KITTI data processing and 3D CNN for Vehicle Detection

3D image classification using CNN (Convolutional Neural Network)

This project consists of C++ implementations of a 3D Rapidly Exploring Random Tree and three other extensions called RRT*, Execution Extended RRT and Synchronised Greedy Biased RRT. It also includes a heuristically guided RRT* with biased sampling towards relevant bottleneck points predicted by a 3D CNN(modified VoxNet in Tensorflow).

Tensorflow implementation of 3D CNN for brain age prediction from MRI

A React-based Pokédex featuring a library of 120 Pokémon with 3D Blender models, fluid animations, and a creative, responsive UI. Includes gym data, voice and audio integration, and Pokémon detection using a TensorFlow CNN with 96% accuracy. Combines real-time PokéAPI data with locally stored JSON for enhanced performance and custom content.

Tensorflow implementation of a 3D-CNN U-net with Grid Attention and DSV for pancreas segmentation trained on CT-82.

Object-level sensor data fusion of RGB camera and 3D radar for road user detection and motion prediction. Trained YOLOv8 and Faster R-CNN models on Fraunhofer INFRA-3DRC-Dataset. Includes radar clustering (DBSCAN), spatial data association, and Kalman filtering for precise tracking. Tools: Python, OpenCV, TensorFlow, PyTorch.

A python class compatible with TensorFlow to perform data augmentation on 3D objects during CNN training.

Seizure classification using a 3D CNN in TensorFlow to classify mutli-channel time series EEG seizure data

Fuzzy Integral based classifier fusion for CNNs on 3D videos of human actions. TensorFlow implementation of IEEE Transaction paper

A 3D_CNN network on Tensorflow for sports video classification by training motion vector.Unfinished.

TensorFlow implementation of the 3D Mask R-CNN. The Mask R-CNN is an end-to-end network for instance segmentation. With compiled 3D Non Max Suppression and Crop And Resize.

DataGenerator for 3D-CNN in keras and tensorflow

A Deep Learning-based Lung Cancer Detection application using a 3D CNN model with TensorFlow and OpenCV, featuring an interactive Tkinter GUI for easy data processing and training.

ModelNet10 shape classification implemented with tensorflow

Generating 3D Chairs in Tensorflow using CNNs

Voxel Ops for TensorFlow Implementation of Point-Voxel CNN for Efficient 3D Deep Learning [NeurIPS 2019, MIT HAN Lab]

A video-processing AI that uses the 3D CNN model from Tensorflow to detect and remove the end-slide of a short video.

This project presents a custom-built 3D Convolutional Neural Network (3D-CNN) model for dynamic hand gesture recognition, implemented using TensorFlow and Keras. The model was trained on preprocessed gesture video frames and achieved satisfactory accuracy.

Code for my implementation of a 3D CNN that utilized TensorFlow Datasets API, the Keras Deep Learning library, and many more data-oriented libraries to produce a classifier that placed top 12% in the RSNA-MICCAI Brain Tumor Radiogenomic Classification on Kaggle.

A real‑time, lip‑reading distress‑signal detector built with TensorFlow and OpenCV. “Silent Beacon” monitors a live camera feed, transcribes silent speech via a 3D‑CNN + BiLSTM model with CTC decoding, detects predefined distress keywords, and instantly raises an alert—complete with logs, snapshot GIFs, and configurable notification hooks.

cnn-3d-tensorflow

3-dimensional convolutional neural network implemented using Tensorflow for cosmological simulational data.

3D CNN uses Tensorflow

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3D convolutions applies a 3 dimensional filter to the dataset and the filter moves 3-direction (x, y, z) to calculate the low level feature representations. It is helpful in event detection in videos, 3D medical images etc. They are not limited to 3d space but can also be applied to 2d space inputs such as images.

TensorFlow CNN 3D CT-Scan for Detecting Viral Pneumonia in the Dataset