Turn your knowledge branch into a knowledge tree with these (free) Udemy courses!
We are looking for complete solution like colossyan or yepic but not a SAAS model. Only apply if you have worked with similar projects, rest details we can discuss on chat. Timeline 2 months for first prototype.
To have a deep learning network that accepts 4D low-resolution images and produces 4D high-resolution images. Project Objectives: 1- Get the 4D low-resolution images through running a degradation model on the ground-truth 4D images dataset by estimating various blur kernels as well as real noise distributions. Most current approaches rely on paired low and high-resolution images to train the network in a fully supervised manner. However, such image pairs are not available in real-world applications. Thus, the aim here is instead to learn super-resolution from unpaired data and without any restricting assumptions on the input image formation. 2- Use GAN (Generative Adversarial Network) framework to perform the up-sampling within the network using transposed convolutions. The aim here is f...
This is the dataset having ECG recordings. I want you to create 10s strips for big recordings. Each stip should be labeled as per the bits in it. Like whether it is AFIB, Normal or Other class
Hello, Looking for AII expert to help us in crypto price prediction using multiple model, we are looking for short term prediction 5 to 30 min with very hight accuracy, 80 to 95%. only developer with experience in this area please.
I have thousands of pdf which contains map image. I want to make tool which extract only map part as a image file from pdf. Finally when I select pdf folder , the tool needs to generate images from pdf to a certain folder. Please check screenshot. NOTE: Result image should only include map part. No other sections or borders are allowed. Budget:500
A project on Data Augmentation in NLP where we can use an ensemble approach using 3 - 4 text data augmentation techniques and later using some similarity filter like universal sentence encoder, we can choose the best augmentation technique for the dataset, and also to use different types of datasets too, for comparision.
Hey! There, I am pursuing MTech and as part of the academic curriculum, I have to publish a research paper in Scopus Indexed Journal. So the Problem is like my guide suggested writing a paper on Data Augmentation in NLP where we can use an ensemble approach using 3 - 4 text data augmentation techniques and later using some similarity filter we can choose the best augmentation technique for the dataset, and also to use different types of datasets too, for comparison. I couldn't find how to start that's why I landed here and found it helpful in this. I've attached a Visual concept of that.
An algorithm for trading crypto currencies has been implemented. Your job is to change the variables to improve the output and incorporate how to add other algorithms to the solution. We will provide you with the exact requirements that we are looking for. Points to Note: 1. We are currently using the Q learning algorithm. We have tried PPO and A2C but there are certain problems with it. 2. We have data from about 12 crypto coins, the main ones primarily include Bitcoin and ethereum. 3. The data ranges from 2013 upto 2020. There is no consensus currently on how much training should be used for the bot (trading agent in our case ) to mature. We have run the algo at about 200 epochs and that is sufficient to mature it. 4. The code is purely in Python In summary: the goal is to imp...
I will provide JSON files with the extracted features (I will extract these from the pcap files). The features will be from malware and non-malware traffic, so the idea is to detect and classify the malware and non-malware samples. The feature selection should be done two ways: Manual and automated and we should be able to clearly identify the features that are being used and which features work well, and which features do not work well. As there are multiple datasets, we should be able to identify the features that work well across all the datasets. There are different versions of the malware, so we need to clearly identify which features work well across all these malware versions. The manual feature selection should allow me to select which features I want to use for the classificatio...
i have a dataset i want to resize all the images to be in same size (224x224x3 )
Use Python to build AI models to play Dirt 5. You’ll need to train a model which can play autonomously! Machine Learning should be used to play the game "Dirt 5." There should be 10 - 15 mins of continuous input where the car will try to stay on the tracks and go around the tracks. The goal is not to win the game but to simulate someone playing the game. If the car hits a barrier or another car or gets off track of the course, it correct itself and get back on track. OpenCV, TensorFlow and Keras should be used. No other deep learning languages. The requirements listed are all of the requirements. Other than that I am open. I believe the game is free for PC on steam. You can look at how the game is played on YouTube for more details: 1 Example: Here is an example video ...
The code is here: The person should have good knowledge in understanding and writing code. I will need it to be done within 3 days.
Add categories car, bike, bus, heavy truck, light truck, 3 wheeler, lcv, tractor in the given code and create a new dataset according to my videos.
We need to implement a Computer Vision (CV) system that will receive images and/or video streaming from CCTV systems. We want a tested pre-trained algorithm as YOLOv4, YOLO9000, OpenCV with the standard prediction of 1,000 classes/labels (as trained on ImageNET). Algorithm to be used is suggested to be OpenSource as: YOLOv4, YOLO9000, OpenCV, etc. we can consider other options. The solution must be implemented on a VPS (Virtual Private Server) or similar server that will be provided by us, but the requirements of the server must be specified by you. ==PLEASE READ MORE ON DOCUMENT ATTACHED==
Analysis of scraped URL data (HTML, screenshots, json) and building models to identify the impersonated domains (malicious and non-malicious). The tasks will be simple if you have worked previously on ML or computer vision projects and might need support for about 2 months. Need to be efficient iin writing clean code and completing the project end-to-end.
We have a gcms data in Sql format We have created around 100 samples and have that data stored in Sql server Now we want to use AI to predict composition of unknown samples using the data we have? Let me known if you think you can do that
Hello there, This is a cool project to do. Find and configure an open-source project that will 'toonify' photos on the local Linux machine. In the end, you want to have a command that will provide 2 pictures and style.jpg. The neural network should convert to and be similar to '' Write documentation of how you did it. Some additional information: You can't use API from other sites. The project should render the image on the local machine. If you have a working solution - just write to me.
Data we gather from different IOT devices placed in cloud, while upload and download we need protect data with respect to privacy and security For providing privacy and security we use facial recognition and digital sign for security for facial recognition we use ML Deep learning and neural networks So i need the peer who has knowledge on ML DNN Network security Cloud
I am interested to work on a long-term research project where I need to conduct a depth study to find a gap or modify method (Approach) in the area of Neural Network optimization for the edge devices. I am planning toward research and publication. Please contact me if interested.
I'm a professional programmer; however, my area of expertise is specifically software engineering and architecture in backend web applications. I'm really interested in tinkering on a project with deep learning and computer vision. I have a pool table and would like to be able to watch shots I've taken and figure out why I missed. I'd like guidance on how to learn for myself the intricacies of this problem: use deep learning and computer vision to automatically clip a video starting with getting down into the shot and end it when the balls come to a rest. I'd like to hire you to spend time with me discussing the problem, and maybe screenshare different tools or resources. I'd like to also hire you to help create the initial things. My expertise is in PHP a...