Image Segmentation Techniques using Digital Image Processing, Machine Learning and Deep Learning Methods. The core contribution is incorporation of hy-percolumn concept in the processing pipeline achieving real-time tracking on 12MPx videos. But the intelligent system left everyone astonished – it taught itself how to identify cats and further went on to assemble the features of a cat to complete the image of a cat! It aims to design an open-source Artificial General Intelligence (AGI) framework that can accurately capture the spirit of the human brain’s architecture and dynamics. Reference Paper IEEE 2019An Efficient Hand Gesture Recognition System Based on Deep CNNPublished in: 2019 IEEE International Conference on Industrial Technology (ICIT)https://ieeexplore.ieee.org/document/8755038. We have successfully introduced important improvements on YOLOv3 to further fasten the detection speed for excellent accuracy. We base our detector on the popular framework of FasterR-CNN and compare its performance to other models such as Mask R-CNN or RetinaNet. The experimental results demonstrate that the designed faster R-CNN network and the FP reduction scheme are effective in the lung nodule detection and the FP reduction for MR images. The prevalence of wireless networks has made the long-term need for communications security more imperative. Thus, it encourages increasing of the productivity through the fast recognition of disease and the consequent action. Based on this, a new apple leaf disease detection model that uses deep-CNNs is proposed by introducing the GoogLeNet Inception structure and Rainbow concatenation. Reference PaperLicense Plate Localization in Unconstrained Scenes Using a Two-Stage CNN-RNNPublished in: IEEE Sensors Journal ( Volume: 19 , Issue: 13 , July1, 1 2019 )https://ieeexplore.ieee.org/document/8643978. Image Synthesis 10. Furthermore, a better learning ability in network can be enhanced under condition without increasing networked scale through multi-scaled training methods. We called this refined network HeadNet. The proposed system prototype is realized. The task requires CNN network to extract features from given image and upsample the image to segment background and foreground. Face recognition is achieved using Deep Learning’s sub-field that is Convolutional Neural Network (CNN). The focus of this paper is to present the image processing technique and test the detection and counting accuracy. Gesture recognition is an important human- computer interaction interface. Moreover, our model has a higher accuracy than the vanilla model with the same thinner factor. Reference Paper IEEE 2019Deep-PRWIS: Periocular Recognition Without the Iris and Sclera Using Deep Learning FrameworksPublished in: IEEE Transactions on Information Forensics and Security ( Volume: 13 , Issue: 4 , April 2018 )https://ieeexplore.ieee.org/document/8101565. The proposed scheme is robust against any means of eavesdropping or intruding as it is comprised of four layers of security as follows: encryption using AES-128, encoding using a repetition code, least significant bit (LSB) steganography and jamming through the addition of noise. The paper describes a vision based platform for real-life indoor and outdoor object detection in order to guide visually impaired people. Deep Learning for Image Processing Perform image processing tasks, such as removing image noise and creating high-resolution images from low-resolutions images, using convolutional neural networks (requires Deep Learning Toolbox™) Deep learning … The image size of the ROI is then resized to 100×120 and then entered into the deep convolutional neural network (CNN), in order to identify multiple hand gestures. These smart glasses can serve in the security domain for the authentication process. These samples are used for data augmentation purposes and feed the learning phase of the CNN, always considering as label the ID of the periocular part. Skin diseases are common in rural communities and flood affected areas. The performance of this technique has been tested on 880 test images out of 1880 images in a database. However, the privacy protection becomes a big problem, as the cloud server cannot be fully trusted. Blood cell image classification is an important part for medical diagnosis system. Reference Paper IEEE 2019Helmet Detection Based On Improved YOLO Deep ModelPublished in: 2019 IEEE 16th International Conference on Networking, Sensing and Control (ICNSC)https://ieeexplore.ieee.org/document/8743246. On top of that, it comes with intuitive dashboards that make it convenient for the teams to manage models in production seamlessly. The similar threshold homogeneity pixel is grouped. The results show that the proposed detector can detect all categories of traffic signs. Reference Paper IEEE 2019Published in: 2019 21st International Conference on Advanced Communication Technology (ICACT)https://ieeexplore.ieee.org/document/8701964. In this paper, a new hyperbola fitting based method of curve lane detection is proposed. First, you need to set up a simulation of the thing you wish to animate (you can capture someone making specific movements and try to imitate that). However, the performance of such an approach deteriorates in the presence of sudden illumination changes in the scene. This technique is popularly known as video oculography. There has been a rapid increase in dietary ailments during the last few decades, caused by unhealthy food routine. The objective of the undertaking is to build up a total system for unique fingerprint verification through extricating and coordinating details. Then, the method of transfer learning was introduced to solve the problem of training data shortages during training process. Image Classification With Localization 3. Reference Paper IEEE 2019 BallTrack: Football ball tracking for real-time CCTV systems Published in: 2019 16th International Conference on Machine Vision Applications (MVA) https://ieeexplore.ieee.org/document/8757880. In this context, an effective approach is suggested for automated text detection and recognition for the natural scenes. Fuzzy logic facilitates to deal with imprecise boundaries of input symptoms in medical expert system. I need a CNN based image segmentation model including the pre-processing code, the training code, test code and inference code. With the advance of deep learning, facial recognition technology has also advanced tremendously. In such a place, the environment must be made hassle-free. The segmented tumor regions are validated through ground truth analysis and manual analysis by a Neurologist. We performed experiments with a dataset comprising 100 classes, averaging 1000 images for each class to acquire top 1 classification rate of up to 85%. In recent years, robotic technologies, e.g. Automatic Teller Machine (ATM) plays a vital role in our modern economic society. Reference Paper IEEE 2019Secure Message Embedding in 3D ImagesPublished in: 2019 International Conference on Innovative Trends in Computer Engineering (ITCE)https://ieeexplore.ieee.org/document/8646685. The two core components of this visual tracking system are: This is one of the excellent deep learning project ideas for beginners. Frame extraction is the prior step, which is followed by box filter based background estimation and removal. Reference Paper IEEE 2019 Hand Gesture Recognition and Voice Conversion System for Dump People Published in: 2019 5th International Conference on Advanced Computing & Communication Systems (ICACCS) https://ieeexplore.ieee.org/document/8728538. The feature maps are upsampled using deconvolution network. Therefore, the farmer concentrates on the cause of the disease in the crops during its growth, but it is not easy to recognize the disease on the spot. The Google Brain project successfully proved that software-based neural networks can imitate the functioning of the human brain, wherein each neuron is trained to detect particular objects. A deep network consisting of Regional convolutional neural network (CNN) and recurrent neural network is designed.The experimental results show that the proposed method not only locates license plates of different countries accurately but also be robust to scenes of illumination variation, noise distortion, and blurry effects. “Olivia” is a Virtual Assistant developed specifically for homes, which can be integrated into any home to make it a Smart Home. Reference Paper IEEE 2019 Crops Disease Diagnosing Using Image-Based Deep Learning Mechanism Published in: 2018 International Conference on Computing and Network Communications (CoCoNet) https://ieeexplore.ieee.org/document/8476914. OpenCog project includes the core components and a platform to facilitate AI R&D. Deep Learning technology aims to imitate the biological neural network, that is, of the human brain. We find the width of a seam for each iteration as a prior for the seam carving process using a set of maximum energy seams in an orthogonal direction to the seam carving process. Signal Processing vs. Initially 72000+ specimens were used from NumtaDB (85000+) dataset for training and 1700+ specimens were used as test dataset. Connor Shorten. Several techniques have been employed to solve this problem. Olivia-the virtual assistant can be installed anywhere inside any house as it lives inside Raspberry Pi which is a really compact and inexpensive computer and can be connected easily to devices such as microphone, speakers, cameras, PIR etc. FMA is an interactive library comprising high-quality and legal audio downloads. Automatic Number Plate Recognition (ANPR) is a system that allows real time recognition of a vehicle license number plate. We present a deep learning system for automatic logo detection in real world images. © 2015–2021 upGrad Education Private Limited. The image is encrypted by color value substitution, block permutation, and intra-block pixel permutation. In this article, you will find top deep learning project ideas for beginners to get hands-on experience on deep learning. While the origins of Deep Learning dates back to the 1950s, it is only with the advancement and adoption of Artificial Intelligence and Machine Learning that it came to the limelight. It plays a pivotal role in different applications, namely medical diagnosis, object detection and recognition, navigation, military, civilian surveillance, robotics, satellite imaging for remote sensing. The acquired results show that our proposed inpainting method gives an outstanding performance to fill the corrupted areas and to remove objects. The proposed method has been compared with state of the art foreground detection algorithms to prove effectiveness. In this context, an effective approach is suggested for automated text detection and recognition for the natural scenes. In this project, we have designed and implemented a detector by adopting the framework of faster R-convolutional neural networks (CNN) and the structure of MobileNet. The dataset consists of 11 challenging categories such as dynamic background, bad weather, camera jitter, low frame rate, etc. This work also involved the process of collecting samples of banana with different level of ripeness, application development and evaluation to improve the accuracy of the developed applications classification results using image processing and data mining techniques. Since this technique is a generalization of logistic regression, it is apt for multi-class classification, assuming that all the classes are mutually exclusive). Iris segmentation plays an important role in the iris recognition system, and the accurate segmentation of iris can lay a good foundation for the follow-up work of iris recognition and can improve greatly the efficiency of iris recognition. Reference Paper IEEE 2019Integration of Digital Watermarking Technique into Medical Imaging SystemsPublished in: 2019 10th International Conference on Dependable Systems, Services and Technologies (DESSERT)https://ieeexplore.ieee.org/document/8770051. Computerized security frameworks are fundamental at this point. The similarity between images can be directly measured by the Manhattan distance between feature vectors on the cloud server side. dataset. Our system is mainly designed for edible objects like fruits and vegetables. Seam carving method is an effective image retargeting method which suffers from high computational complexity. Then each eye is represented by 6 – coordinates (x,y) starting from the left corner of the eye and then working clockwise around the eye. In this project, a lung nodule detection method based on deep learning is proposed for thoracic MR images. After the splitting gear breaks each character is regarded as a single and unique gesture. In terms of accuracy, the algorithm proved to be 86% accurate and was also adopted to control an actual wheelchair. In this paper, to address this problem we provide the mechanism, which dynamically analyses the images of the disease. This project aims to create a recognition system that can classify digits ranging from 0 to 9 using a combination of shallow network and deep neural network and by implementing logistic regression. Deep Learning for image captioning comes to your rescue. As an alternative, two-dimensional face recognition based on the built-in visible-light camera of mobile devices has been widely used. The mechanism performs the diagnosing of the disease, especially for the strawberry fruits and leaves, with data set of images using deep learning. The application is developed using Python and functions from OpenCV library and, ultimately ported upon Raspberry PI3 Model B+ platform. Owing to the unavailability of the finger-wrinkle open database obtained by smartphone camera, we built the Dongguk finger-wrinkle database, including the images from 33 people. 12 Sigma’s Lung Cancer detection algorithm. The results show that the recognition performance by our method exceeds in those of conventional methods. IBM Watson is Integrated with the Watson Studio to empower cross-functional teams to deploy, monitor, and optimize ML/Deep Learning models quickly and efficiently. Over the past decade, researchers have demonstrated the possibilities to automate the initial lesion detection. Deep learning and edge computing are the emerging technologies, which are used for efficient processing of huge amount of data with distinct accuracy. The FCN-AlexNet of deep learning method was used to segment images, and accurate localization of thyroid nodules was achieved. This, combined with the emergence of drug resistant bacteria in India makes the problem worse [3]. Indeed, we reduced the depth and width of the backbone network of YOLO. Pre-processing gestures are obtained using histogram (OH) with PCA to reduce the dimensions of the traits obtained after OH. The present work proposes a driver drowsiness detection algorithm based on Camera and EEG headset . However, the lack of a common dataset impedes research when comparing the performance of such algorithms. We also provide a systematic detection performance comparison of various models on multiple popular datasets including FlickrLogos-32, TopLogo-10 and recently introduced QMUL-OpenLogo benchmark, which allows for a direct comparison between recently proposed extensions. Finally, extensive experimental results show that their denoiser is effective for those images with a large number of interference pixels which may cause misjudgement. This way, for every periocular region, the CNN receives multiple samples of different ocular classes, forcing it to conclude that such regions should not be considered in its response. Image classification is a pivotal application in the field of deep learning, and hence, you will gain knowledge on various deep learning concepts while working on this project. In the end, the CTDRNet is implemented and evaluated with an accuracy of 96% and processing rate of 2.5 fps. Finally, we present a final network implementation on a Raspberry Pi 3B that demonstrates a detection speed of 1.63 frames per second and an average precision of 0.842. One of them is steganography. This proect deals with analyzing opportunities to perform this in non- iterative way for dental medical images for two versions of a coder based on discrete cosine transform (DCT) – AGU and AGU-M. In this study, they utilise CNN with the multi-layer structure for the removal of salt and pepper noise, which contains padding, batch normalisation and rectified linear unit. The detector and the classifier proposed here are proved to be superior to the state-of-the-art method. This paper improves the network structure of YOLO algorithm and proposes a new network structure YOLO-R. First, three Passthrough layers were added to the original YOLO network. In this project, you will model a chatbot using IBM Watson’s API. Now, you use the motion capture data to train a neural network through reinforcement learning. Reference Paper IEEE 2019 Kinect-Based Platform for Movement Monitoring and Fall-Detection of Elderly People Published in: 2019 12th International Conference on Measurement https://ieeexplore.ieee.org/document/8780004. On top of that, it comes with intuitive dashboards that make it convenient for the teams to manage models in production seamlessly. It is an open-source and easily accessible dataset that is great for a host of MIR tasks, including browsing and organizing vast music collections. Reference Paper IEEE 2019 Fused Convolutional Neural Network for White Blood Cell Image Classification Published in: 2019 International Conference on Artificial Intelligence in Information and Communication (ICAIIC) https://ieeexplore.ieee.org/document/8669049. In this work, custom CNNs and a transfer-learned AlexNet are applied to an experimental data set with artificial defects in order to analyze suitability and required network depth for such surface inspections. Detectron is a Facebook AI Research’s (FAIR) software system designed to execute and run state-of-the-art Object Detection algorithms. In this project, the problem of facial expression is addressed, which contains two different stages: 1. In this work, we present a low-cost strawberry detection system based on convolutional neural networks. Reference Paper IEEE 2019A Fuzzy Expert System Design for Diagnosis of Skin DiseasesPublished in: 2019 2nd International Conference on Advancements in Computational Sciences (ICACS)https://ieeexplore.ieee.org/document/8689140. Hand gesture recognition system and face recognition system has been implemented in this paper using which various tasks can be performed. The system is trained on images drawn randomly from the ImageNet database, and works well on natural images from a wide variety of sources. It includes over 50 pre-trained models and is extremely flexible – it supports rapid implementation and evaluation of novel research. Next, to avoid background influences on objects or noise affecting the ROI, we use the kernelized correlation filters (KCF) algorithm to track the detected ROI. In this paper we present a computational tool for automatic glaucoma detection. In this system, Olivia can interact with the stranger at the door in case the owner is not present at home and will notify the owner about the visit using Email and SMS along with the image of the stranger. This system works by recognizing patterns from finger vein images and these images are captured using a camera based on near-infrared technology. The experimental results demonstrate that our proposed network is superior to three previous state-of-the-art networks. The realtime semantic segmenter S is used to refine the foreground segmentation outputs as feedbacks for improving the model updating accuracy. finger vein-based validation systems are getting extra attraction among other authentication systems due to high security in terms of ensuring data confidentiality. shopping malls have become an integral part of life and people in cities often go to shopping malls in order to purchase their daily requirements. We compare the result of our model accuracy and computational time with CNN-recurrent neural network (RNN) combined model. Three different hardware-architecture variants, two for image watermarking and one for video (pipelined), are proposed, which reutilize the already small arithmetic units in different computation steps, to further reduce implementation cost. There are several different types of traffic signs like speed limits, no … Tool : This project is based on Machine learning… Reference Paper IEEE 2019Published in: 2019 6th International Conference on Signal Processing and Integrated Networks (SPIN)https://ieeexplore.ieee.org/document/8711706. But due to shortage of expertise in rural areas, it is impossible so far. The experimental results shown that the proposed method has better performance in localization and diagnosis of benign and malignant lesions. This method constitutes an essential place in image processing. In the test set, compared with the traditional YOLO V3, the improved algorithm detection accuracy increased by 2.44% with the same detection rate. When you feel confident, you can then tackle the advanced projects. Reference Paper IEEE 2019A Novel Real-time Driver Monitoring System Based on Deep Convolutional Neural NetworkPublished in: 2019 IEEE International Symposium on Robotic and Sensors Environments (ROSE)https://ieeexplore.ieee.org/document/8790428. Two deep CNN architectures are developed in this study that are modified from AlexNet and VGGNet, respectively. However, face recognition performance is greatly influenced by the factors, such as facial expression, illumination, and pose changes. The proposed method is tested on 142 T2-weighted MR scans from the First Affiliated Hospital of Guangzhou Medical University. Reference Paper IEEE 2019Shadow detection and removal from images using machine learning and morphological operationsPublished in: The Journal of Engineering ( Volume: 2019 , Issue: 1 , 1 2019 )https://ieeexplore.ieee.org/document/8627060. As new advances are being made in this domain, it is helping ML and Deep Learning experts to design innovative and functional Deep Learning projects. This is an excellent project to nurture and improve your deep learning skills. Image Colorization 7. Then, we extract the features for an image with the CNN on the basis of a patch by applying a patch-sized sliding-window to scan the whole image. Convolutional recurrent neural network (CRNN) and connectionist text proposal network (CTPN) methods cannot extract container text features effectively. In training, they divide images into three parts: training set, validation set and test set. They designed one of the largest neural networks for ML – it comprised of 16,000 computer processors connected together. Image captioning is the process of generating a textual description for an image. By using mobile application to recognize the face and compares face within their data to checked whether, that user is an automated owner (or) not. Some agricultural tasks that are ideal for robotic automation are yield estimation and robotic harvesting. To protect the copyright of digital videos, video copy detection has become a hot topic in the field of digital copyright protection. The Google Brain project is Deep Learning AI research that began in 2011 at Google. Reference Paper IEEE 2019A Method for Localizing the Eye Pupil for Point-of-Gaze EstimationPublished in: IEEE Potentials ( Volume: 38 , Issue: 1 , Jan.-Feb. 2019 )https://ieeexplore.ieee.org/document/8595416. Binary classification of the obtained visual image data into defect and defect-free sets is one sub-task of these systems and is still often carried out either completely manually by an expert or by using pre-defined features as classifiers for automatic image post-processing. Reference Paper IEEE 2019An Iterative Image Inpainting Method Based on Similarity of Pixels ValuesPublished in: 2019 6th International Conference on Electrical and Electronics Engineering (ICEEE)https://ieeexplore.ieee.org/document/8792492. Results prove the concept and working principle of the devised system, Reference Paper IEEE 2019Scene to Text Conversion and Pronunciation for Visually Impaired PeoplePublished in: 2019 Advances in Science and Engineering Technology International Conferences (ASET)https://ieeexplore.ieee.org/document/8714269. making them smarter. Image Reconstruction 8. The system is smart enough to identify and differentiate between the owner and stranger using face recognition and act accordingly. Accurate segmentation of retinal vessels is a basic step in diabetic retinopathy (DR) detection. Second, the sampled frames of each video clip are fed into a pre-trained CNN model to generate the corresponding convolutional feature maps (CFMs). The experimental results shows that the classification accuracy of this method can reach at 0.60, which is better than the traditional direct training method and has better robustness and generalization. Further, artificial neural network (ANN) is shown to provide better performance than Naive Bayes and K-Nearest Neighbours models. You will create a deep learning model that uses neural networks to classify the genre of music automatically. The experiment show that our network is simple to train and easy to generalize to other datasets, and the mask average precision is nearly up to 98.5% on our own datasets. With these extensions, not only can the hidden information be kept secure, but the system can be used to hide even more than a single image. In the proposed multi-scale information fusion module (MSIF), parallel convolution layers with different dilation rates are used, so that the model can obtain more dense feature information and better capture retinal vessel information of different sizes. The main contribution of this paper is the development of an expert system tool for evaluating the ripeness of banana fruit. In either way you want project on image processing … This paper also changes the layer number of the Passthrough layer connection in the original YOLO algorithm from Layer 16 to Layer 12 to increase the ability of the network to extract the information of the shallow pedestrian features. If you wish to scale it up a notch, you can visit. Experimental results demonstrate that the architecture can effectively remove salt and pepper noise for the various noisy images. Ablation studies are presented to validate the choice of hyper-parameters, framework, and network structure. Additional modifications to both the training data and network structure that improve precision and execution speed, e.g., input compression, image tiling, color masking, and network compression, are discussed. Our system is an upgraded version of the old stress detection systems which excluded the live detection and the personal counseling but ... Real-Time Image Processing and Deep Learning … The analysis result is immediately sent to the farmer required the decision and then feedback from the farmer is reflected to the model. Most of the dumb people are deaf also. to empower cross-functional teams to deploy, monitor, and optimize ML/Deep Learning models quickly and efficiently. This is one of the interesting deep learning project ideas. Firstly, we use skin color detection and morphology to remove unnecessary background information from the image, and then use background subtraction to detect the ROI. Here, you will use Python, OpenCV, and Keras to build a system that can detect the closed eyes of drivers and alert them if ever they fall asleep while driving. Latest updates of the Electronic lab equipment's, This blog post provides best and the latest image processing projects based on Latest scientific journals. As for the test set, it will include 1000 images that are randomly chosen from each of the ten classes. In this paper, we propose an assistive calorie measurement system to help patients and doctors succeed in their fight against diet-related health conditions. The paper describes a deep network based system specialized for ball detection in long shot videos. The alert when opened also shows some coffee shops near the driver’s location to increase the driver’s alertness.

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