ISS (image semantic segmentation, image captioning)

• 74 Evaluating area of vegetation on aerial image using ISS (image semantic segmentation)

Spec: Segment multispectral image using deep convolutional neural U-Net.

Language: Matlab (Deep Learning & Neural Networks Toolbox, Computer Vision Toolbox).

• 134 Image semantic segmentation using CNN with dilation

Spec: Segment image using deep learning.

Language: Matlab (Deep Learning & Neural Networks Toolbox, Computer Vision Toolbox).

Image classification using bag of visual words

• 47 Bicycle detection from car using bag of visual words & SVM (support vector machine)

Spec: Integrate computer vision and machine learning.

Language: C++ (OpenCV), Matlab (Computer Vision Toolbox, Machine Learning Toolbox).

• 58 Birds detection from airplane using bag of visual words & SVM

Spec: Integrate computer vision and machine learning.

Language: C++ (OpenCV), Matlab (Computer Vision Toolbox, Machine Learning Toolbox).

Image classification using CNN, residual NN, transfer learning, SVM

• 62 Recognizing neurological disease on MRI image using CNN

Spec: Build, train & validate deep network to classify images.

Language: Python (Keras-Tensorflow), Matlab (Deep Learning & Neural Networks Toolbox, Computer Vision Toolbox).

• 136 Recognizing object in image using classification CNN

Spec: Build, train & validate deep network to classify images.

Language: Python (Keras-Tensorflow), Matlab (Deep Learning & Neural Networks Toolbox, Computer Vision Toolbox).

• 63 Evaluating rotation of object in image using regression CNN

Spec: Build, train & validate deep regression network to evaluate rotation angles of objects in images.

Language: Python (Keras-Tensorflow), Matlab (Deep Learning & Neural Networks Toolbox, Computer Vision Toolbox).

• 72 Recognizing neurological disease on grayscale MRI image using residual NN

Spec: Build, train & validate deep residual network to classify images.

Language: Python (Keras-Tensorflow), Matlab (Deep Learning & Neural Networks Toolbox, Computer Vision Toolbox).

• 87 Recognizing hand-written digits preprocessed by RICA & SF

Spec: Investigate RICA & SF for image classification.

Language: Matlab (Machine Learning Toolbox).

• 73 Recognizing neurological disease on colored MRI image using residual NN

Spec: Build, train & validate deep residual network to classify images.

Language: Python (Keras-Tensorflow), Matlab (Deep Learning & Neural Networks Toolbox, Computer Vision Toolbox).

• 64 Recognizing neurological disease on MRI image using CNN trained in cloud

Spec: Build, train & validate deep network to classify images. It is done in cloud.

Language: Python (Keras-Tensorflow), Matlab (Deep Learning & Neural Networks Toolbox, Computer Vision Toolbox).

• 135 Recognizing neurological disease on MRI image using TL with retrained GoogLeNet

Spec: TL (transfer learning) from a network pretrained on images of one set of classes to a network which is supposed to recognize images of another set. The TL is done by retraining.

Language: Python (Keras-Tensorflow), Matlab (Deep Learning & Neural Networks Toolbox).

• 131 Recognizing neurological disease on MRI image using TL with GoogLeNet retrained in deep network designer

Spec: TL (transfer learning) from a network pretrained on images of one set of classes to a network which is supposed to recognize images of another set. The TL is done by retraining.

Language: Matlab (Deep Learning & Neural Networks Toolbox).

• 70 Recognizing neurological disease on MRI image using TL with retrained AlexNet

Spec: TL (transfer learning) from a network pretrained on images of one set of classes to a network which is supposed to recognize images of another set. The TL is done by retraining.

Language: Python (Keras-Tensorflow), Matlab (Deep Learning & Neural Networks Toolbox).

• 132 Recognizing neurological disease on MRI image using TL with AlexNet retrained in deep network designer

Spec: TL (transfer learning) from a network pretrained on images of one set of classes to a network which is supposed to recognize images of another set. The TL is done by retraining.

Language: Matlab (Deep Learning & Neural Networks Toolbox).

• 71 Recognizing neurological disease on MRI image using TL with feature extraction from AlexNet

Spec: TL (transfer learning) from a network pretrained on images of one set of classes to a network which is supposed to recognize images of another set. The TL is done by feature extraction based on integration of neural network (CNN) with machine learning (SVM).

Language: Python (Keras-Tensorflow), Python (Scikit-learn), Matlab (Deep Learning & Neural Networks Toolbox).

• 133 Transfer learning by converting classification NN (project136) into regression NN (project63)

Spec: TL (transfer learning) from a network pretrained for classification to a network which is supposed to run for regression. The TL is done by retraining.

Language: Python (Keras-Tensorflow), Matlab (Deep Learning & Neural Networks Toolbox).

• 10 Fingerprint identification using pretrained & retrained CNN

Spec: TL (transfer learning) from a network pretrained on images of one set of classes to a network which is supposed to recognize images of another set. The TL is done by retraining.

Language: Python (Keras-Tensorflow), Matlab (Deep Learning & Neural Networks Toolbox, Computer Vision Toolbox).

• 48 Birds detection from airplane using CNN trained from scratch

Spec: Build, train & validate network to classify images.

Language: Python (Keras-Tensorflow), Matlab (Deep Learning & Neural Networks Toolbox, Computer Vision Toolbox, ).

• 46 Deer detection from car using feature extraction from pretrained CNN

Spec: TL (transfer learning) from a network pretrained on images of one set of classes to a network which is supposed to recognize images of another set. The TL is done by feature extraction based on integration of neural network (CNN) with machine learning (SVM).

Language: Python (Keras-Tensorflow), Matlab (Deep Learning & Neural Networks Toolbox, Computer Vision Toolbox, Machine Learning Toolbox).

• 57 Birds detection from airplane using feature extraction from pretrained CNN

Spec: TL (transfer learning) from a network pretrained on images of one set of classes to a network which is supposed to recognize images of another set. The TL is done by feature extraction based on integration of neural network (CNN) with machine learning (SVM).

Language: Python (Keras-Tensorflow), Matlab (Deep Learning & Neural Networks Toolbox, Computer Vision Toolbox, Machine Learning Toolbox).

Image retrieval

• 50 Recognizing text on speed limit road sign using image retrieval

Spec: Investigate image retrieval (based on bag of visual words & SVM) for text recognition.

Language: C++ (OpenCV), Matlab (Computer Vision Toolbox).

Object detection using R-CNN (regions with CNN), Fast R-CNN, Faster R-CNN

• 75 Stop road sign detection using R-CNN

Spec: Integrate computer vision (Viola-Jones or ACF) and neural network (CNN).

Language: Matlab (Computer Vision Toolbox).

• 76 Detecting cars on highway using Faster R-CNN

Spec: Build & train CNN to detect predefined object in images.

Language: Matlab (Computer Vision Toolbox).

• 49 Airplane detection from satellite using R-CNN on pretrained CNN

Spec: Integrate computer vision (Viola-Jones or ACF) and neural network (CNN).

Language: Matlab (Deep Learning & Neural Networks Toolbox, Computer Vision Toolbox).

Object detection using local feature detection, extraction & matching

• 32 Fingerprint identification using feature matching, spatial transformation & image quality evaluation

Spec: Investigate integration of image registration with image quality evaluation for image classification.

Language: C++ (OpenCV), Matlab (Computer Vision Toolbox, Image Processing Toolbox).

• 54 Finding defects in details on conveyor belt using calibrated camera

Spec: Measure size of planar object detected in image captured by calibrated single camera.

Language: C++ (OpenCV), Matlab (Computer Vision Toolbox, Image Processing Toolbox).

• 60 Estimating coordinates & orientation of details to be picked up by robot arm from conveyor belt

Spec: Measure distance to planar object (and its orientation) detected in image captured by calibrated single camera.

Language: C++ (OpenCV), Matlab (Computer Vision Toolbox, Image Processing Toolbox).

Video stabilization using local feature detection, extraction & matching

• 52 Helmet camera video stabilization using image registration

Spec: Stabilize video using FAST (Features from Accelerated Segment Test).

Language: C++ (OpenCV), Matlab (Computer Vision Toolbox).

Object detection using ACF (aggregate channel features), Viola-Jones

• 77 Stop road sign detection from car using ACF

Spec: Configure & train ACF object detector to recognize object in images.

Language: Matlab (Computer Vision Toolbox).

• 78 Stop road sign detection from car using Viola-Jones

Spec: Configure & train Cascade object detector to recognize object in images.

Language: C++ (OpenCV), Matlab (Computer Vision Toolbox).

• 59 Speed limit road sign detection from car using ACF

Spec: Configure & train ACF object detector to recognize object in images.

Language: Matlab (Computer Vision Toolbox).

• 51 Speed limit road sign detection from car using Viola-Jones

Spec: Configure & train Cascade object detector to recognize object in images.

Language: C++ (OpenCV), Matlab (Computer Vision Toolbox).

Object tracking using CAMShift (continuously adaptive mean shift), KLT (Kanade-Lucas-Tomasi)

• 79 Face tracking using CAMShift

Spec: Integrate Viola-Jones object detector and CAMShift tracking algorithm.

Language: C++ (OpenCV), Matlab (Computer Vision Toolbox).

• 80 Face tracking using KLT

Spec: Integrate Viola-Jones object detector and KLT tracking algorithm.

Language: C++ (OpenCV), Matlab (Computer Vision Toolbox).

Object tracking using Kalman filter

• 81 Tracking people by surveillance camera using Kalman filter

Spec: Integrate motion-based object detector and Kalman filter to track moving objects by stationary camera.

Language: C++ (OpenCV), Matlab (Computer Vision Toolbox).

• 82 Tracking pedestrians from moving car using Kalman filter

Spec: Integrate ACF object detector and Kalman filter to track moving objects by moving camera.

Language: C++ (OpenCV), Matlab (Computer Vision Toolbox).

Object tracking using motion-based object detector

• 53 Heart rate detection using smartphone video camera

Spec: Apply motion-based object detector to a video captured by stationary camera.

Language: C++ (OpenCV), Matlab (Computer Vision Toolbox).

Motion estimation

• 116 Motion estimation using optical flow

Spec: Evaluate optical flow using Horn-Schunck algorithm.

Language: C++ (OpenCV), Matlab (Computer Vision Toolbox).

Measuring 2-D objects (planar vision)

• 83 Measuring size of 2-D object using calibrated camera

Spec: Measure distance to planar object (and its size) detected in image captured by calibrated single camera.

Language: C++ (OpenCV), Matlab (Computer Vision Toolbox).

• 54 Finding defects in details on conveyor belt using calibrated camera

Spec: Measure size of planar object detected in image captured by calibrated single camera.

Language: C++ (OpenCV), Matlab (Computer Vision Toolbox, Image Processing Toolbox).

• 60 Estimating coordinates & orientation of details to be picked up by robot arm from conveyor belt

Spec: Measure distance to planar object (and its orientation) detected in image captured by calibrated single camera.

Language: C++ (OpenCV), Matlab (Computer Vision Toolbox, Image Processing Toolbox).

Measuring 3-D objects (stereo vision)

• 84 Measuring distance from stereo camera to person using disparity map

Spec: Measure distance to moving object in video captured by stereo camera.

Language: C++ (OpenCV), Matlab (Computer Vision Toolbox).

• 85 Measuring distance from stereo camera to face using triangulation

Spec: Measure distance to object in image captured by stereo camera.

Language: C++ (OpenCV), Matlab (Computer Vision Toolbox).

Multiple view geometry using SfM (structure from motion)

• 55 Reconstructing 3-D scene from two 2-D images using SfM

Spec: Reconstruct 3-D scene from two 2-D images using epipolar geometry.

Language: C++ (OpenCV), Matlab (Computer Vision Toolbox).

• 56 Reconstructing 3-D scene from three 2-D images using SfM

Spec: Reconstruct 3-D scene from three 2-D images using epipolar geometry.

Language: C++ (OpenCV), Matlab (Computer Vision Toolbox).

Lidar 3-D point cloud

• 86 Building 3-D point cloud from Lidar readings

Spec: Reconstruct 3-D scene from two point clouds captured by Lidar.

Language: Matlab (Computer Vision Toolbox).

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