Tensorflow is an open-source library for numerical computation developed by Google that provides tools for dataflow programming and machine learning. It helps give users the ability to create deep learning models with greater ease, enabling new levels of development productivity, research, and discovery. TensorFlow achieves this through the use of dataflow graphs which allow the user to construct models at a much higher level. By relying on the predictive power of data and machine learning methods, a TensorFlow developer can empower a client to help design more efficient AI-driven algorithms, provide more accurate predictions and automated interactions with their customers, draw insights from vast amounts of structured and unstructured data, build more personalized experiences for their users, and much more.
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- Programming state-of-the-art deep learning algorithms for computer vision tasks
- Utilizing data analytics to deliver valuable insights from datasets
- Applying convolutional neural networks for image classification problems
- Creating efficient graph neural networks to approximate functions
- Implementing Machine Learning models to caption images or detect similarities between sentences
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We are looking for an experienced OpenCV developer to assist our Flutter team in implementing OpenCV in our mobile app. The ideal candidate should have a strong background in computer vision and image processing, as well as experience with OpenCV libraries and tools. Responsibilities: Collaborate with our Flutter team to integrate OpenCV into our mobile app Develop and implement computer vision algorithms using OpenCV libraries and tools Optimize and refine code for maximum efficiency and effectiveness Create high-quality documentation for all code and projects Participate in code reviews and testing to ensure the highest level of quality for all projects Provide technical support to team members and clients as needed Requirements: Strong background in computer vision and image processi...
1. create a depth map of the image using default parameters (no manual user intervention); 2. use flags to decide how to animate the 3d environment/camera (horizontally, vertically, in a tall circle or in a ide circle). the flag will come from our API e.g. "3d-movement":"vertical" 3. export the animation into a 6 second mp4 file. Attached is a 2D image (input) that was used to create the attached mp4 file (output) with "vertical" movement. This is the result we want to recreate with this project.
Intelligent Interview webapp: Build with Neural network (TensorFlow model) Scope of work: while candidate is being interview, we are saving the video and sending that video to server for further processing. Once interview is completed, Cron Job pick all the video which is saved with the status pending for processing and process the video and do the analysis Step 1. Process the video Step 2. Extract the Audio from the video Step 3. Converting the Audio Speech to Text Step 4. Analyzing the Text Step 5. Analysis of the Video and Calculating the value of Extraction Problem: --Facing issue at real time video processing and the process of video analysis is very slow. --Data loss issue at audio model. Focused points: --Speedup the video process --Improve accuracy
We need a computer vision model for detecting people in images or videos, and it should be optimized to work on the OpenVINO platform. We already have a dataset available for training the model. Objectives: The main objective of this project is to develop a people detection model that can accurately detect human beings in different environments. The model should be optimized to work on the OpenVINO platform for efficient inference. Requirements: Dataset: We have a dataset available for use in training the model. The dataset should be analyzed and preprocessed to ensure that it is appropriate for the model training process. Model Architecture: The model architecture should be simple, easy to understand, and accurate in detecting people in images or videos. It should be optimized...
I want to create desktop app. which should take the input from camera, with start and end button, and then it should create video analysis of the cricket ball. Analysis includes. the speed of the ball, detection of the ball , show trajectory path of the ball &. then shows the trajectory path representation in graphical form in 360 degree
My project is to add new custom dataset to the original one Incrementally. For example, I want to add new class while preserving other classes from previous model. The output will be a new class with the original one. To be clear, I have two classes named ( permanent teeth, primary teeth, and filling). Model 1 trained on PERM dataset ( single class) Model 2 used pre-trained from model 1 to train new class (PRIM dataset). The output should be ( two classes, PERM & PRIM). Model 3 used pre-trained from model 2 to train new class ( filling). The output after this model should be 3 classes and so on. I want to tackle the problem of catastrophic forgetting. Requirements: 1. Using Mask RCNN or U-Net versions ( TF & Keras) 2. Applied the continual learning approach similar to the atta...
We would like to develop a Red light violation detection, over speeding, no helmet, overloading on motorcycles, wrong lane changing and other violations. the license plate should be captured and details of the car should be fetched from the database and ticket sent to driver and police using python, yolo, OpenCV etc. The project should have a dashboard for deployment. We are expecting a person with a good amount of experience in Open CV and python.