Convolution jobs

...Udacity's simulator? Yes What is the main issue you're encountering with the model? The car does not start How have you been validating the performance of the model? validated the model's performance by monitoring its accuracy metric. I am currently working on a project that involves building and refining a Convolution Neural Network (CNN) model for a self-driving car. This project demonstrate basic self driving car model using udacity car driving simulator. In this project I built a Convolution Neural Network model to predict the steering angle for a virtual car in the simulator running at a constant speed. Despite successful model configuration and established bidirectional communication between the Trained Model & The Udacity Car Driving Simulator, ...

I am urgently in need of an expert to assist me with a set of complex electrical circuit problems. Your task would be to: - Solve higher order ODE circuit problems - Assist with convolution problems - Tackle Laplace transfer issues The successful accomplishment of this project will result in: - Finding the transfer function - Analyzing the frequency response - Solving for the circuit variables This project requires a great understanding of electrical engineering principles, particularly, higher order ODE, convolution problems, and Laplace transfer. Proficiency in complex problem-solving under limited time conditions is an added advantage. I need this job completed ASAP. If this sounds like the kind of project that you'd excel at, please get in touch.

I am on the mission to boost my sales. Your experience is the key factor I am looking for. Your repertoire should reflect your experience with similar projects where you have delivered noticeable growth in sales. Skills & Experience: - Experience with sales enhancement projects. - Demonstrated convolution of innovative strategies that have led to increasing revenue streams. - Ability to analyze and forecast sales trends, and leverage this knowledge for future growth. Please bid only if your past experiences align well with these requirements. I am not just looking for someone to complete a project, but for a partner who can understand the ins and outs of increasing sales, and reflect the same in the work.

I need a developer experienced in deep learning and Python to create a new project incorporating both elements. The task involves: - Developing a deep learning graph convolutional neural network model that can predict the natural calamities like earthquake and flood - Building a Python application using this model You may opt for either a pre-existing GCN model or develop one from scratch. Proficiency in Python programming, deep learning and experience with the GCN model are essential. Open-mindedness towards different methodologies, creativity and analytical abilities will be appreciated.

...design engineer to create a 2D convolution hardware implementation for an image processing application. The goal is to achieve reduced computational area, power, and time without compromising performance. **Core Requirements** - Implement 4x4 matrix and 2x2 kernel convolution. - Employ kogge stone adder for efficiency. - Integrate vedic multiplier for rapid multiplication. - Ensure system operates with integer value precision. - Target design is for an FPGA using Verilog or VHDL. **Ideal Skills** - Proficiency in FPGA programming. - Strong background in digital arithmetic circuits. - Experience with kogge stone adders and vedic multipliers. - Knowledge of image processing techniques. - Use of Shifting , multiplication and addition in performing 2d convolution - Fl...

I'm seeking a proficient Verilog developer to implement a 2D convolution for the following image processing applications: edge detection and object recognition. • Core Requirements: - An extensive understanding of 2D Convolution and its application in edge detection and object recognition - Strong proficiency in Verilog programming language • Device specifications: - The 2D convolution algorithm needs to be coded specifically for an ASIC/FPGA device. Prior experience with designing for this platform is essential. This project demands precision, an in-depth understanding of image processing and excellent problem-solving skills. A proficiency in Verilog can significantly boost the effectiveness of the development process. Hence, expertise in Ve...

...mathematically that will show: Spatial Input Operator: • spatial_input_operator(longitude, latitude, categorical_data) as illustrated in the figure: • Description: This operator takes in spatial components (longitude and latitude) along with categorical data and prepares the input for the CNN model. Spatial Convolution Operator: • spatial_convolution_operator is the ( modified operator that combine long & lat with Categorical sets): • Description: This operator performs spatial convolution on the input data applying convolutional operations to capture spatial patterns + Categorical data. Spatial Pooling Operator: • spatial_pooling_operator from(convolved_data, pool_size, pooling_type): • Description: This operator applies spatial poolin...

...mathematically that will show: Spatial Input Operator: • spatial_input_operator(longitude, latitude, categorical_data) as illustrated in the figure: • Description: This operator takes in spatial components (longitude and latitude) along with categorical data and prepares the input for the CNN model. Spatial Convolution Operator: • spatial_convolution_operator is the ( modified operator that combine long & lat with Categorical sets): • Description: This operator performs spatial convolution on the input data applying convolutional operations to capture spatial patterns + Categorical data. Spatial Pooling Operator: • spatial_pooling_operator from(convolved_data, pool_size, pooling_type): • Description: This operator applies spatial poolin...

I want to make a air canvas, where a user can write on the screen using hand gestures, the project should also have a virtual keyboard. The project should be made using mnist, emnist datasets, deep learning algorithms like cnn, ensemble, hybrid models. The output should also include convolution matrix, and other details as well. The project should be made as a website.

I am looking for a developer who can develop my project, which involves node classification using graph convolution neural networks using chest x-ray images. Deadline: The project must be completed within 1 month. Dataset: I have a specific dataset that should be used for this project. Expected Accuracy: I expect the model to have an accuracy of more than 90%. Ideal Skills and Experience: - Strong knowledge and experience in node classification - Proficiency in graph convolution neural networks - Expertise in working with chest x-ray images - Ability to work within tight deadlines

I am looking for a MATLAB expert to assist me with building a wireless communication link for my Master's project. The project requires the use of LDPC encoder, Convolution encoder, and the modulation schemes QAM and M-APSK. Requirements: - LDPC encoder with a code rate of 1/2, 1/3, 2/13 - Preferred modulation scheme: Either QAM or M-APSK - Testing different values for M, such as M=8, M=16, M=32, M=64 - Simulink implementation Ideal Skills and Experience: - Proficiency in MATLAB - Experience with LDPC encoder and Convolution encoder - Knowledge of QAM and M-APSK modulation schemes - Familiarity with Simulink If you are an expert in MATLAB and wireless communication, please bid on this project.

I am looking for a skilled freelancer who can assist me with my Thesis work on "Bacterial classification using depthwise convolution CNN". The project requires coding in Python and the use of a specific dataset that I already have. Skills and experience required: - Proficiency in Python programming language - Strong understanding of depthwise convolutional neural networks (CNN) - Experience with image classification and machine learning algorithms - Knowledge of bacterial classification techniques The ideal freelancer should be able to complete the project within a timeframe of less than 1 month.

...am looking for a freelancer to develop a Semi-Supervised Multiscale Dynamic Graph Convolution Network for Hyperspectral Image Classification. The project requires the following: - Desired accuracy for the classification task: Above 95% - Availability of labeled training data for the classification task - Development of the network using Python programming language Ideal skills and experience: - Strong knowledge and experience in developing graph convolution networks - Proficiency in Python programming language and relevant libraries/frameworks for deep learning - Familiarity with hyperspectral image classification techniques - Ability to handle semi-supervised learning and multiscale dynamic graph convolution - Strong problem-solving skills and attention to detai...

I have a machine learning/deep learning project that I need help with. The goal of the project is part segmentation of the 3D objects with Graph convolution networks, and I have labeled data available for training. It is kind of Academic work but , I need help in programming part .Meeting after every part of work finished is necessary ,,explaination also important . I'm expecting a better level of accuracy from the model that is developed to solve the problem within baseline . If you have the skills and expertise to complete this machine learning project successfully, please get in touch with me. I look forward to discussing it further. My budget is up to 1000$.

I have a code which raises some issues in achieving the best accuracy and outcome using Graph convolution netwrks

___ Computer science task EEG simulation I am seeking assistance with the signal processing aspect of an EEG simulation project. Digital signal processing including common denoising techniques (ICA), filtering, resampling, and convolution. The goal of this task is to denoise an EEG dataset acquired during a simultaneous EEG-fMRI experiment, extract some frequency-domain measures from the denoised EEG signal, and correlate with fMRI image (which is a 4d image, each voxel is a time series). The end-result will be whole-brain correlation maps showing which brain areas correlate best with EEG. Skills and Experience: - Strong background in signal processing, specifically in EEG data analysis - Proficiency in Python programming language - Experience with EEG simulation and modeling ...

Project Title: Computer Sci...in signal processing, specifically in EEG data analysis - Proficiency in Python programming language - Experience with EEG simulation and modeling - Familiarity with relevant libraries and tools in Python for signal processing - Ability to work within a 1-2 week timeframe to complete the task Digital signal processing including common denoising techniques (ICA), filtering, resampling, and convolution. The goal of this assignment is to denoise an EEG dataset acquired during a simultaneous EEG-fMRI experiment, extract some frequency-domain measures from the denoised EEG signal, and correlate with fMRI image (which is a 4d image, each voxel is a time series). The end-result will be whole-brain correlation maps showing which brain areas correlate best ...

Hi Usama Z., Detection and Verification System: This system should first detect human faces using a laptop/USB camera and then verify detected faces Mobile App: Create a simple IOS mobile app that should notify users about authorized and unauthorized persons. Required-Clear project explanation, Block diagrams. Implementation steps(Incl. Code), Me...system should first detect human faces using a laptop/USB camera and then verify detected faces Mobile App: Create a simple IOS mobile app that should notify users about authorized and unauthorized persons. Required-Clear project explanation, Block diagrams. Implementation steps(Incl. Code), Methodologies used and potential challenges faced during the project. Technology and Language: Convolution neural network and python

I am looking for a skilled TensorFlow developer who can help me...generation. I will be providing the dataset, so no need to worry about that. The ideal candidate should have experience with GANs and deep learning in TensorFlow. The generated images should be of low resolution, less than 512x512. If you have experience with image generation using GANs in TensorFlow, I'd love to hear from you. I require three models: - DCGAN model and code (Convolution based) - Cycle GAN model and code (Convolution based) - Vision transformer GANs model and code For all three evaluation table and FID (Fréchet Inception Distance) for image quality evaluation Dataset: You can ask me for any missing details in your bid I'll update it.

I am looking for a highly accurate target tracking system that can be used to track small objects such as birds ,trees and other drones from drone captured video. The system should be able to function in varied environmental conditions such as rain and fog. Ideal Skills and Experience: - Experience in computer vision and object tracki...be able to function in varied environmental conditions such as rain and fog. Ideal Skills and Experience: - Experience in computer vision and object tracking - Proficiency in machine learning and deep learning - Knowledge of image processing techniques - Familiarity with drones and drone captured video - Ability to work with varied environmental conditions Comparison of : Efficient Convolution Operators for Tracking 2. Norfair algorithm

...Normalization before every activation • Changing the SGD to adam optimizer At test time, a Dropout layer with a dropout probability α will: • Multiply the input tensor by α. • Drop neurons from the input with probability α. • Power normalizes the input tensor by α. • None of the above. If your input to the convolutional layer is 32 × 32 × 16, how many parameters are there in a single 1 × 1 convolution filter, including bias? • 2 • 17 • 1025 • 1 Which methods can be used to prevent overfitting? • Changing scheduler • Changing batch size • L2 regularization • Dropout A (32 × 32 × 3) image is passed through a convolutional layer with 32 filters, each of size (3 ...

python machine learning engineer who knows colab, convolution Need to finish the project within this weekend Happy bidding

Notes and help for signal, image and optical processing including - sampling and aliasing - spatial filtering - sinusoids - phase - FT theorems and properties - convolution and correlation - optical computing

this research has 3 objectives based on GCN(graph convolution neural networks).Sample research papers are attching in the full implementation along with alogrithms and all other parameters as described in the sample of the details can be discussed.

Please anyone has expertise in GCN and done projects, need some help.

implement TransUnet on NSLC radiomic dataset for the classification of nsclc cancer U-Net has dominated image segmentation tasks, especially in the field of medical imaging. Among most of the hitherto proposed U-Nets, Convolution Neural Networks (CNN) are widely used as their underlying structures.

I need a short theoretical back ground about machine learning including the following points: 1- Explanation of Machine learning 2- Types of machine learning algorithms : Supervised , unsupervised and and reinforced leaning 3- Neural networks 4- Convolutional neural networks including what is a convolution 5- Generative models 6- Back propagation The following conditions need to be met for the text to be accepted: 1- minimum 10 pages, the more the better 2- If any photo is used a citation is neccessary 3- If i upload the document to turn it in for plagiarism check it must not exceed 2 % 4- All text must be extracted from journal papers NOT FROM WEBSITES and Every text has to be cited where it was taken from

Need a report written for analysis of a given signal to obtain and plot Fourier transform using MATLAB/Octave/SCILAB. Will need MATLAB code using time domain convolution, frequency domain multiplication and inverse Fourier transform. Further details will be shared with the selected freelancer. Need it done in 48 hours after the project is awarded. Freelancer with the most decent price quote will be preferred.

The code in this repository is for python <3.0 and does not work properly. PyQt4 is used which is outdated. replace with PyQT5 or 6 And some other issues. I need you to update the code to work as it is described in the repository. Price is 15CAD. there is very little room to negotiate. deadline is flexible.

The code in this repository is for python <3.0 and does not work properly. PyQt4 is used which is outdated. replace with PyQT5 or 6 And some other issues. I need you to update the code to work as it is described in the repository. Price is 15CAD. there is very little room to negotiate. deadline is flexible.

Description is as attached 1-LaplaceFocus Measure: In order to detect regions of higher contrast the Laplace operator can be applied. Using the standard Laplace operator yields no response of the filter when fxx =-fyy . The squared second derivation should be used instead of this. For the discreet model the self convolution of the Sobel Operator is applied. In order to increase the robustness the summation of the responses of the two filter masks (horizontal and vertical) in a local window is calculated as the Laplace focus measure F ML. Notice please here it is on 2D and I need it on 3D So this formel misses the z-komponent. 2-Mean Method Focus Measure: If the image is becoming sharper the variance Of the grey values Of that Scene is getting higher. The ratio of the mean grey...

I need a simple bespoke git project - nothing fancy. Just email the code to me in a word doc and a PDF of the output. Something easy, simple, Use real-world data. Please clearly note the source of data collection, and ensure you are using real-world data. Should show: Understanding of deep learning - Know the mathematical foundation and structure of neural networks - Know convolution networks (convnet) and its application to computer vision - Understand recurrent neural networks (RNN) and its application to text analysis and sequence data - Understand deep-learning models for time series data. It doesn't need to be super big or fancy.

we study the problem of how to improve KIE ability by automatically making full use of the textual and visual features n We introduce the improved graph learning module into the model to refine the graph structure on the complex documents given visually rich context. n This study provides a new perspective on structural information extraction from documents

my objective is to apply medical image classification by applying graph convolution networks pre-trained to the deep learning model. Further details I can explain in person when I get some coder who is willing to help me.

use Maximally Stable Extremal Regions (MSER) for detecting text candidates from the enhanced images. We then introduce Cloud of Line Distribution (COLD) features, which capture the distribution of pixels of text candidates in the polar domain. The extracted features are sent to a Convolution Neural Network (CNN) to correct the bounding boxes for arbitrarily oriented text lines by removing false positives. Experiments are conducted on a dataset of low light images to evaluate the proposed enhancement step. In addition, experimental results on a variety of standard benchmark datasets, namely, ICDAR 2013, ICDAR 2015 and ICDAR 2017

a project to record the attendance of students in a certain lecture using convolution neural network with an interface (it should not be existing on any website ) the program should capture the face, assigned it to an id and name taken from the user and put it to the database , show if the student is attending the lecture or not and put the record next to their name and id

Image processing , DCGAN, Convolution neural networks

Image processing , DCGAN, Convolution neural networks it's CNN based image recognition project, using DCGAN,,,,As per the document, the task is to generate images using DCGAN and CNN. Model is not mentioned in the document. If you allow me to use pre built model then I can complete the task within 45 hours.,,,, Pls if you can do it start your bid with CNN >>

Image processing , DCGAN, Convolution neural networks

Image processing , DCGAN, Convolution neural networks

One of the most common image filtering methods is performed using the act of convolution. More specifically, a convergence takes place between the original image and a table of factors called a mask or kernel. The act of convergence can visually reminiscent of array multiplication, but differs significantly. In general In this case, the paintings are not the same size, but the mask is small e.g. 3x3 while the image is much larger. In these cases the image is split in subdivisions of the same size as the mask and in each subdivision is executed the convergence.

In this assignment, you need to write a code/program to do image filtration or convolution of 2 noise filters. Please submit a report on the assignment. 1.0 Introduction - Please state a simple objective - what you want to study based on the choice of the filter 2.0 Method 3.0 Discussion

research on Convolution neural network

Looking for expert in Deep learning based NOMA in internet of thing's expert require .random binary bits of 1024 length and do rate 1/2 convolution encoding and do the BPSK modulation and pass it through a noisy channel and decoding it with LSTM( long short term memory).

Signals and Systems, convolution numericals, Matlab code

We need to generate random binary bits of 1024 length and do rate 1/2 convolution encoding and do the BPSK modulation and pass it through a noisy channel and decoding it with LSTM( long short term memory). We need to get the output same as the applied input. Medium Access Protocols involves a broader spectrum (up to 60 GHz) and will allow for non-orthogonal techniques and most likely be OFDMA-based. Nonetheless, there is a consensus in the literature that the orthogonal multiple access approach will not suffice to support the massive access from a vast number of loT systems devices. That is because grant-based communications suffer from collision rates over the random- access channel that is as high as 10%, for less than ten active users. Moreover, the signalling overhead involved i...

Two 16-bit number from X0 and X9 and H0 to H9 multiply them and add them . Code shall be done in VHDL Y= x0h0+x1h1+x2h2+x3h3+........x9h9. For more details find the attached Set of Question.

Implement the Convolution Neural Networks(CNN) approach on dataset by importing the data from mentioned library.

I have assignment contains three questions. One question for applying composite transformations on one point. Next question for applying perspective projection. The last one about performing image Convolution. I prefer to write code in jupyter note book

What I need a template to add ANY custom layer to a Keras sequential model. IT should contain a block to calculate forward pass and backward gradient. It should not contain available layer in Tensorflow (tf.nn.*). For example a template to re-construct Resnet with custom convolutional layer (assuming I want to alter behavior of convolution). The code should work in a complex sequential model and should not work only on some models only. Budget is negotiable max in $30 or so. Deadline is negotiable around 3 days.