Dcgan epochs jobs
...extracted) 1. Time-domain features - *short-term energy of signal, zero crossing rate, maximum amplitude, minimum energy, entropy of energy* 2. Frequency-domain features- * MFCC - [12 (form 26 mel freq), 13 delta,13 delta acceleration ], spectral centroid, spectral rolloff, spectral entropy and chroma coefficients* - Do K-means clustering, make confusion matrix and do MLP perceptron. choose epochs as per needed - Make a user interface model where input audio of unknown sample (3- second) is given and it can give o/p as emotion. (like use django or any other) Key Responsibilities: - Developing and implementing a speech recognition model - Ensuring the model can accurately process multiple languages Ideal Skills: - Expertise in ML algorithms and audio datasets - ...
...FedPer and FedAvg in the field of HAR. In this way, I used only the Encoder part of the transformer and instead of applying positional encoding to the input, I applied it to the attention matrix. Then I came to the methods FedAvg and FedPer, on the client side, I used a transformer to train the model, and on the server side, I used a transformer to aggregate the weights. I considered the number of epochs as 100, and 2 learning rates, one 0.01 and the other 0.001, and batch sizes of 16, 32, and 64. I chose to measure the accuracy of the model in these lrs and different sizes.i have used two datasets (PAMAP2 and MotionSense) and my model gained 99 percent of accuracy. I want to test my model on another two datasets (WISDM and Opportunity) and i expect my model gain the accuracy bet...
...Eternity." This avant-garde project challenges typographers to reimagine and reinvent the concept of time through the artful arrangement of letters, numbers, and :Temporal Typography: "Echoes of Eternity" invites typographers to manipulate and play with the very fabric of time through the medium of letters. Each character becomes a vessel, carrying the essence of different eras and epochs, creating a harmonious blend of past, present, and future in a typographic in Characters: Participants will craft typographic narratives that echo the stories of various historical periods. From ancient civilizations to futuristic utopias, each typographic creation will narrate tales of the human experience, capturing the spirit of different ages through the nuanced use of fonts
...desired outcome, select a suitable algorithm. Consider RNNs, LSTMs, or CNNs for their ability to handle sequential or structured data. Define Model Architecture: Design the neural network architecture with layers, activation functions, and connections. You can use libraries like TensorFlow or PyTorch to build the model. Hyperparameter Tuning: Experiment with different hyperparameters (learning rates, epochs, hidden layer sizes) to optimize the model's performance. Step 3: Implementation and Training Develop Training Script: Write the code to train the model on your collected data. The script should include data loading, model definition, loss function definition, optimizer selection, and training loop. Train the Model: Run the training script and monitor the model's pe...
...Read this - The library should be installed in another python project - It should work on Linux ## Methods - uploadDataset(“/tmp/”) Receives a file with this structure Returns an uuid pointing to the location of received dataset - startTraining({ "epochs": 25, "dataset_uuid": "fffb42f1-4b83-db259ca3850c”}) Receives some settings like epoch and the dataset uuid. Due to the training may take a while, this should be an async task Returns an uuid pointing to the started job (training) - getTrainingStatus("901b9311-9876-4539-83ac-80c8b919282f”) Receives the training uuid Returns a dictionary with these values { "status":"in-progress", "progress":
I'm currently engaged in a fascinating sleep study. In order to fully examine and understand the data that's been collected, I need the assistance of a well-versed MATLAB programmer. Here is a rundown of the tasks I need help with: - Develop a code from scratch that I write epochs of interest from my sleep study data, which are in 30-second epochs. - Use the jfemgAll function to extract pertinent features from the data. - Ensure that the code can seamlessly export these features to an Excel file. Ideal skills and experience: - Proficiency in MATLAB coding. - Knowledge about data analysis related to sleep studies would be a plus. - Proficient in Excel. - Detail-oriented and capable of working independently. I'm eagerly looking forward to meeting a freela...
I am looking for a skilled ML developer who can implement a GAN model for my academic research project. The specific GAN model I am looking to implement is a GAN for chest X-rays, with a focus on overcoming class imbalance and data augmentation. Skills and experience required: - Strong understanding and experience with GAN models, specifically DCGAN, WGAN, or CGAN - Experience working with medical imaging datasets, particularly chest X-rays - Proficiency in data preprocessing techniques to handle class imbalance and generate synthetic data - Familiarity with machine learning frameworks such as TensorFlow or PyTorch - Knowledge of evaluation metrics for GAN models in the medical domain The project will involve using an existing dataset for training the GAN model, which I already ha...
...desired outcome, select a suitable algorithm. Consider RNNs, LSTMs, or CNNs for their ability to handle sequential or structured data. Define Model Architecture: Design the neural network architecture with layers, activation functions, and connections. You can use libraries like TensorFlow or PyTorch to build the model. Hyperparameter Tuning: Experiment with different hyperparameters (learning rates, epochs, hidden layer sizes) to optimize the model's performance. Step 3: Implementation and Training Develop Training Script: Write the code to train the model on your collected data. The script should include data loading, model definition, loss function definition, optimizer selection, and training loop. Train the Model: Run the training script and monitor the model's pe...
I am looking for a skilled freelancer who can generate synthetic text data using GAN for the purpose of training a model. The ideal candidate should have experience in working with GANs and should be familiar with different architectures such as DCGAN and CycleGAN. However, since I have no preference for a specific architecture, the freelancer can choose the most suitable one for the task. The main goal of this project is to generate high-quality synthetic text data that can be used for training a model.
...decoder. The two-dimensional vector on the latent space passes through three fully-connected neural networks with dimension (256, 512, 3×512) with relu activation function and linear output activation function; the output is a 3D point cloud with the number of points 512. Section 5.1.1: To train the networks, we use ADAM with a learning rate of 0.001 and batch size of 16; the total number of the epochs is 500. The mean value of MEDs of the dataset is 0.0339, and we use the bandwidth value k to 0.5. We use Chamfer distance as the reconstruction loss; code:
Adapt this multilabel classifier (using EfficientNet) onto my laptop. Can use Pytorch if you wish, but do not omit steps shown on the webpage. Aim for executing 10 - 30 epochs full 45gb dataset on my laptop, similar accuracy and ROC to webpage. Must use efficientnet, include weighting considerations, include .h5 transfer learning as per webpage.
I am looking for an experienced freelancer to help me with a Machine Learning project, specifically related to image inpainting problems using a DCGAN. The goal is to make an AI model that can complete objects in images that have been partially erased or are incomplete. The desired output resolution is low, under 512x512. I don't have any specific datasets for this project, so the freelancer will have the freedom to choose which datasets to use. Regarding documentation, I already have code for the project, but need to train the model and send the results. Thank you very much in advance!
I have a paper that proposed a hybrid framework, I want the code of "a lung cancer deep convolutional GAN (LCGAN) to generate synthetic lung cancer images". It was based on DCGAN but they have some differences in the architecture. The project requests important points: 1- Write the code in Python programing language using Pytorch in Google Colaboratary 2- Explain each build layer and the details of this layer; how and why (the purpose of changing it) 3- Write explain comment for every function 4- Explain how can dwnload the images are generated from the model on my drive 5- How i can use the same code with different dataset with different size such as: 512*512 640*640 1536*2048 6- Describes the steps to run the project 7- Firstly used the same dataset in the paper (it is ...
...Recently Used) with social aware SLR 3. Most popular Caching with social aware(SMP) 4. DDQN based caching without social aware(DQ) 5. Proposed Methodology (GC-GRU Federated Learning) Requirements: Following are the major outputs I need to get graphed: Performance evaluation: Convergence performance How fast my model converge in comparison to given models. It will be compared with number of episodes/epochs with the cumulative Reward. Caching performance on basis of average delay 1. You need to find delay with respect to content size.(10-100MB) 2. Delay with respect to storage capacity.(Kindly keep in mind the capacity of mobile device ( take from 1GB-10GB) 3. Delay wrt to distance( Distance may very from 10-50m) Energy Consumption 1. How energy consumption is decreased when number...
I am looking for a developer who can help me improve an existing emotion recognition model using Siamese Neural Network. The desired outcome of the project is to enhance the accuracy and performance of the model. Skills and experience needed: - Strong knowledge and experience in TensorFlow - Familiarity with emotion recognition models - Experience in trai...improve an existing emotion recognition model using Siamese Neural Network. The desired outcome of the project is to enhance the accuracy and performance of the model. Skills and experience needed: - Strong knowledge and experience in TensorFlow - Familiarity with emotion recognition models - Experience in training and optimizing neural networks Please note that the desired number of training epochs for this project was not ...
I am looking for a sk...can help me create a GANs model for image 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.
Scope: 1. Installation of source code, first tests 2. Preporation of datasets (at this step I can say what resolution is requered. ) 3. First training trials for few epochs, first inference trails. 4. Training (8 hours). Deliverables: 1. Installation instructions for AWS instance 2. Extensions of source code (if they will be nessacery) 3. Python scripts for data processing (if they will be nessasary) 4. Pretrained Model (after 8 hours of training) Note: if there are some inconsistencies in the data or source code, the effort can be increased.
Need an expert to build deep learning model. The basic model would be provided, but you need to build further two models from it: 1. Basic model with Attention 2. Basic model with Squeeze and Excitation & ASPP Note that the training and testing data would be provided to you. YOU DO NOT NEED TO TRAIN THE MODEL ITSELF, just need to check if the model is working ( or DSC is not NaN after certain epochs).
I'm going to develop a model to predict the loan. I'm using ANN for modeling. while fitting my model, I got this error which block me for going forward. epochs_hist = (X_train, y_train, batch_size=128, epochs=100, verbose=1, validation_split=0.0) wondering if you could help me out with this, thanks!
PLEASE MAKE SURE YOU READ THE ENTIRE DESCRIPTION BEFORE YOU PLACE BID Hi, I want to create my own AI tool and am looking for a developer who is an expert i...train_data[:, 0] # Create the input and output arrays for the testing data X_test = test_data[:, 1:] y_test = test_data[:, 0] # Define the model model = Sequential() (Dense(12, input_dim=[1], activation='relu')) (Dense(1, activation='linear')) # Compile the model (loss='mean_squared_error', optimizer='adam') # Train the model (X_train, y_train, epochs=100, batch_size=32) # Evaluate the model on the test data test_error = (X_test, y_test, verbose=0) print('Test MSE:', test_error) # Use the model to make predictions on new data predictions = (X_test)
Hi, need someone with yolov5/pytorch experience to help with this - I'm training ML model with yolov5 this is my command - python3 -m --nproc_per_node 2 --batch 100 --epochs 1000 --data /home/username/Documents/folder_name/ --weights --device 0,1 --hyp data/hyps/ --name folder_name --patience 0 It will cut out after 30min, because of the default pytorch timeout 1800s. How can I increase it? Thanks described here -
Plurana is a culttech startup that makes art more accessible to people. Our goal is to digitise world ornamental heritage, and now we are looking for remote digital artists and illustrators willing to recreate authentic patterns. As part of our team, you will work with objects of different cultures and epochs and will have a chance to familiarise yourself with the collections of world-renowned museums. To get the idea of what you will do, see this file attached. *You’re our ideal candidate if you are* - an expert user of Adobe Illustrator (it is crucial as all reconstructions should be in the AI format) and have the most recent version of this programme; - a productive artist able to reconstruct 100 patterns in 1-2 months; - a self-disciplined and accurate person paying great...
... "ub": [9, ] * chromosome_size, # Upper bound "minmax": "max" # Is it min or max optimization problem? } # creating a model from Episto class, using number of epochs, population size, and other inputs... model = Episto(epoch=20, pop_size=50, x=0.7, y=0.9, z=0) # create a model best_position, best_fitness = (problem_dict_episto) # find the solution return(, best_position, best_fitness) # history contains all information from all epochs link to the original paper: Also, I have the pseudo-code of the algorithm that I can share it with you later. I can help you understand the algorithm too,
1. Input: Data set contains EEG signals in EDF format. 2. Preprocessing: Need to split the signal into 30sec epochs. 3. Feature Extraction: Fast Fourier transfrom (need signal representation after FFT) 4. Convert it into Spectrogram in frequency domain (need spectrogram image in frequency domain)
1. Input: EEG dataset( in form of .edf files = total 61 files with 30 mins or more size) 2. Pre-processing: divide each signal into 30 sec epochs 3. Signal to spectogram: coverting the signal into spectogram using Fast Fourier Transform (need signal and spectogram representation) 4. Data splitting: training-75, testing-25 5. Classification: using pretrained transfer learning models VGG16 InceptionV3 DenseNet169 ConvNeXtBase 6. Output: the input signal is MCI or Normal Control 7. Performance metrics- Accuracy, precision, recall, f1-score Note: Dataset will be provided by me language Python Editor: Jupyter notebook
Identify the relation between the values of k and x,y. Write a formula for the transition from x,y to k. Summarize the whole work! Everything is step-by-step, structured and clear. If it...coordinates, which these points produce. The main areas that fall into the work are mathematics, geometry, cryptography, statistics, programming and information protection! The reason for this is that the ECDSA function is written according to the latest developments Modeling an algorithm. Please, only high-class experts in identifying predictive functions with powers for the test and more training epochs. 4.5 billions row The file itself: a little preface.
I am new to Python Keras but I want to know how this code works. Can you explain what is the relation between x_input, y_input, input-var I made and the predicted output. Why the output is just one value and why does this program a...'__main__': print('PyCharm') x_input = ([[1, 2, 3, 4, 5]]) y_input = ([[4]]) model = Sequential() (Dense(units=32, activation="tanh", input_dim=[1], kernel_initializer='random_normal')) (Dense(units=1, kernel_initializer='random_normal')) (loss='mse', optimizer='sgd', metrics=['accuracy']) # TRAINING history = (x_input, y_input, epochs=10, batch_size=32, verbose=0) # RUN # print(model.test_on_batch(x_input)) # print() inputs = ([[11, 12, 13, 14, 15]]) print((inputs))
Run the "Example run (CIFAR10 with 50% symmetric noise) with taking 4 noise values 0.1, 0.2, 0.3 and 0.4 for 25 epochs or 50 epochs, and then generate a Epochs vs Accuracy graph for all the noise values in one graph only.
...and has proven experience For this project, I have various crypto assets which has prices split into 3 minute epochs of data (The data is taken from lots of exchanges) Each epoch has approx 3 minutes of data and various companies (including myself) submit what they think the true price of the asset is for the period in USD, so might take weighting average of certain price times etc. Once all companies submit their estimate of the true price, the external service then calculates the median of prices submitted and a quartile range. My submitted price needs to be inside that quartile range as often as possible for my service to be considered accurate. Attached are 1000 sample epochs of data for each of the crypto assets (11 in total). In these files, they have the prices ...
Hello. I need a dev that would develop a simple deep learning model that would predict the electric... 1 September 2021 to 30 September 2022. The features are the following: 1) Datetime 2) Energy Demand 3) Petroil and Gas features price 4)Climatic Data on three cities 5) Rewenable Energy Production 6) The data to predict: Hourly Electricity price. I need someone that does the following things: 1) Select the most accurated model (LSTM or any other) and setup anything in the most accurated way (epochs, number of layers etc...) 2) Apply all hyperparameters in order to improve the accuracy 3) Reach a reasonable accuracy (at least 0.80) 4) Save the model to a .pkl file The developer should give me: 1) The source code file, written in python and show me the real accuracy of the model 2)...
hi, I have a dataset, and i want to use them for learning deep learning algorithms, I want to compare LSTM, Bi-LSTM and RF-GRU-NTP. I would need to compare the R2 score, MSE and RMSE. . The MAE fig for GRU, LSTM and Bi-LSTM . and epochs. in the end, I would like to have a pickle to use the model for predictions.
I am somewhat new to using Tensorflow and learn to use it from a C# application....Call(Tensors inputs, Tensor state, Nullable`1 training) at (Tensors inputs, Tensor state, Boolean training) at Tensorflow.Keras.Engine.Model.train_step(Tensor x, Tensor y) at Tensorflow.Keras.Engine.Model.train_step_function(OwnedIterator iterator) at (Int32 epochs, Int32 verbose) at (NDArray x, NDArray y, Int32 batch_size, Int32 epochs, Int32 verbose, Single validation_split, Boolean shuffle, Int32 initial_epoch, Int32 max_queue_size, Int32 workers, Boolean use_multiprocessing) at (String[] args) in C:Usersnum1sourcereposLSTM_TestLSTM_Test:line 24
This is a deep learning project (Plant Disease Classification) where you have to implement any 4-5 transform learning models (like VGG16, VGG19, ResNet, MobileNet, Inceptionv3, EffiicentNet,...implement any 4-5 transform learning models (like VGG16, VGG19, ResNet, MobileNet, Inceptionv3, EffiicentNet, Xception or any other model) on this dataset. Dataset: Evaluate model in sequential manner using Basic Imports, Data Processing (Image Augmentation), Using pre-trained model and then fitting the model (running epochs) and evaluating the accuracies and losses with graphs, show the confusion matrix for all classes, classification report, and test with separate images given in "images to predict" directory at the end.
My team is working on a project that uses Nvidia Nemo to convert speech to text (Russian and English)and client voice identification. We need to create a Russian model. Nvidia's Russian model is not accurate enough. We have following initial questions. 1) Is it possible to use one model to dynamically diarize multiple audio files 2) How to augment a model using last check point 3) How many epochs needed to create a model 4) We need to identify speaker language (Russian or English) and use correct model 5) Is it possible to create one model for both Russian and English 6) Hardware spec requirements for creating a ASR model
1 of the files Data needs Data augmentation to increase number of images from 24 to 240 Code rom keras import regularizers IMG_SIZE = 224 input_shape = (IMG_SIZE, IMG_SIZE, 3) model4 = () (Conv2D(32, kernel_size=(3, 3),activation='LeakyReLU',padding = 'Same',input_shape=input_sha....L2(1e-5))) (Conv2D(filters=64, kernel_size=(3, 3), activation='relu')) (Flatten()) (Dense(64, activation='LeakyReLU')) (Dense(num_classes, activation='softmax')) () (optimizer=(lr=3e-4),loss='categorical_crossentropy',metrics=['accuracy']) history4=((), epochs=30, verbose=2, validation_data=())
...a python and MapGIS pro to help me with my CSV Xcel file dataset. I need 3 predictive models that have extremely high accuracy for 4 target variables and provide all of the code with markdowns explaining. Make sure you eliminate variables with low influence and any collinearity, standardize variables of different formats and data types and prevent over-fitting. Optimize the models by adjusting epochs and other items. Account for null values, construct flag variables for categoricals, Test for accuracy and select the most accurate models. Try several model types to find the best one. Construct the 3 models with the preprocessed data. Each of the 3 models is a different model type. The new models will need to learn daily as new data is updated. The output should be a column on the ...
...because I would rather reject parts than have them sorted incorrectly. My images are 300x300. I look at the weight of the prediction, and 95% of my predictions are almost certain, say .99999, so I haven’t been able to do the simple thing of just looking at the strength of the prediction. In case this is relevant, the resnet50 classifier that I have trained might be overtrained. Within three epochs it is at like 99.7% accuracy with a val_accuracy of 98%. Epoch 3/3 99/99 [==============================] - 572s 6s/step - loss: 0.0138 - accuracy: 0.9967 - val_loss: 0.3574 - val_accuracy: 0.9796 Here is an article that shows what needs to be implemented. The project milestone is when the
1. Google Colab code 2. Report of the results 3. Deadline 20 days after selection 4. After selection, you must send progress to avoid mistakes within 5days. 5. If it is not work in Google Colab on my Mac, you must fix it through TeamViewer or so. I. Music Dataset CSV data (fixed, I will give you and ...fix it through TeamViewer or so. I. Music Dataset CSV data (fixed, I will give you and discuss.) 2. Data analysis: (Reading and Understanding the Data, Showing raw data, Visualizing Audio Files, Plot Raw Wave Files, Spectrograms, pectral Rolloff, Spectral Centroid, MFCC (Mel-Frequency-Cepstral Coefficients), Chroma Feature, Zero Crossing Rate, Feature Extraction, Scaling the Features) 3. Build DCGAN (Deep Convolutional Generative Adversarial Network) for emotion-based genre classi...
Music Genre Classification with DCGAN Work content 1. Google Colab code 2. Report (Simple) the results 3. Deadline (10days after being selected or can be decided through talking. Should mention progress after 3-days). I. Dataset (music data) CSV data (fixed, I will give you or we can discuss) 2. Data analysis: (Reading and Understanding the Data, Showing raw data, Visualizing Audio Files, Plot Raw Wave Files, Spectrograms, pectral Rolloff, Spectral Centroid, MFCC (Mel-Frequency-Cepstral Coefficients), Chroma Feature, Zero Crossing Rate, Feature Extraction, Scaling the Features) 2. Build GRU (Gated Recurrent Unit) for genre classification 3. Model Evaluation of DCGAN for genre classification (Confusion matrix, data results, figures) 4. Comparison with CNN results (or others...
I have a simple python/keras/resnet50 script to train an image classification model. The resnet50 part is like 40 lines of code. I need someone to port it to pytorch. Below is the heart of the script that needs to change. If you know pytorch, this should be easy to do. This is not the whole script, but if you can show...outputs=output_layer) # we are making all the layers intrainable except the last layer for layer in [:-1]: layer.trainable=False xtrain, xtest, ytrain, ytest = train_test_split(x,y,test_size=0.2,random_state=5) (loss='categorical_crossentropy', optimizer='adam',metrics=['accuracy']) # 13 Fit the Model print("fitting the model") history = (xtrain,ytrain,epochs=numEpochs,batch_size=64,verbose=True,validation_data=...
I am working on combining a U-Net (model) with a Vision Transformer (model) to achieve the task of removing weather-based noise from input images (rain, snow, fog). My method trains a little bit and stop after few initial epochs then reports error in computing the first PSNR and SSIM metrics. I can't seem to figure out the problem. At this point I need help to make the model train successfully and achieve good results. Freelancer with good knowledge of Python3, PyTorch, and deep learning will be very useful.
Time Sensitive: 4/14 11:59 PST Code a DCGAN and/or proGAN model that can take a random noise image or feature template image and generate images of dark skin conditions (Melanoma) using Keras (preferably in Google Colab too) Pricing: $150 (negotiable) Attached is the Melanoma Images (some graphic) & my current Pix2Pix GAN If you have any questions, please contact me!
...Inception Distance (FID) between 1000 generated and real data as the metric for evaluation. 3 Models for Assignment 3.1 Bayes’s Classifier with several Class Conditional Densities such as Gaussian, GMMs (Have to code up EM) 3.2 Bayes’s Classifier with different density estimates (ML, MAP and Parzen Window and nearest neighbor estimates) 5 Also using any one data set do the following:- 5.1 Train a DCGAN for one of the datasets given. Compute FID and plot the generated images in a 10×10 grids. 5.2 Train a VAE on the same dataset and repeat the above experiment. 5.3 Plot t-SNE embeddings for both 2 and 3 dimensions for one of the datasets. 5.4 Compare the above plots with the ones obtained using PCA on the same dataset on 2 and 3 dimens...
...Inception Distance (FID) between 1000 generated and real data as the metric for evaluation. 3 Models for Assignment 3.1 Bayes’s Classifier with several Class Conditional Densities such as Gaussian, GMMs (Have to code up EM) 3.2 Bayes’s Classifier with different density estimates (ML, MAP and Parzen Window and nearest neighbor estimates) 5 Also using any one data set do the following:- 5.1 Train a DCGAN for one of the datasets given. Compute FID and plot the generated images in a 10×10 grids. 5.2 Train a VAE on the same dataset and repeat the above experiment. 5.3 Plot t-SNE embeddings for both 2 and 3 dimensions for one of the datasets. 5.4 Compare the above plots with the ones obtained using PCA on the same dataset on 2 and 3 dimens...
need urgent help in the Deep learning project as describing below - price can be flexible .!! PART II: Long Short-Term Memory (LSTM) Dataset: ATIS Intent - Use ATIS_intent_train and ATIS_intent_test file for the assignment. Note: Data trimming is not allowed in this question. Dataset description: The ATI...just LSTM and linear layers to predict intent of utterance at time T considering previous X utterances’ context. 3. Now, show plots for accuracy and weighted F1 scores for X = {0,1,2,3,4} 4. Does the performance of the model increase with increase in X? Justify - For every point within each part, visualize the learning using the following plots: ● Training Loss vs Number of Epochs ● Validation Loss vs Number of Epochs ● Plots showing convergence over differen...
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 >>
