarity-Index-SSIM-analysis-
In image processing, an image similarity index, also known as a similarity measure or similarity metric, is a numerical value that quantifies the degree of similarity or dissimilarity between two or more images.
alsani-ipe/Introduction-Deep-Learning-with-Python
Deep learning is a type of machine learning and artificial intelligence (AI) that imitates the way humans gain certain types of knowledge. Deep learning models can be taught to perform classification tasks and recognize patterns in photos, text, audio and other various data.
alsani-ipe/Python-OpenCV-12
OpenCV (Open Source Computer Vision Library) is a popular open-source computer vision and machine learning software library. It provides various tools and functions that allow developers to perform a wide range of image and video processing tasks.
alsani-ipe/transformers
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
alsani-ipe/All-Resources-of-Artificial-Intelligence
This Repository contains all premium and free resources about Data science and Artificial intelligence fields.
alsani-ipe/alsani-ipe.github.io
alsani-ipe/darknet
YOLOv4 / Scaled-YOLOv4 / YOLO - Neural Networks for Object Detection (Windows and Linux version of Darknet )
alsani-ipe/Data-Preprocessing-Tools
This repository helps you by providing some amazing prepossing tools and python code.
alsani-ipe/Deep-Learning-pdf-books-Collections
alsani-ipe/GC10-DET-Metallic-Surface-Defect-Datasets
This is the GC10-DET datasets of the upcoming paper " Deep Metallic Surface Defect Detection: the New Benchmark and Detection Network" The images of 10 common Metallic Surface defects were collected, and their pixel level ground-truth were labeled.
alsani-ipe/Getting-Started-with-OpenCV
OpenCV (Open Source Computer Vision Library) is a popular open-source computer vision and machine learning software library. It provides various tools and functions that allow developers to perform a wide range of image and video processing tasks.
alsani-ipe/IDM
Internet Download Manager
alsani-ipe/Image-Edge-Detection-Convert-to-Blurr-Image-
Edge detection is a technique used in image processing to identify boundaries within an image. It's commonly used in computer vision and image analysis applications. There are several algorithms you can use for edge detection, such as the Canny edge detector, Sobel operator, and Prewitt operator.
alsani-ipe/Machine-Learning-pdf-Books-Collections
alsani-ipe/Scatter-plots-with-Plotly-Express
Plotly Express is the easy-to-use, high-level interface to Plotly, which operates on a variety of types of data and produces easy-to-style figures. The plotly.express module (usually imported as px) contains functions that can create entire figures at once, and is referred to as Plotly Express or PX.
alsani-ipe/Sunburst-Charts-Plotting-in-Python
Sunburst plots visualize hierarchical data spanning outwards radially from root to leaves. Similar to Icicle charts and Treemaps, the hierarchy is defined by labels (names for px.icicle) and parents attributes. The root starts from the center and children are added to the outer rings.
alsani-ipe/ultralytics
NEW - YOLOv8 🚀 in PyTorch > ONNX > OpenVINO > CoreML > TFLite
alsani-ipe/yolov5
YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite