There are 4 repositories under cnn-for-visual-recognition topic.
real-time fire detection in video imagery using a convolutional neural network (deep learning) - from our ICIP 2018 paper (Dunnings / Breckon) + ICMLA 2019 paper (Samarth / Bhowmik / Breckon)
Projects from the Deep Learning Specialization from deeplearning.ai provided by Coursera
This deep learning application can detect Facial Keypoints (15 unique points). They mark important areas of the face - the eyes, corners of the mouth, the nose, etc.
Implementation of Logistic Regression, MLP, CNN, RNN & LSTM from scratch in python. Training of deep learning models for image classification, object detection, and sequence processing (including transformers implementation) in TensorFlow.
Using DUCK-Net for polyp image segmentation. ( Nature Scientific Reports 2023 )
This repositary contain all my exercises and projects of Udacity Computer Vision Nanodegree Program
Pre-trained VGG-Net Model for image classification using tensorflow
Genre Classification using Convolutional Neural Networks
TensorFlow Lite object detection example for Raspberry Pi Zero
Computer Vision Case Study in image recognition to classify an image to a binary class, based on Convolutional Neural Networks (CNN), with TensorFlow and Keras in Python, to identify from an image whether it is an image of a dog or cat. (Includes: Data, Case Study Paper, Code)
Used Convolutional Deep Neural nets to extract features from the image
Google MediaPipe Javascript Demos (including live demos)
Segmenting WSIs using Deep Convolutional Neural Networks
For this project, we are going to detect rice leaf disease using CNN and serve the result via messenger chatbot. We will also implement this to an independent Android app.
The project aims at building a machine learning model that will be able to classify the various hand gestures used for fingerspelling in sign language. In this user independent model, classification machine learning algorithms are trained using a set of image data and testing is done. Various machine learning algorithms are applied on the datasets, including Convolutional Neural Network (CNN).
C++ and Python implementation of a automatic system for pedestrian detection at night using far infrared visual information based on convolutional neural networks.
Implement SS-CNN "Dubey et al. Deep Learning the City ECCV16"
Resume Parsing app to extract information using AI
This is "ready from box" face recognition app, based on Mediapipe, dlib and face_recognition modules.
ConvNet (CNN) implementation to classify x-ray medical images
VHDL implementation of a customizable CNN
Semantic neural network to realize pixel-wise classification of 2D nano-material using Matlab
Project for detecting Autism and Dyslexia using ML. A POC for the KPMG Ideation Challenge, 2021.
Implementing autonomous capabilities with a convolutional neural network (CNN) and machine vision on a modified RC car, using a Raspberry Pi and an Arduino, written in Python and C, and utilising the TensorFlow and OpenCV libraries
We present the Automatic Helmet Detection System, a CNN model trained on image dataset that can detect motorbikes as well as riders wearing helmets.
Detecting empty space for parking lot car using cnn model
A deep learning CNN model with 9 layers used for image classification of food ingredients and recipes. This recipe recommendation bot will recommend recipes based on image or text user input. Deployed in the Telegram app under ASU_Chef_Bot.
CMU Foreground/Background Similarity Server from DARPA MEMEX
Implementation of CNN (Convolutional neural network) from scratch
Applied YOLO model trained on COCO dataset to detect obstacles and Lane-Net model trained on tusimple.ai dataset for end-to-end lane detection. • Improved usability and response time by 50% using the combination and optimization of legacy codes of algorithms in assisted driving.
The repository implements the a simple Convolutional Neural Network (CNN) from scratch for image classification. I experimented with it on MNIST digits and COIL object dataset.
My solutions to CS231N (Convolutional Neural Networks for Visual Recognition, Spring 2017)